Research and Development for Technology Evolution Potential Forecasting System

NASA Astrophysics Data System (ADS)

Gao, Changqing; Cao, Shukun; Wang, Yuzeng; Ai, Changsheng; Ze, Xiangbo

Technology forecasting is a powerful weapon for many enterprises to gain an animate future. Evolutionary potential radar plot is a necessary step of some valuable methods to help the technology managers with right technical strategy. A software system for Technology Evolution Potential Forecasting (TEPF) with automatic radar plot drawing is introduced in this paper. The framework of the system and the date structure describing the concrete evolution pattern are illustrated in details. And the algorithm for radar plot drawing is researched. It is proved that the TEPF system is an effective tool during the technology strategy analyzing process with a referenced case study.

Building the Sun4Cast System: Improvements in Solar Power Forecasting

DOE PAGES

Haupt, Sue Ellen; Kosovic, Branko; Jensen, Tara; ...

2017-06-16

The Sun4Cast System results from a research-to-operations project built on a value chain approach, and benefiting electric utilities’ customers, society, and the environment by improving state-of-the-science solar power forecasting capabilities. As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers.more » The project followed a value chain approach to determine key research and technology needs to reach desired results. Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, the basis of the system beyond about 6 h. For short-range (0-6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short to mid-term irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach, and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed. As a result, this paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.« less

Building the Sun4Cast System: Improvements in Solar Power Forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haupt, Sue Ellen; Kosovic, Branko; Jensen, Tara

The Sun4Cast System results from a research-to-operations project built on a value chain approach, and benefiting electric utilities’ customers, society, and the environment by improving state-of-the-science solar power forecasting capabilities. As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers.more » The project followed a value chain approach to determine key research and technology needs to reach desired results. Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, the basis of the system beyond about 6 h. For short-range (0-6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short to mid-term irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach, and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed. As a result, this paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.« less

Forecasting the VCR: A Retrospective Assessment of Media Trade Press and Academic Forecasts of Its Impact on Broadcasting.

ERIC Educational Resources Information Center

Napoli, Philip M.

Retrospective technology assessment (RTA) is the use of historical research to assess current and future technology issues. This paper uses the introduction of the videocassette recorder (VCR) as an RTA case study, focusing on the broadcasting and advertising trade presses and their forecasts of the VCR's potential impact on broadcasting. Trade…

Past speculations of the future: a review of the methods used for forecasting emerging health technologies.

PubMed

Doos, Lucy; Packer, Claire; Ward, Derek; Simpson, Sue; Stevens, Andrew

2016-03-10

Forecasting can support rational decision-making around the introduction and use of emerging health technologies and prevent investment in technologies that have limited long-term potential. However, forecasting methods need to be credible. We performed a systematic search to identify the methods used in forecasting studies to predict future health technologies within a 3-20-year timeframe. Identification and retrospective assessment of such methods potentially offer a route to more reliable prediction. Systematic search of the literature to identify studies reported on methods of forecasting in healthcare. People are not needed in this study. The authors searched MEDLINE, EMBASE, PsychINFO and grey literature sources, and included articles published in English that reported their methods and a list of identified technologies. Studies reporting methods used to predict future health technologies within a 3-20-year timeframe with an identified list of individual healthcare technologies. Commercially sponsored reviews, long-term futurology studies (with over 20-year timeframes) and speculative editorials were excluded. 15 studies met our inclusion criteria. Our results showed that the majority of studies (13/15) consulted experts either alone or in combination with other methods such as literature searching. Only 2 studies used more complex forecasting tools such as scenario building. The methodological fundamentals of formal 3-20-year prediction are consistent but vary in details. Further research needs to be conducted to ascertain if the predictions made were accurate and whether accuracy varies by the methods used or by the types of technologies identified. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Forecasting new product diffusion using both patent citation and web search traffic.

PubMed

Lee, Won Sang; Choi, Hyo Shin; Sohn, So Young

2018-01-01

Accurate demand forecasting for new technology products is a key factor in the success of a business. We propose a way to forecasting a new product's diffusion through technology diffusion and interest diffusion. Technology diffusion and interest diffusion are measured by the volume of patent citations and web search traffic, respectively. We apply the proposed method to forecast the sales of hybrid cars and industrial robots in the US market. The results show that that technology diffusion, as represented by patent citations, can explain long-term sales for hybrid cars and industrial robots. On the other hand, interest diffusion, as represented by web search traffic, can help to improve the predictability of market sales of hybrid cars in the short-term. However, interest diffusion is difficult to explain the sales of industrial robots due to the different market characteristics. Finding indicates our proposed model can relatively well explain the diffusion of consumer goods.

MERIT: A man/computer data management and enhancement system for upper air nowcasting/forecasting in the United States. [Minimum Energy Routes using Interactive Techniques (MERIT)

NASA Technical Reports Server (NTRS)

Steinberg, R.

1984-01-01

It is suggested that the very short range forecast problem for aviation is one of data management rather than model development and the possibility of improving the aviation forecast using current technology is underlined. The MERIT concept of modeling technology, and advanced man/computer interactive data management and enhancement techniques to provide a tailored, accurate and timely forecast for aviation is outlined. The MERIT includes utilization of the Langrangian approach, extensive use of the automated aircraft report to complement the present data base and provide the most current observations; and the concept that a 2 to 12 hour forecast provided every 3 hr can meet the domestic needs of aviation instead of the present 18 and 24 hr forecast provided every 12 hr.

A forecast of broadcast satellite communications

NASA Technical Reports Server (NTRS)

Martino, J. P.; Lenz, R. C., Jr.

1977-01-01

This paper presents forecasts of likely changes in broadcast satellite technology, the technology of ground terminals, and the technology of terrestrial communications competitive with satellites. The impacts of these changes in technology are then assessed, using a cross-impact model of U.S. domestic telecommunications, to determine the consequences of various possible changes in communications satellite technology. These consequences are discussed in terms of various possible services, for households, businesses, and specialized customers, which might become economically viable as a result of improvements in satellite technology.

Solar and Wind Forecasting | Grid Modernization | NREL

Science.gov Websites

and Wind Forecasting Solar and Wind Forecasting As solar and wind power become more common system operators. An aerial photo of the National Wind Technology Center's PV arrays. Capabilities value of accurate forecasting Wind power visualization to direct questions and feedback during industry

Computers and Technological Forecasting

ERIC Educational Resources Information Center

Martino, Joseph P.

1971-01-01

Forecasting is becoming increasingly automated, thanks in large measure to the computer. It is now possible for a forecaster to submit his data to a computation center and call for the appropriate program. (No knowledge of statistics is required.) (Author)

New Technology Trends in Education: Seven Years of Forecasts and Convergence

ERIC Educational Resources Information Center

Martin, Sergio; Diaz, Gabriel; Sancristobal, Elio; Gil, Rosario; Castro, Manuel; Peire, Juan

2011-01-01

Each year since 2004, a new Horizon Report has been released. Each edition attempts to forecast the most promising technologies likely to impact on education along three horizons: the short term (the year of the report), the mid-term (the next 2 years) and the long term (the next 4 years). This paper analyzes the evolution of technology trends…

An Early Prediction of Sunspot Cycle 25

NASA Astrophysics Data System (ADS)

Nandy, D.; Bhowmik, P.

2017-12-01

The Sun's magnetic activity governs our space environment, creates space weather and impacts our technologies and climate. With increasing reliance on space- and ground-based technologies that are subject to space weather, the need to be able to forecast the future activity of the Sun has assumed increasing importance. However, such long-range, decadal-scale space weather prediction has remained a great challenge as evident in the diverging forecasts for solar cycle 24. Based on recently acquired understanding of the physics of solar cycle predictability, we have devised a scheme to extend the forecasting window of solar cycles. Utilizing this we present an early forecast for sunspot cycle 25 which would be of use for space mission planning, satellite life-time estimates, and assessment of the long-term impacts of space weather on technological assets and planetary atmospheres.

The Gods of the Copybook Headings: A Caution to Forecasters.

ERIC Educational Resources Information Center

Martino, Joseph P.

1984-01-01

Technological forecasters often fail to recognize the whole range of changing circumstances that may affect their predictions. Drawing on his own broad experience, the author offers basic reminders to those who set out to gauge the direction of future changes in technology. (IM)

Forecasting new product diffusion using both patent citation and web search traffic

PubMed Central

Lee, Won Sang; Choi, Hyo Shin

2018-01-01

Accurate demand forecasting for new technology products is a key factor in the success of a business. We propose a way to forecasting a new product’s diffusion through technology diffusion and interest diffusion. Technology diffusion and interest diffusion are measured by the volume of patent citations and web search traffic, respectively. We apply the proposed method to forecast the sales of hybrid cars and industrial robots in the US market. The results show that that technology diffusion, as represented by patent citations, can explain long-term sales for hybrid cars and industrial robots. On the other hand, interest diffusion, as represented by web search traffic, can help to improve the predictability of market sales of hybrid cars in the short-term. However, interest diffusion is difficult to explain the sales of industrial robots due to the different market characteristics. Finding indicates our proposed model can relatively well explain the diffusion of consumer goods. PMID:29630616

2020 Vision: Experts Forecast What the Digital Revolution Will Bring Next

ERIC Educational Resources Information Center

T.H.E. Journal, 2010

2010-01-01

In this article, a trio of current and former federal ed tech honchos, as well as a host of technology leaders nationwide, offer their forecasts, while also considering the lessons the first chapters of digital age have left behind. A timeline of learning technologies is also included.

A Fifteen-Year Forecast of Information-Processing Technology. Final Report.

ERIC Educational Resources Information Center

Bernstein, George B.

This study developed a variation of the DELPHI approach, a polling technique for systematically soliciting opinions from experts, to produce a technological forecast of developments in the information-processing industry. SEER (System for Event Evaluation and Review) combines the more desirable elements of existing techniques: (1) intuitive…

Spaceborne sensors (1983-2000 AD): A forecast of technology

NASA Technical Reports Server (NTRS)

Kostiuk, T.; Clark, B. P.

1984-01-01

A technical review and forecast of space technology as it applies to spaceborne sensors for future NASA missions is presented. A format for categorization of sensor systems covering the entire electromagnetic spectrum, including particles and fields is developed. Major generic sensor systems are related to their subsystems, components, and to basic research and development. General supporting technologies such as cryogenics, optical design, and data processing electronics are addressed where appropriate. The dependence of many classes of instruments on common components, basic R&D and support technologies is also illustrated. A forecast of important system designs and instrument and component performance parameters is provided for the 1983-2000 AD time frame. Some insight into the scientific and applications capabilities and goals of the sensor systems is also given.

New product forecasting with limited or no data

NASA Astrophysics Data System (ADS)

Ismai, Zuhaimy; Abu, Noratikah; Sufahani, Suliadi

2016-10-01

In the real world, forecasts would always be based on historical data with the assumption that the behaviour be the same for the future. But how do we forecast when there is no such data available? New product or new technologies normally has limited amount of data available. Knowing that forecasting is valuable for decision making, this paper presents forecasting of new product or new technologies using aggregate diffusion models and modified Bass Model. A newly launched Proton car and its penetration was chosen to demonstrate the possibility of forecasting sales demand where there is limited or no data available. The model was developed to forecast diffusion of new vehicle or an innovation in the Malaysian society. It is to represent the level of spread on the new vehicle among a given set of the society in terms of a simple mathematical function that elapsed since the introduction of the new product. This model will forecast the car sales volume. A procedure of the proposed diffusion model was designed and the parameters were estimated. Results obtained by applying the proposed diffusion model and numerical calculation shows that the model is robust and effective for forecasting demand of the new vehicle. The results reveal that newly developed modified Bass diffusion of demand function has significantly contributed for forecasting the diffusion of new Proton car or new product.

Impact of improved information on the structure of world grain trade. [wheat

NASA Technical Reports Server (NTRS)

1979-01-01

The benefits to be derived by the United States from improvements in global grain crop forecasting capability are discussed. The improvements in forecasting accuracy, which are a result of the use of satellite technology in conjunction with existing ground based estimating procedures are described. The degree of forecasting accuracy to be obtained from satellite technology is also examined. Specific emphasis is placed on wheat production in seven countries/regions: the United States; Canada; Argentina; Australia; Western Europe; the USSR; and all other countries in a group.

Potential Technologies for Assessing Risk Associated with a Mesoscale Forecast

DTIC Science & Technology

2015-10-01

American GFS models, and informally applied on the Weather Research and Forecasting ( WRF ) model. The current CI equation is as follows...Reen B, Penc R. Investigating surface bias errors in the Weather Research and Forecasting ( WRF ) model using a Geographic Information System (GIS). J...Forecast model ( WRF -ARW) with extensions that might include finer terrain resolutions and more detailed representations of the underlying atmospheric

Operational flash flood forecasting platform based on grid technology

NASA Astrophysics Data System (ADS)

Thierion, V.; Ayral, P.-A.; Angelini, V.; Sauvagnargues-Lesage, S.; Nativi, S.; Payrastre, O.

2009-04-01

Flash flood events of south of France such as the 8th and 9th September 2002 in the Grand Delta territory caused important economic and human damages. Further to this catastrophic hydrological situation, a reform of flood warning services have been initiated (set in 2006). Thus, this political reform has transformed the 52 existing flood warning services (SAC) in 22 flood forecasting services (SPC), in assigning them territories more hydrological consistent and new effective hydrological forecasting mission. Furthermore, national central service (SCHAPI) has been created to ease this transformation and support local services in their new objectives. New functioning requirements have been identified: - SPC and SCHAPI carry the responsibility to clearly disseminate to public organisms, civil protection actors and population, crucial hydrologic information to better anticipate potential dramatic flood event, - a new effective hydrological forecasting mission to these flood forecasting services seems essential particularly for the flash floods phenomenon. Thus, models improvement and optimization was one of the most critical requirements. Initially dedicated to support forecaster in their monitoring mission, thanks to measuring stations and rainfall radar images analysis, hydrological models have to become more efficient in their capacity to anticipate hydrological situation. Understanding natural phenomenon occuring during flash floods mainly leads present hydrological research. Rather than trying to explain such complex processes, the presented research try to manage the well-known need of computational power and data storage capacities of these services. Since few years, Grid technology appears as a technological revolution in high performance computing (HPC) allowing large-scale resource sharing, computational power using and supporting collaboration across networks. Nowadays, EGEE (Enabling Grids for E-science in Europe) project represents the most important effort in term of grid technology development. This paper presents an operational flash flood forecasting platform which have been developed in the framework of CYCLOPS European project providing one of virtual organizations of EGEE project. This platform has been designed to enable multi-simulations processes to ease forecasting operations of several supervised watersheds on Grand Delta (SPC-GD) territory. Grid technology infrastructure, in providing multiple remote computing elements enables the processing of multiple rainfall scenarios, derived to the original meteorological forecasting transmitted by Meteo-France, and their respective hydrological simulations. First results show that from one forecasting scenario, this new presented approach can permit simulations of more than 200 different scenarios to support forecasters in their aforesaid mission and appears as an efficient hydrological decision-making tool. Although, this system seems operational, model validity has to be confirmed. So, further researches are necessary to improve models core to be more efficient in term of hydrological aspects. Finally, this platform could be an efficient tool for developing others modelling aspects as calibration or data assimilation in real time processing.

Advances in the development of remote sensing technology for agricultural applications

NASA Technical Reports Server (NTRS)

Powers, J. E.; Erb, R. B.; Hall, F. G.; Macdonald, R. B.

1979-01-01

The application of remote sensing technology to crop forecasting is discussed. The importance of crop forecasts to the world economy and agricultural management is explained, and the development of aerial and spaceborne remote sensing for global crop forecasting by the United States is outlined. The structure, goals and technical aspects of the Large Area Crop Inventory Experiment (LACIE) are presented, and main findings on the accuracy, efficiency, applicability and areas for further study of the LACIE procedure are reviewed. The current status of NASA crop forecasting activities in the United States and worldwide is discussed, and the objectives and organization of the newly created Agriculture and Resources Inventory Surveys through Aerospace Remote Sensing (AgRISTARS) program are presented.

Regional early flood warning system: design and implementation

NASA Astrophysics Data System (ADS)

Chang, L. C.; Yang, S. N.; Kuo, C. L.; Wang, Y. F.

2017-12-01

This study proposes a prototype of the regional early flood inundation warning system in Tainan City, Taiwan. The AI technology is used to forecast multi-step-ahead regional flood inundation maps during storm events. The computing time is only few seconds that leads to real-time regional flood inundation forecasting. A database is built to organize data and information for building real-time forecasting models, maintaining the relations of forecasted points, and displaying forecasted results, while real-time data acquisition is another key task where the model requires immediately accessing rain gauge information to provide forecast services. All programs related database are constructed in Microsoft SQL Server by using Visual C# to extracting real-time hydrological data, managing data, storing the forecasted data and providing the information to the visual map-based display. The regional early flood inundation warning system use the up-to-date Web technologies driven by the database and real-time data acquisition to display the on-line forecasting flood inundation depths in the study area. The friendly interface includes on-line sequentially showing inundation area by Google Map, maximum inundation depth and its location, and providing KMZ file download of the results which can be watched on Google Earth. The developed system can provide all the relevant information and on-line forecast results that helps city authorities to make decisions during typhoon events and make actions to mitigate the losses.

NWS Operational Requirements for Ensemble-Based Hydrologic Forecasts

NASA Astrophysics Data System (ADS)

Hartman, R. K.

2008-12-01

Ensemble-based hydrologic forecasts have been developed and issued by National Weather Service (NWS) staff at River Forecast Centers (RFCs) for many years. Used principally for long-range water supply forecasts, only the uncertainty associated with weather and climate have been traditionally considered. As technology and societal expectations of resource managers increase, the use and desire for risk-based decision support tools has also increased. These tools require forecast information that includes reliable uncertainty estimates across all time and space domains. The development of reliable uncertainty estimates associated with hydrologic forecasts is being actively pursued within the United States and internationally. This presentation will describe the challenges, components, and requirements for operational hydrologic ensemble-based forecasts from the perspective of a NOAA/NWS River Forecast Center.

Development and Application of Advanced Weather Prediction Technologies for the Wind Energy Industry (Invited)

NASA Astrophysics Data System (ADS)

Mahoney, W. P.; Wiener, G.; Liu, Y.; Myers, W.; Johnson, D.

2010-12-01

Wind energy decision makers are required to make critical judgments on a daily basis with regard to energy generation, distribution, demand, storage, and integration. Accurate knowledge of the present and future state of the atmosphere is vital in making these decisions. As wind energy portfolios expand, this forecast problem is taking on new urgency because wind forecast inaccuracies frequently lead to substantial economic losses and constrain the national expansion of renewable energy. Improved weather prediction and precise spatial analysis of small-scale weather events are crucial for renewable energy management. In early 2009, the National Center for Atmospheric Research (NCAR) began a collaborative project with Xcel Energy Services, Inc. to perform research and develop technologies to improve Xcel Energy's ability to increase the amount of wind energy in their generation portfolio. The agreement and scope of work was designed to provide highly detailed, localized wind energy forecasts to enable Xcel Energy to more efficiently integrate electricity generated from wind into the power grid. The wind prediction technologies are designed to help Xcel Energy operators make critical decisions about powering down traditional coal and natural gas-powered plants when sufficient wind energy is predicted. The wind prediction technologies have been designed to cover Xcel Energy wind resources spanning a region from Wisconsin to New Mexico. The goal of the project is not only to improve Xcel Energy’s wind energy prediction capabilities, but also to make technological advancements in wind and wind energy prediction, expand our knowledge of boundary layer meteorology, and share the results across the renewable energy industry. To generate wind energy forecasts, NCAR is incorporating observations of current atmospheric conditions from a variety of sources including satellites, aircraft, weather radars, ground-based weather stations, wind profilers, and even wind sensors on individual wind turbines. The information is utilized by several technologies including: a) the Weather Research and Forecasting (WRF) model, which generates finely detailed simulations of future atmospheric conditions, b) the Real-Time Four-Dimensional Data Assimilation System (RTFDDA), which performs continuous data assimilation providing the WRF model with continuous updates of the initial atmospheric state, 3) the Dynamic Integrated Forecast System (DICast®), which statistically optimizes the forecasts using all predictors, and 4) a suite of wind-to-power algorithms that convert wind speed to power for a wide range of wind farms with varying real-time data availability capabilities. In addition to these core wind energy prediction capabilities, NCAR implemented a high-resolution (10 km grid increment) 30-member ensemble RTFDDA prediction system that provides information on the expected range of wind power over a 72-hour forecast period covering Xcel Energy’s service areas. This talk will include descriptions of these capabilities and report on several topics including initial results of next-day forecasts and nowcasts of wind energy ramp events, influence of local observations on forecast skill, and overall lessons learned to date.

Future Weather Forecasting in the Year 2020-Investing in Technology Today: Improving Weather and Environmental Predictions

NASA Technical Reports Server (NTRS)

Anthes, Richard; Schoeberl, Mark

2000-01-01

Fast-forward twenty years to the nightly simultaneous TV/webcast. Accurate 8-14 day regional forecasts will be available as will be a whole host of linked products including economic impact, travel, energy usage, etc. On-demand, personalized street-level forecasts will be downloaded into your PDA. Your home system will automatically update the products of interest to you (e.g. severe storm forecasts, hurricane predictions, etc). Short and long range climate forecasts will be used by your "Quicken 2020" to make suggest changes in your "futures" investment portfolio. Through a lively and informative multi-media presentation, leading Space-Earth Science Researchers and Technologists will share their vision for the year 2020, offering a possible futuristic forecast enabled through the application of new technologies under development today. Copies of the 'broadcast' will be available on Beta Tape for your own future use. If sufficient interest exists, the program may also be made available for broadcasters wishing to do stand-ups with roll-ins from the San Francisco meeting for their viewers back home.

Multidisciplinary studies of the social, economic and political impact resulting from recent advances in satellite meteorology. Volume 6: Executive summary. [technological forecasting spacecraft control/attitude (inclination) -classical mechanics

NASA Technical Reports Server (NTRS)

1975-01-01

An assessment of the technological impact of modern satellite weather forecasting for the United States is presented. Topics discussed are: (1) television broadcasting of weather; (2) agriculture (crop production); (3) water resources; (4) urban development; (5) recreation; and (6) transportation.

Workshop for transportation forecasters

DOT National Transportation Integrated Search

2009-01-01

On September 22-23, 2009, the U.S. Department of Transportation, Research and Innovative Technology Administration's - Bureau of Transportation Statistics is hosted an international workshop on transportation forecasting in Washington, D.C. Topics fo...

Financial options methodology for analyzing investments in new technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wenning, B.D.

1994-12-31

The evaluation of investments in longer term research and development in emerging technologies, because of the nature of such subjects, must address inherent uncertainties. Most notably, future cash flow forecasts include substantial uncertainties. Conventional present value methodology, when applied to emerging technologies severely penalizes cash flow forecasts, and strategic investment opportunities are at risk of being neglected. Use of options valuation methodology adapted from the financial arena has been introduced as having applicability in such technology evaluations. Indeed, characteristics of superconducting magnetic energy storage technology suggest that it is a candidate for the use of options methodology when investment decisionsmore » are being contemplated.« less

Financial options methodology for analyzing investments in new technology

NASA Technical Reports Server (NTRS)

Wenning, B. D.

1995-01-01

The evaluation of investments in longer term research and development in emerging technologies, because of the nature of such subjects, must address inherent uncertainties. Most notably, future cash flow forecasts include substantial uncertainties. Conventional present value methodology, when applied to emerging technologies severely penalizes cash flow forecasts, and strategic investment opportunities are at risk of being neglected. Use of options evaluation methodology adapted from the financial arena has been introduced as having applicability in such technology evaluations. Indeed, characteristics of superconducting magnetic energy storage technology suggest that it is a candidate for the use of options methodology when investment decisions are being contemplated.

Future Research in Health Information Technology: A Review.

PubMed

Hemmat, Morteza; Ayatollahi, Haleh; Maleki, Mohammad Reza; Saghafi, Fatemeh

2017-01-01

Currently, information technology is considered an important tool to improve healthcare services. To adopt the right technologies, policy makers should have adequate information about present and future advances. This study aimed to review and compare studies with a focus on the future of health information technology. This review study was completed in 2015. The databases used were Scopus, Web of Science, ProQuest, Ovid Medline, and PubMed. Keyword searches were used to identify papers and materials published between 2000 and 2015. Initially, 407 papers were obtained, and they were reduced to 11 papers at the final stage. The selected papers were described and compared in terms of the country of origin, objective, methodology, and time horizon. The papers were divided into two groups: those forecasting the future of health information technology (seven papers) and those providing health information technology foresight (four papers). The results showed that papers related to forecasting the future of health information technology were mostly a literature review, and the time horizon was up to 10 years in most of these studies. In the health information technology foresight group, most of the studies used a combination of techniques, such as scenario building and Delphi methods, and had long-term objectives. To make the most of an investment and to improve planning and successful implementation of health information technology, a strategic plan for the future needs to be set. To achieve this aim, methods such as forecasting the future of health information technology and offering health information technology foresight can be applied. The forecasting method is used when the objectives are not very large, and the foresight approach is recommended when large-scale objectives are set to be achieved. In the field of health information technology, the results of foresight studies can help to establish realistic long-term expectations of the future of health information technology.

Future Research in Health Information Technology: A Review

PubMed Central

Hemmat, Morteza; Ayatollahi, Haleh; Maleki, Mohammad Reza; Saghafi, Fatemeh

2017-01-01

Introduction Currently, information technology is considered an important tool to improve healthcare services. To adopt the right technologies, policy makers should have adequate information about present and future advances. This study aimed to review and compare studies with a focus on the future of health information technology. Method This review study was completed in 2015. The databases used were Scopus, Web of Science, ProQuest, Ovid Medline, and PubMed. Keyword searches were used to identify papers and materials published between 2000 and 2015. Initially, 407 papers were obtained, and they were reduced to 11 papers at the final stage. The selected papers were described and compared in terms of the country of origin, objective, methodology, and time horizon. Results The papers were divided into two groups: those forecasting the future of health information technology (seven papers) and those providing health information technology foresight (four papers). The results showed that papers related to forecasting the future of health information technology were mostly a literature review, and the time horizon was up to 10 years in most of these studies. In the health information technology foresight group, most of the studies used a combination of techniques, such as scenario building and Delphi methods, and had long-term objectives. Conclusion To make the most of an investment and to improve planning and successful implementation of health information technology, a strategic plan for the future needs to be set. To achieve this aim, methods such as forecasting the future of health information technology and offering health information technology foresight can be applied. The forecasting method is used when the objectives are not very large, and the foresight approach is recommended when large-scale objectives are set to be achieved. In the field of health information technology, the results of foresight studies can help to establish realistic long-term expectations of the future of health information technology. PMID:28566991

The System of Inventory Forecasting in PT. XYZ by using the Method of Holt Winter Multiplicative

NASA Astrophysics Data System (ADS)

Shaleh, W.; Rasim; Wahyudin

2018-01-01

Problems at PT. XYZ currently only rely on manual bookkeeping, then the cost of production will swell and all investments invested to be less to predict sales and inventory of goods. If the inventory prediction of goods is to large, then the cost of production will swell and all investments invested to be less efficient. Vice versa, if the inventory prediction is too small it will impact on consumers, so that consumers are forced to wait for the desired product. Therefore, in this era of globalization, the development of computer technology has become a very important part in every business plan. Almost of all companies, both large and small, use computer technology. By utilizing computer technology, people can make time in solving complex business problems. Computer technology for companies has become an indispensable activity to provide enhancements to the business services they manage but systems and technologies are not limited to the distribution model and data processing but the existing system must be able to analyze the possibilities of future company capabilities. Therefore, the company must be able to forecast conditions and circumstances, either from inventory of goods, force, or profits to be obtained. To forecast it, the data of total sales from December 2014 to December 2016 will be calculated by using the method of Holt Winters, which is the method of time series prediction (Multiplicative Seasonal Method) it is seasonal data that has increased and decreased, also has 4 equations i.e. Single Smoothing, Trending Smoothing, Seasonal Smoothing and Forecasting. From the results of research conducted, error value in the form of MAPE is below 1%, so it can be concluded that forecasting with the method of Holt Winter Multiplicative.

Space weather forecasting: Past, Present, Future

NASA Astrophysics Data System (ADS)

Lanzerotti, L. J.

2012-12-01

There have been revolutionary advances in electrical technologies over the last 160 years. The historical record demonstrates that space weather processes have often provided surprises in the implementation and operation of many of these technologies. The historical record also demonstrates that as the complexity of systems increase, including their interconnectedness and interoperability, they can become more susceptible to space weather effects. An engineering goal, beginning during the decades following the 1859 Carrington event, has been to attempt to forecast solar-produced disturbances that could affect technical systems, be they long grounded conductor-based or radio-based or required for exploration, or the increasingly complex systems immersed in the space environment itself. Forecasting of space weather events involves both frontier measurements and models to address engineering requirements, and industrial and governmental policies that encourage and permit creativity and entrepreneurship. While analogies of space weather forecasting to terrestrial weather forecasting are frequently made, and while many of the analogies are valid, there are also important differences. This presentation will provide some historical perspectives on the forecast problem, a personal assessment of current status of several areas including important policy issues, and a look into the not-too-distant future.

Assessment of historical and projected segments of US and world civil and military rotorcraft markets, 1960 - 1990

NASA Technical Reports Server (NTRS)

Yates, W. J.

1981-01-01

The geographic climatic, political, economic and demographic environment of 75 countries was analyzed with respect to helicopter procurement history and usage. Key environmental indicators which are variables were projected into strengths and weaknesses of U.S. technology are reviewed. The civil market sensitivity to new technology is forecast with selected premises as to vehicle life, noise standards, fuel costs, GNP expansion and traffic growth. The forecast is based on a scenario of helicopter technology improvements resulting in increased size and performance.

Report of the Panel on Computer and Information Technology

NASA Technical Reports Server (NTRS)

Lundstrom, Stephen F.; Larsen, Ronald L.

1984-01-01

Aircraft have become more and more dependent on computers (information processing) for improved performance and safety. It is clear that this activity will grow, since information processing technology has advanced by a factor of 10 every 5 years for the past 35 years and will continue to do so. Breakthroughs in device technology, from vacuum tubes through transistors to integrated circuits, contribute to this rapid pace. This progress is nearly matched by similar, though not as dramatic, advances in numerical software and algorithms. Progress has not been easy. Many technical and nontechnical challenges were surmounted. The outlook is for continued growth in capability but will require surmounting new challenges. The technology forecast presented in this report has been developed by extrapolating current trends and assessing the possibilities of several high-risk research topics. In the process, critical problem areas that require research and development emphasis have been identified. The outlook assumes a positive perspective; the projected capabilities are possible by the year 2000, and adequate resources will be made available to achieve them. Computer and information technology forecasts and the potential impacts of this technology on aeronautics are identified. Critical issues and technical challenges underlying the achievement of forecasted performance and benefits are addressed.

Forty and 80 GHz technology assessment and forecast including executive summary

NASA Technical Reports Server (NTRS)

Mazur, D. G.; Mackey, R. J., Jr.; Tanner, S. G.; Altman, F. J.; Nicholas, J. J., Jr.; Duchaine, K. A.

1976-01-01

The results of a survey to determine current demand and to forecast growth in demand for use of the 40 and 80 GHz bands during the 1980-2000 time period are given. The current state-of-the-art is presented, as well as the technology requirements of current and projected services. Potential developments were identified, and a forecast is made. The impacts of atmospheric attenuation in the 40 and 80 GHz bands were estimated for both with and without diversity. Three services for the 1980-2000 time period -- interactive television, high quality three stereo pair audio, and 30 MB data -- are given with system requirements and up and down-link calculations.

Demand forecast model based on CRM

NASA Astrophysics Data System (ADS)

Cai, Yuancui; Chen, Lichao

2006-11-01

With interiorizing day by day management thought that regarding customer as the centre, forecasting customer demand becomes more and more important. In the demand forecast of customer relationship management, the traditional forecast methods have very great limitation because much uncertainty of the demand, these all require new modeling to meet the demands of development. In this paper, the notion is that forecasting the demand according to characteristics of the potential customer, then modeling by it. The model first depicts customer adopting uniform multiple indexes. Secondly, the model acquires characteristic customers on the basis of data warehouse and the technology of data mining. The last, there get the most similar characteristic customer by their comparing and forecast the demands of new customer by the most similar characteristic customer.

A Study to Determine the Evolution of Advances in Medical Technology Expected in the Next 25 Years and Possible Impacts on Coast Guard Operation and Support Programs. Appendix D. Literature Search of Forecasts Relevant to Medical Technologies.

DTIC Science & Technology

1980-05-01

Medicine - Biomedicine Related Subjects: Drugs * 1’ 136 Forecast: Minoxidil , an experimental drug for reducing high blood pressure is also proven to be...Derived by The Futures Group from: Sannerstedt, Rune, et.al., " Minoxidil : Haemodynamic and Clinical Experiences With a New Peripheral Vasodilator

The Creation and Application of Two Innovative Real-Time Delphi and Cross-Impact Simulation Approaches to Forecast the Future: Forecasting High-Speed Broadband Developments for the State of Hawai`i

ERIC Educational Resources Information Center

Bergo, Rolv Alexander

2013-01-01

Technology development is moving rapidly and our dependence on information services is growing. Building a broadband infrastructure that can support future demand and change is therefore critical to social, political, economic and technological developments. It is often up to local policy makers to find the best solutions to support this demand…

Military needs and forecast, 2

NASA Technical Reports Server (NTRS)

Goldstayn, Alan B.

1986-01-01

FORECAST 2 has accomplished its objectives of identifying high leverage technologies for corporate Air Force review. Implementation is underway with emphasis on restructuring existing programs and programming resources in the FY88 BES/FY89 POM. Many joint service/agency opportunities exist.

The social function of technology assessment

NASA Technical Reports Server (NTRS)

Huddle, F. P.

1972-01-01

The problem of preserving the uneasy balance between a dynamic society and the equilibrium of man-environment society is discussed. Four sets of activities involved in technology assessment are considered: (1) Technology forecasting is necessary to warn of future dangers and opportunities, for effective timing, and to identify tradeoffs and alternatives. But forecasting is also chancy at best. (2) Social indicators need to be developed for the characterization of social status and measurement of social progress, as well as a better understanding of social needs. (3) With respect to technology assessment, the conflict between profitable directions of innovations and socially desirable directions is described, and a systematic way is needed to determine in advance what is technologically feasible to meet social needs. (4) National goals with respect to scientific and technological developments are also required.

Man-made Boards Technology Trends based on TRIZ Evolution Theory

NASA Astrophysics Data System (ADS)

Yu, Huiling; Fan, Delin

China is one of the world's largest manufacturers and consumers of man-made board applications. A systematic and efficient method of foreseeing future technology trends and their evolutionary potentials is a key task that can help companies guide their planning and allocate their resources. Application of the law of evolution with a S-shaped curve could contribute essentially to the accuracy of the long-term forecast. This research seeks to determine the current stage and the position on the S-curve of man-made board technology in China on the TRIZ evolution theo ryand introduce a methodology which combines patent analysis and technology life cycle forecasting to find a niche space of man-made technology development in China.

An Integrated Urban Flood Analysis System in South Korea

NASA Astrophysics Data System (ADS)

Moon, Young-Il; Kim, Min-Seok; Yoon, Tae-Hyung; Choi, Ji-Hyeok

2017-04-01

Due to climate change and the rapid growth of urbanization, the frequency of concentrated heavy rainfall has caused urban floods. As a result, we studied climate change in Korea and developed an integrated flood analysis system that systematized technology to quantify flood risk and flood forecasting in urban areas. This system supports synthetic decision-making through real-time monitoring and prediction on flash rain or short-term rainfall by using radar and satellite information. As part of the measures to deal with the increase of inland flood damage, we have found it necessary to build a systematic city flood prevention system that systematizes technology to quantify flood risk as well as flood forecast, taking into consideration both inland and river water. This combined inland-river flood analysis system conducts prediction on flash rain or short-term rainfall by using radar and satellite information and performs prompt and accurate prediction on the inland flooded area. In addition, flood forecasts should be accurate and immediate. Accurate flood forecasts signify that the prediction of the watch, warning time and water level is precise. Immediate flood forecasts represent the forecasts lead time which is the time needed to evacuate. Therefore, in this study, in order to apply rainfall-runoff method to medium and small urban stream for flood forecasts, short-term rainfall forecasting using radar is applied to improve immediacy. Finally, it supports synthetic decision-making for prevention of flood disaster through real-time monitoring. Keywords: Urban Flood, Integrated flood analysis system, Rainfall forecasting, Korea Acknowledgments This research was supported by a grant (16AWMP-B066744-04) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport of Korean government.

PEOPLE IN PHYSICS: Interview with Heather Reid

NASA Astrophysics Data System (ADS)

Kibble, Conducted by Bob

2000-09-01

Heather Reid is Scotland's best known weather forecaster. She does not just present the forecast on television but has to rely on her science education and use modern technology to create it first. She is also active in other scientific areas.

NREL and IBM Improve Solar Forecasting with Big Data | Energy Systems

Science.gov Websites

forecasting model using deep-machine-learning technology. The multi-scale, multi-model tool, named Watt-sun the first standard suite of metrics for this purpose. Validating Watt-sun at multiple sites across the

Interactive Forecasting with the National Weather Service River Forecast System

NASA Technical Reports Server (NTRS)

Smith, George F.; Page, Donna

1993-01-01

The National Weather Service River Forecast System (NWSRFS) consists of several major hydrometeorologic subcomponents to model the physics of the flow of water through the hydrologic cycle. The entire NWSRFS currently runs in both mainframe and minicomputer environments, using command oriented text input to control the system computations. As computationally powerful and graphically sophisticated scientific workstations became available, the National Weather Service (NWS) recognized that a graphically based, interactive environment would enhance the accuracy and timeliness of NWS river and flood forecasts. Consequently, the operational forecasting portion of the NWSRFS has been ported to run under a UNIX operating system, with X windows as the display environment on a system of networked scientific workstations. In addition, the NWSRFS Interactive Forecast Program was developed to provide a graphical user interface to allow the forecaster to control NWSRFS program flow and to make adjustments to forecasts as necessary. The potential market for water resources forecasting is immense and largely untapped. Any private company able to market the river forecasting technologies currently developed by the NWS Office of Hydrology could provide benefits to many information users and profit from providing these services.

Jet aircraft emissions during cruise: Present and future

NASA Technical Reports Server (NTRS)

Grobman, J. S.

1975-01-01

Forecasts of engine exhaust emissions that may be practicably achievable for future commercial aircraft operating at high altitude cruise conditions are compared to cruise emission for present day aircraft. The forecasts are based on: (1) knowledge of emission characteristics of combustors and augmentors; (2) combustion research in emission reduction technology, and (3) trends in projected engine designs for advanced subsonic or supersonic commercial aircraft. Recent progress that was made in the evolution of emissions reduction technology is discussed.

Technology requirements for communication satellites in the 1980's

NASA Technical Reports Server (NTRS)

Burtt, J. E.; Moe, C. R.; Elms, R. V.; Delateur, L. A.; Sedlacek, W. C.; Younger, G. G.

1973-01-01

The key technology requirements are defined for meeting the forecasted demands for communication satellite services in the 1985 to 1995 time frame. Evaluation is made of needs for services and technical and functional requirements for providing services. The future growth capabilities of the terrestrial telephone network, cable television, and satellite networks are forecasted. The impact of spacecraft technology and booster performance and costs upon communication satellite costs are analyzed. Systems analysis techniques are used to determine functional requirements and the sensitivities of technology improvements for reducing the costs of meeting requirements. Recommended development plans and funding levels are presented, as well as the possible cost saving for communications satellites in the post 1985 era.

The Weather Forecast Using Data Mining Research Based on Cloud Computing.

NASA Astrophysics Data System (ADS)

Wang, ZhanJie; Mazharul Mujib, A. B. M.

2017-10-01

Weather forecasting has been an important application in meteorology and one of the most scientifically and technologically challenging problem around the world. In my study, we have analyzed the use of data mining techniques in forecasting weather. This paper proposes a modern method to develop a service oriented architecture for the weather information systems which forecast weather using these data mining techniques. This can be carried out by using Artificial Neural Network and Decision tree Algorithms and meteorological data collected in Specific time. Algorithm has presented the best results to generate classification rules for the mean weather variables. The results showed that these data mining techniques can be enough for weather forecasting.

Forecast and virtual weather driven plant disease risk modeling system

USDA-ARS?s Scientific Manuscript database

We describe a system in use and development that leverages public weather station data, several spatialized weather forecast types, leaf wetness estimation, generic plant disease models, and online statistical evaluation. Convergent technological developments in all these areas allow, with funding f...

Making the Connection: Technological Literacy and Technology Assessment.

ERIC Educational Resources Information Center

Deal, Walter F.

2002-01-01

Technology assessment is the process of identifying, analyzing, and evaluating potential consequences of technology. Tools for assessing and forecasting impact include relevance trees and futures wheels. Activities based on these tools can be used to teach assessment to technology education students. (SK)

Earth Observations and the Role of UAVs: A Capabilities Assessment. Version 1.1

NASA Technical Reports Server (NTRS)

Cox, Timothy H.; Somers, Ivan; Fratello, David J.

2006-01-01

This document provides an assessment of the civil UAV missions and technologies and is intended to parallel the Office of the Secretary of Defense UAV Roadmap. The intent of this document is four-fold: 1. Determine and document desired future missions of Earth observation UAVs based on user-defined needs 2. Determine and document the technologies necessary to support those missions 3. Discuss the present state of the platform capabilities and required technologies, identifying those in progress, those planned, and those for which no current plans exist 4. Provide the foundations for development of a comprehensive civil UAV roadmap to complement the Department of Defense (DoD) effort (http://www.acq.osd.mil/uas/). Two aspects of the President's Management Agenda (refer to the document located at: www.whitehouse.gov/omb/budget/fy2002/mgmt.pdf ) are supported by this undertaking. First, it is one that will engage multiple Agencies in the effort as stakeholders and benefactors of the systems. In that sense, the market will be driven by the user requirements and applications. The second aspect is one of supporting economic development in the commercial sector. Market forecasts for the civil use of UAVs have indicated an infant market stage at present with a sustained forecasted growth. There is some difficulty in quantifying the value of the market since the typical estimate excludes system components other than the aerial platforms. Section 2.4 addresses the civil UAV market forecast and lists several independent forecasts. One conclusion that can be drawn from these forecasts is that all show a sustained growth for the duration of each long-term forecast.

A hybrid sales forecasting scheme by combining independent component analysis with K-means clustering and support vector regression.

PubMed

Lu, Chi-Jie; Chang, Chi-Chang

2014-01-01

Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (ICA) with K-means clustering and support vector regression (SVR). The proposed scheme first uses the ICA to extract hidden information from the observed sales data. The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. Finally, the SVR forecasting models are applied to each group to generate final forecasting results. Experimental results from information technology (IT) product agent sales data reveal that the proposed sales forecasting scheme outperforms the three comparison models and hence provides an efficient alternative for sales forecasting.

A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression

PubMed Central

2014-01-01

Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (ICA) with K-means clustering and support vector regression (SVR). The proposed scheme first uses the ICA to extract hidden information from the observed sales data. The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. Finally, the SVR forecasting models are applied to each group to generate final forecasting results. Experimental results from information technology (IT) product agent sales data reveal that the proposed sales forecasting scheme outperforms the three comparison models and hence provides an efficient alternative for sales forecasting. PMID:25045738

Long range forecasts of the Northern Hemisphere anomalies with antecedent sea surface temperature patterns

NASA Technical Reports Server (NTRS)

Kung, Ernest C.

1994-01-01

The contract research has been conducted in the following three major areas: analysis of numerical simulations and parallel observations of atmospheric blocking, diagnosis of the lower boundary heating and the response of the atmospheric circulation, and comprehensive assessment of long-range forecasting with numerical and regression methods. The essential scientific and developmental purpose of this contract research is to extend our capability of numerical weather forecasting by the comprehensive general circulation model. The systematic work as listed above is thus geared to developing a technological basis for future NASA long-range forecasting.

Advanced decision modeling for real time variable tolling : development and testing of a data collection platform.

DOT National Transportation Integrated Search

2012-06-01

Our current ability to forecast demand on tolled facilities has not kept pace with advances in decision sciences and : technological innovation. The current forecasting methods suffer from lack of descriptive power of actual behavior because : of the...

Solar energy market penetration models - Science or number mysticism

NASA Technical Reports Server (NTRS)

Warren, E. H., Jr.

1980-01-01

The forecast market potential of a solar technology is an important factor determining its R&D funding. Since solar energy market penetration models are the method used to forecast market potential, they have a pivotal role in a solar technology's development. This paper critiques the applicability of the most common solar energy market penetration models. It is argued that the assumptions underlying the foundations of rigorously developed models, or the absence of a reasonable foundation for the remaining models, restrict their applicability.

Development of a model-based flood emergency management system in Yujiang River Basin, South China

NASA Astrophysics Data System (ADS)

Zeng, Yong; Cai, Yanpeng; Jia, Peng; Mao, Jiansu

2014-06-01

Flooding is the most frequent disaster in China. It affects people's lives and properties, causing considerable economic loss. Flood forecast and operation of reservoirs are important in flood emergency management. Although great progress has been achieved in flood forecast and reservoir operation through using computer, network technology, and geographic information system technology in China, the prediction accuracy of models are not satisfactory due to the unavailability of real-time monitoring data. Also, real-time flood control scenario analysis is not effective in many regions and can seldom provide online decision support function. In this research, a decision support system for real-time flood forecasting in Yujiang River Basin, South China (DSS-YRB) is introduced in this paper. This system is based on hydrological and hydraulic mathematical models. The conceptual framework and detailed components of the proposed DSS-YRB is illustrated, which employs real-time rainfall data conversion, model-driven hydrologic forecasting, model calibration, data assimilation methods, and reservoir operational scenario analysis. Multi-tiered architecture offers great flexibility, portability, reusability, and reliability. The applied case study results show the development and application of a decision support system for real-time flood forecasting and operation is beneficial for flood control.

Recent Trends in Variable Generation Forecasting and Its Value to the Power System

DOE PAGES

Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; ...

2014-12-23

We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value ofmore » adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.« less

Using Earth Observation to Forecast Human and Animal Vector-Borne Disease Outbreaks

USDA-ARS?s Scientific Manuscript database

Earth observing technologies, including data from with earth-orbiting satellites, coupled with new investigations and a better understanding of the impact of environmental factors on transmission dynamics of mosquito-borne diseases permitted us to forecast Rift Valley fever (RVF) outbreaks in animal...

Increasing the temporal resolution of direct normal solar irradiance forecasted series

NASA Astrophysics Data System (ADS)

Fernández-Peruchena, Carlos M.; Gastón, Martin; Schroedter-Homscheidt, Marion; Marco, Isabel Martínez; Casado-Rubio, José L.; García-Moya, José Antonio

2017-06-01

A detailed knowledge of the solar resource is a critical point in the design and control of Concentrating Solar Power (CSP) plants. In particular, accurate forecasting of solar irradiance is essential for the efficient operation of solar thermal power plants, the management of energy markets, and the widespread implementation of this technology. Numerical weather prediction (NWP) models are commonly used for solar radiation forecasting. In the ECMWF deterministic forecasting system, all forecast parameters are commercially available worldwide at 3-hourly intervals. Unfortunately, as Direct Normal solar Irradiance (DNI) exhibits a great variability due to the dynamic effects of passing clouds, 3-h time resolution is insufficient for accurate simulations of CSP plants due to their nonlinear response to DNI, governed by various thermal inertias due to their complex response characteristics. DNI series of hourly or sub-hourly frequency resolution are normally used for an accurate modeling and analysis of transient processes in CSP technologies. In this context, the objective of this study is to propose a methodology for generating synthetic DNI time series at 1-h (or higher) temporal resolution from 3-h DNI series. The methodology is based upon patterns as being defined with help of the clear-sky envelope approach together with a forecast of maximum DNI value, and it has been validated with high quality measured DNI data.

Forecasting Container Throughput at the Doraleh Port in Djibouti through Time Series Analysis

NASA Astrophysics Data System (ADS)

Mohamed Ismael, Hawa; Vandyck, George Kobina

The Doraleh Container Terminal (DCT) located in Djibouti has been noted as the most technologically advanced container terminal on the African continent. DCT's strategic location at the crossroads of the main shipping lanes connecting Asia, Africa and Europe put it in a unique position to provide important shipping services to vessels plying that route. This paper aims to forecast container throughput through the Doraleh Container Port in Djibouti by Time Series Analysis. A selection of univariate forecasting models has been used, namely Triple Exponential Smoothing Model, Grey Model and Linear Regression Model. By utilizing the above three models and their combination, the forecast of container throughput through the Doraleh port was realized. A comparison of the different forecasting results of the three models, in addition to the combination forecast is then undertaken, based on commonly used evaluation criteria Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). The study found that the Linear Regression forecasting Model was the best prediction method for forecasting the container throughput, since its forecast error was the least. Based on the regression model, a ten (10) year forecast for container throughput at DCT has been made.

Technology and Adolescents: Perspectives on the Things to Come

ERIC Educational Resources Information Center

Katz, Raul L.; Felix, Max; Gubernick, Madlen

2014-01-01

Assuming that, given the processes of technology diffusion, adolescent behavior forecasts future consumption of digital information, it would seem pertinent to study the characteristics of teenager technology use. This research asks: What are the key patterns regarding the use of technology platforms by teenagers? Is technology usage among…

Establishing an Environmental Scanning/Forecasting System to Augment College and University Planning.

ERIC Educational Resources Information Center

Morrison, James L.

1987-01-01

The major benefit of an environmental scanning/forecasting system is in providing critical information for strategic planning. Such a system allows the institution to detect social, technological, economic, and political trends and potential events. The environmental scanning database developed by United Way of America is described. (MLW)

A formulation of multidimensional growth models for the assessment and forecast of technology attributes

NASA Astrophysics Data System (ADS)

Danner, Travis W.

Developing technology systems requires all manner of investment---engineering talent, prototypes, test facilities, and more. Even for simple design problems the investment can be substantial; for complex technology systems, the development costs can be staggering. The profitability of a corporation in a technology-driven industry is crucially dependent on maximizing the effectiveness of research and development investment. Decision-makers charged with allocation of this investment are forced to choose between the further evolution of existing technologies and the pursuit of revolutionary technologies. At risk on the one hand is excessive investment in an evolutionary technology which has only limited availability for further improvement. On the other hand, the pursuit of a revolutionary technology may mean abandoning momentum and the potential for substantial evolutionary improvement resulting from the years of accumulated knowledge. The informed answer to this question, evolutionary or revolutionary, requires knowledge of the expected rate of improvement and the potential a technology offers for further improvement. This research is dedicated to formulating the assessment and forecasting tools necessary to acquire this knowledge. The same physical laws and principles that enable the development and improvement of specific technologies also limit the ultimate capability of those technologies. Researchers have long used this concept as the foundation for modeling technological advancement through extrapolation by analogy to biological growth models. These models are employed to depict technology development as it asymptotically approaches limits established by the fundamental principles on which the technological approach is based. This has proven an effective and accurate approach to modeling and forecasting simple single-attribute technologies. With increased system complexity and the introduction of multiple system objectives, however, the usefulness of this modeling technique begins to diminish. With the introduction of multiple objectives, researchers often abandon technology growth models for scoring models and technology frontiers. While both approaches possess advantages over current growth models for the assessment of multi-objective technologies, each lacks a necessary dimension for comprehensive technology assessment. By collapsing multiple system metrics into a single, non-intuitive technology measure, scoring models provide a succinct framework for multi-objective technology assessment and forecasting. Yet, with no consideration of physical limits, scoring models provide no insight as to the feasibility of a particular combination of system capabilities. They only indicate that a given combination of system capabilities yields a particular score. Conversely, technology frontiers are constructed with the distinct objective of providing insight into the feasibility of system capability combinations. Yet again, upper limits to overall system performance are ignored. Furthermore, the data required to forecast subsequent technology frontiers is often inhibitive. In an attempt to reincorporate the fundamental nature of technology advancement as bound by physical principles, researchers have sought to normalize multi-objective systems whereby the variability of a single system objective is eliminated as a result of changes in the remaining objectives. This drastically limits the applicability of the resulting technology model because it is only applicable for a single setting of all other system attributes. Attempts to maintain the interaction between the growth curves of each technical objective of a complex system have thus far been limited to qualitative and subjective consideration. This research proposes the formulation of multidimensional growth models as an approach to simulating the advancement of multi-objective technologies towards their upper limits. Multidimensional growth models were formulated by noticing and exploiting the correlation between technology growth models and technology frontiers. Both are frontiers in actuality. The technology growth curve is a frontier between capability levels of a single attribute and time, while a technology frontier is a frontier between the capability levels of two or more attributes. Multidimensional growth models are formulated by exploiting the mathematical significance of this correlation. The result is a model that can capture both the interaction between multiple system attributes and their expected rates of improvement over time. The fundamental nature of technology development is maintained, and interdependent growth curves are generated for each system metric with minimal data requirements. Being founded on the basic nature of technology advancement, relative to physical limits, the availability for further improvement can be determined for a single metric relative to other system measures of merit. A by-product of this modeling approach is a single n-dimensional technology frontier linking all n system attributes with time. This provides an environment capable of forecasting future system capability in the form of advancing technology frontiers. The ability of a multidimensional growth model to capture the expected improvement of a specific technological approach is dependent on accurately identifying the physical limitations to each pertinent attribute. This research investigates two potential approaches to identifying those physical limits, a physics-based approach and a regression-based approach. The regression-based approach has found limited acceptance among forecasters, although it does show potential for estimating upper limits with a specified degree of uncertainty. Forecasters have long favored physics-based approaches for establishing the upper limit to unidimensional growth models. The task of accurately identifying upper limits has become increasingly difficult with the extension of growth models into multiple dimensions. A lone researcher may be able to identify the physical limitation to a single attribute of a simple system; however, as system complexity and the number of attributes increases, the attention of researchers from multiple fields of study is required. Thus, limit identification is itself an area of research and development requiring some level of investment. Whether estimated by physics or regression-based approaches, predicted limits will always have some degree of uncertainty. This research takes the approach of quantifying the impact of that uncertainty on model forecasts rather than heavily endorsing a single technique to limit identification. In addition to formulating the multidimensional growth model, this research provides a systematic procedure for applying that model to specific technology architectures. Researchers and decision-makers are able to investigate the potential for additional improvement within that technology architecture and to estimate the expected cost of each incremental improvement relative to the cost of past improvements. In this manner, multidimensional growth models provide the necessary information to set reasonable program goals for the further evolution of a particular technological approach or to establish the need for revolutionary approaches in light of the constraining limits of conventional approaches.

Fishing Forecasts

NASA Technical Reports Server (NTRS)

1988-01-01

ROFFS stands for Roffer's Ocean Fishing Forecasting Service, Inc. Roffer combines satellite and computer technology with oceanographic information from several sources to produce frequently updated charts sometimes as often as 30 times a day showing clues to the location of marlin, sailfish, tuna, swordfish and a variety of other types. Also provides customized forecasts for racing boats and the shipping industry along with seasonal forecasts that allow the marine industry to formulate fishing strategies based on foreknowledge of the arrival and departure times of different fish. Roffs service exemplifies the potential for benefits to marine industries from satellite observations. Most notable results are reduced search time and substantial fuel savings.

New Measurements and Modeling Capability to Improve Real-time Forecast of Cascadia Tsunamis along U.S. West Coast

NASA Astrophysics Data System (ADS)

Wei, Y.; Titov, V. V.; Bernard, E. N.; Spillane, M. C.

2014-12-01

The tragedies of 2004 Sumatra and 2011 Tohoku tsunamis exposed the limits of our knowledge in preparing for devastating tsunamis, especially in the near field. The 1,100-km coastline of the Pacific coast of North America has tectonic and geological settings similar to Sumatra and Japan. The geological records unambiguously show that the Cascadia fault had caused devastating tsunamis in the past and this geological process will cause tsunamis in the future. Existing observational instruments along the Cascadia Subduction Zone are capable of providing tsunami data within minutes of tsunami generation. However, this strategy requires separation of the tsunami signals from the overwhelming high-frequency seismic waves produced during a strong earthquake- a real technical challenge for existing operational tsunami observational network. A new-generation of nano-resolution pressure sensors can provide high temporal resolution of the earthquake and tsunami signals without loosing precision. The nano-resolution pressure sensor offers a state-of the-science ability to separate earthquake vibrations and other oceanic noise from tsunami waveforms, paving the way for accurate, early warnings of local tsunamis. This breakthrough underwater technology has been tested and verified for a couple of micro-tsunami events (Paros et al., 2011). Real-time forecast of Cascadia tsunamis is becoming a possibility with the development of nano-tsunameter technology. The present study provides an investigation on optimizing the placement of these new sensors so that the forecast time can be shortened.. The presentation will cover the optimization of an observational array to quickly detect and forecast a tsunami generated by a strong Cascadia earthquake, including short and long rupture scenarios. Lessons learned from the 2011 Tohoku tsunami will be examined to demonstrate how we can improve the local forecast using the new technology We expect this study to provide useful guideline for future siting and deployment of the new-generation tsunameters. Driven by the new technology, we demonstrate scenarios of real-time forecast of Cascadia tsunami impact along the Pacific Northwest, as well as in the Puget Sound.

Consumption trend analysis in the industrial sector: Existing forecasts

NASA Astrophysics Data System (ADS)

1981-08-01

The Gas Research Institute (GRI) is engaged in medium- to long-range research and development in various sectors of the economy that depend on gasing technologies and equipment. To assess the potential demand for natural gas in the industrial sector, forecasts available from private and public sources were compared and analyzed. More than 20 projections were examined, and 10 of the most appropriate long-range demand forecasts were analyzed and compared with respect to the various assumptions, methodologies and criteria on which each was based.

Improving Societal Benefit Areas from Applications Enhanced by the Joint Polar Satellite System

NASA Astrophysics Data System (ADS)

Goldberg, M.

2016-12-01

Applications of satellite data are paramount to transform science and technology to product and services which are used in critical decision making for societal benefits. For the satellite community, good representations of technology are the satellite sensors, while science provides the instrument calibration and derived geophysical parameters. Weather forecasting is an application of the science and technology provided by remote sensing satellites. The Joint Polar Satellite System, which includes the Suomi National Polar-orbiting Partnership (S-NPP) provides formidable science and technology to support many applications and includes support to 1) weather forecasting - data from the JPSS Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) are used to forecast weather events out to 7 days - nearly 85% of all data used in weather forecasting are from polar orbiting satellites; 2) environmental monitoring -data from the JPSS Visible Infrared Imager Radiometer Suite (VIIRS) are used to monitor the environment including the health of coastal ecosystems, drought conditions, fire, smoke, dust, snow and ice, and the state of oceans, including sea surface temperature and ocean color; and 3) climate monitoring - data from JPSS instruments, including OMPS and CERES will provide continuity to climate data records established using NOAA POES and NASA Earth Observing System (EOS) satellite observations. To bridge the gap between products and applications, the JPSS Program has established a proving ground program to optimize the use of JPSS data with other data sources to improve key products and services. A number of operational and research applications will be presented along with how the data and applications support a large number of societal benefit areas of the Global Earth Observation Systems of Systems (GEOSS).

JPSS Operational and Research Applications: The Pathway from Observations to Applications to Information.

NASA Astrophysics Data System (ADS)

Goldberg, M.; Sjoberg, W.; Layns, A. L.

2017-12-01

Applications of satellite data are paramount to transform science and technology to product and services which are used in critical decision making. For the satellite community, good representations of technology are the satellite sensors, while science provides the instrument calibration and derived geophysical parameters. Weather forecasting is an application of the science and technology provided by remote sensing satellites. The Joint Polar Satellite System, which includes the Suomi National Polar-orbiting Partnership (S-NPP) provides formidable science and technology to support many applications and includes support to 1) weather forecasting - data from the JPSS Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) are used to forecast weather events out to 7 days - nearly 85% of all data used in weather forecasting are from polar orbiting satellites; 2) environmental monitoring -data from the JPSS Visible Infrared Imager Radiometer Suite (VIIRS) are used to monitor the environment including the health of coastal ecosystems, drought conditions, fire, smoke, dust, snow and ice, and the state of oceans, including sea surface temperature and ocean color; and 3) climate monitoring - data from JPSS instruments, including OMPS and CERES will provide continuity to climate data records established using NOAA POES and NASA Earth Observing System (EOS) satellite observations. To bridge the gap between products and applications, the JPSS Program has established the Proving Ground and Risk Reduction (PGRR) Program to identify opportunities to maximize the operational application of current JPSS capabilities. The PGRR Program also helps identify and evaluate the use of JPSS capabilities for new operational missions. New PGRR initiatives focus on hydrological, Arctic, data assimilation, atmospheric chemistry, ocean ecosystem applications. At the conference, the benefits of JPSS data on societal benefits will be presented along with results from the PGRR initiatives.

Remote Sensing Technologies and Geospatial Modelling Hierarchy for Smart City Support

NASA Astrophysics Data System (ADS)

Popov, M.; Fedorovsky, O.; Stankevich, S.; Filipovich, V.; Khyzhniak, A.; Piestova, I.; Lubskyi, M.; Svideniuk, M.

2017-12-01

The approach to implementing the remote sensing technologies and geospatial modelling for smart city support is presented. The hierarchical structure and basic components of the smart city information support subsystem are considered. Some of the already available useful practical developments are described. These include city land use planning, urban vegetation analysis, thermal condition forecasting, geohazard detection, flooding risk assessment. Remote sensing data fusion approach for comprehensive geospatial analysis is discussed. Long-term city development forecasting by Forrester - Graham system dynamics model is provided over Kiev urban area.

Winter wheat quality monitoring and forecasting system based on remote sensing and environmental factors

NASA Astrophysics Data System (ADS)

Haiyang, Yu; Yanmei, Liu; Guijun, Yang; Xiaodong, Yang; Dong, Ren; Chenwei, Nie

2014-03-01

To achieve dynamic winter wheat quality monitoring and forecasting in larger scale regions, the objective of this study was to design and develop a winter wheat quality monitoring and forecasting system by using a remote sensing index and environmental factors. The winter wheat quality trend was forecasted before the harvest and quality was monitored after the harvest, respectively. The traditional quality-vegetation index from remote sensing monitoring and forecasting models were improved. Combining with latitude information, the vegetation index was used to estimate agronomy parameters which were related with winter wheat quality in the early stages for forecasting the quality trend. A combination of rainfall in May, temperature in May, illumination at later May, the soil available nitrogen content and other environmental factors established the quality monitoring model. Compared with a simple quality-vegetation index, the remote sensing monitoring and forecasting model used in this system get greatly improved accuracy. Winter wheat quality was monitored and forecasted based on the above models, and this system was completed based on WebGIS technology. Finally, in 2010 the operation process of winter wheat quality monitoring system was presented in Beijing, the monitoring and forecasting results was outputted as thematic maps.

Applying different independent component analysis algorithms and support vector regression for IT chain store sales forecasting.

PubMed

Dai, Wensheng; Wu, Jui-Yu; Lu, Chi-Jie

2014-01-01

Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting.

Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting

PubMed Central

Dai, Wensheng

2014-01-01

Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting. PMID:25165740

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aabakken, J.

This report, prepared by NREL's Strategic Energy Analysis Center, includes up-to-date information on power technologies, including complete technology profiles. The data book also contains charts on electricity restructuring, power technology forecasts, electricity supply, electricity capability, electricity generation, electricity demand, prices, economic indicators, environmental indicators, and conversion factors.

Toward a new Federal policy for technology: The outline emerges

NASA Technical Reports Server (NTRS)

Logsdon, J. M.

1972-01-01

The development is traced of a new federal policy for the support and use of technology. The premises underlying such a policy and forecasts likely future developments are analyzed. The first Presidential message on science and technology is included.

76 FR 9696 - Equipment Price Forecasting in Energy Conservation Standards Analysis

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-22

... for particular efficiency design options, an empirical experience curve fit to the available data may be used to forecast future costs of such design option technologies. If a statistical evaluation indicates a low level of confidence in estimates of the design option cost trend, this method should not be...

Adjustment to Technological Change: Summary and Policy Implications.

ERIC Educational Resources Information Center

Mangum, Garth L.

A supplement to the report on adjustment to technological change, the document reviews policies of recent years related to adjustment to technological change and the added implications of the Blair and Fechter studies ("Mechanisms for Aiding Worker Adjustment to Technological Change" by Larry M. Blair and "Forecasting the Impact of Technological…

The combined value of wind and solar power forecasting improvements and electricity storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, Bri-Mathias; Brancucci Martinez-Anido, Carlo; Wang, Qin

As the penetration rates of variable renewable energy increase, the value of power systems operation flexibility technology options, such as renewable energy forecasting improvements and electricity storage, is also assumed to increase. In this work, we examine the value of these two technologies, when used independently and concurrently, for two real case studies that represent the generation mixes for the California and Midcontinent Independent System Operators (CAISO and MISO). Since both technologies provide additional system flexibility they reduce operational costs and renewable curtailment for both generation mixes under study. Interestingly, the relative impacts are quite similar when both technologies aremore » used together. Though both flexibility options can solve some of the same issues that arise with high penetration levels of renewables, they do not seem to significantly increase or decrease the economic potential of the other technology.« less

The combined value of wind and solar power forecasting improvements and electricity storage

DOE PAGES

Hodge, Bri-Mathias; Brancucci Martinez-Anido, Carlo; Wang, Qin; ...

2018-02-12

As the penetration rates of variable renewable energy increase, the value of power systems operation flexibility technology options, such as renewable energy forecasting improvements and electricity storage, is also assumed to increase. In this work, we examine the value of these two technologies, when used independently and concurrently, for two real case studies that represent the generation mixes for the California and Midcontinent Independent System Operators (CAISO and MISO). Since both technologies provide additional system flexibility they reduce operational costs and renewable curtailment for both generation mixes under study. Interestingly, the relative impacts are quite similar when both technologies aremore » used together. Though both flexibility options can solve some of the same issues that arise with high penetration levels of renewables, they do not seem to significantly increase or decrease the economic potential of the other technology.« less

Transportation Sector Model of the National Energy Modeling System. Volume 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1998-01-01

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. The NEMS Transportation Model comprises a series of semi-independent models which address different aspects of the transportation sector. The primary purpose of this model is to provide mid-term forecasts of transportation energy demand by fuel type including, but not limited to, motor gasoline, distillate, jet fuel, and alternative fuels (such as CNG) not commonly associated with transportation. Themore » current NEMS forecast horizon extends to the year 2010 and uses 1990 as the base year. Forecasts are generated through the separate consideration of energy consumption within the various modes of transport, including: private and fleet light-duty vehicles; aircraft; marine, rail, and truck freight; and various modes with minor overall impacts, such as mass transit and recreational boating. This approach is useful in assessing the impacts of policy initiatives, legislative mandates which affect individual modes of travel, and technological developments. The model also provides forecasts of selected intermediate values which are generated in order to determine energy consumption. These elements include estimates of passenger travel demand by automobile, air, or mass transit; estimates of the efficiency with which that demand is met; projections of vehicle stocks and the penetration of new technologies; and estimates of the demand for freight transport which are linked to forecasts of industrial output. Following the estimation of energy demand, TRAN produces forecasts of vehicular emissions of the following pollutants by source: oxides of sulfur, oxides of nitrogen, total carbon, carbon dioxide, carbon monoxide, and volatile organic compounds.« less

Speech systems research at Texas Instruments

NASA Technical Reports Server (NTRS)

Doddington, George R.

1977-01-01

An assessment of automatic speech processing technology is presented. Fundamental problems in the development and the deployment of automatic speech processing systems are defined and a technology forecast for speech systems is presented.

Averaging business cycles vs. myopia: Do we need a long term vision when developing IRP?

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDonald, C.; Gupta, P.C.

1995-05-01

Utility demand forecasting is inherently imprecise due to the number of uncertainties resulting from business cycles, policy making, technology breakthroughs, national and international political upheavals and the limitations of the forecasting tools. This implies that revisions based primarily on recent experience could lead to unstable forecasts. Moreover, new planning tools are required that provide an explicit consideration of uncertainty and lead to flexible and robust planning tools are required that provide an explicit consideration of uncertainty and lead to flexible and robust planning decisions.

Using Sensor Web Processes and Protocols to Assimilate Satellite Data into a Forecast Model

NASA Technical Reports Server (NTRS)

Goodman, H. Michael; Conover, Helen; Zavodsky, Bradley; Maskey, Manil; Jedlovec, Gary; Regner, Kathryn; Li, Xiang; Lu, Jessica; Botts, Mike; Berthiau, Gregoire

2008-01-01

The goal of the Sensor Management Applied Research Technologies (SMART) On-Demand Modeling project is to develop and demonstrate the readiness of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities to integrate both space-based Earth observations and forecast model output into new data acquisition and assimilation strategies. The project is developing sensor web-enabled processing plans to assimilate Atmospheric Infrared Sounding (AIRS) satellite temperature and moisture retrievals into a regional Weather Research and Forecast (WRF) model over the southeastern United States.

Futures Research and the Strategic Planning Process: Implications for Higher Education. ASHE-ERIC Higher Education Research Report No. 9, 1984.

ERIC Educational Resources Information Center

Morrison, James L.; And Others

The use of futures research to improve a college's ability to deal with changes brought about by social, economic, political, and technological developments is discussed, with attention to new planning strategies and forecasting methods. While traditional long-range planning tracks and forecasts the institution's internal development, strategic…

Technology Forecasting for the Purpose of Predicting Employment Growth

ERIC Educational Resources Information Center

Smith, Cormac

2016-01-01

Throughout history, there has been a great emphasis placed on the ability to predict future events. The value of such prognostication varies between situations and domains, but the objective remains the same. Is it possible to use current or past observations to forecast future events? One specific area in which such insight is sought after is the…

[Improved euler algorithm for trend forecast model and its application to oil spectrum analysis].

PubMed

Zheng, Chang-song; Ma, Biao

2009-04-01

The oil atomic spectrometric analysis technology is one of the most important methods for fault diagnosis and state monitoring of large machine equipment. The gray method is preponderant in the trend forecast at the same time. With the use of oil atomic spectrometric analysis result and combining the gray forecast theory, the present paper established a gray forecast model of the Fe/Cu concentration trend in the power-shift steering transmission. Aiming at the shortage of the gray method used in the trend forecast, the improved Euler algorithm was put forward for the first time to resolve the problem of the gray model and avoid the non-precision that the old gray model's forecast value depends on the first test value. This new method can make the forecast value more precision as shown in the example. Combined with the threshold value of the oil atomic spectrometric analysis, the new method was applied on the Fe/Cu concentration forecast and the premonition of fault information was obtained. So we can take steps to prevent the fault and this algorithm can be popularized to the state monitoring in the industry.

Environmental noise forecasting based on support vector machine

NASA Astrophysics Data System (ADS)

Fu, Yumei; Zan, Xinwu; Chen, Tianyi; Xiang, Shihan

2018-01-01

As an important pollution source, the noise pollution is always the researcher's focus. Especially in recent years, the noise pollution is seriously harmful to the human beings' environment, so the research about the noise pollution is a very hot spot. Some noise monitoring technologies and monitoring systems are applied in the environmental noise test, measurement and evaluation. But, the research about the environmental noise forecasting is weak. In this paper, a real-time environmental noise monitoring system is introduced briefly. This monitoring system is working in Mianyang City, Sichuan Province. It is monitoring and collecting the environmental noise about more than 20 enterprises in this district. Based on the large amount of noise data, the noise forecasting by the Support Vector Machine (SVM) is studied in detail. Compared with the time series forecasting model and the artificial neural network forecasting model, the SVM forecasting model has some advantages such as the smaller data size, the higher precision and stability. The noise forecasting results based on the SVM can provide the important and accuracy reference to the prevention and control of the environmental noise.

Forecasting quantities of disused household CRT appliances--a regional case study approach and its application to Baden-Württemberg.

PubMed

Walk, Wolfgang

2009-02-01

Due to special requirements regarding logistics and recycling, disused cathode ray tube (CRT) appliances are handled in some countries as a separate waste fraction. This article presents a forecast of future household waste CRT quantities based on the past and present equipment of households with television sets and computer monitors. Additional aspects taken into consideration are the product life time distribution and the ongoing change in display technology. Although CRT technology is fading out, the findings of this forecast show that quantities of waste CRT appliances will not decrease before 2012 in Baden-Württemberg, Germany. The results of this regional case study are not quantitatively transferable without further analysis. The method provided allows analysts to consider how the time shift between production and discard could impact recycling options, and the method could be valuable for future similar analyses elsewhere.

Forecasting skills of the ensemble hydro-meteorological system for the Po river floods

NASA Astrophysics Data System (ADS)

Ricciardi, Giuseppe; Montani, Andrea; Paccagnella, Tiziana; Pecora, Silvano; Tonelli, Fabrizio

2013-04-01

The Po basin is the largest and most economically important river-basin in Italy. Extreme hydrological events, including floods, flash floods and droughts, are expected to become more severe in the next future due to climate change, and related ground effects are linked both with environmental and social resilience. A Warning Operational Center (WOC) for hydrological event management was created in Emilia Romagna region. In the last years, the WOC faced challenges in legislation, organization, technology and economics, achieving improvements in forecasting skill and information dissemination. Since 2005, an operational forecasting and modelling system for flood modelling and forecasting has been implemented, aimed at supporting and coordinating flood control and emergency management on the whole Po basin. This system, referred to as FEWSPo, has also taken care of environmental aspects of flood forecast. The FEWSPo system has reached a very high level of complexity, due to the combination of three different hydrological-hydraulic chains (HEC-HMS/RAS - MIKE11 NAM/HD, Topkapi/Sobek), with several meteorological inputs (forecasted - COSMOI2, COSMOI7, COSMO-LEPS among others - and observed). In this hydrological and meteorological ensemble the management of the relative predictive uncertainties, which have to be established and communicated to decision makers, is a debated scientific and social challenge. Real time activities face professional, modelling and technological aspects but are also strongly interrelated with organization and human aspects. The authors will report a case study using the operational flood forecast hydro-meteorological ensemble, provided by the MIKE11 chain fed by COSMO_LEPS EQPF. The basic aim of the proposed approach is to analyse limits and opportunities of the long term forecast (with a lead time ranging from 3 to 5 days), for the implementation of low cost actions, also looking for a well informed decision making and the improvement of flood preparedness and crisis management for basins greater than 1.000 km2.

JPSS Products, Applications and Training

NASA Astrophysics Data System (ADS)

Torres, J. R.; Connell, B. H.; Miller, S. D.

2017-12-01

The Joint Polar Satellite System (JPSS) is a new generation polar-orbiting operational environmental satellite system that will monitor the weather and environment around the globe. JPSS will provide technological and scientific improvements in environmental monitoring via high resolution satellite imagery and derived products that stand to improve weather forecasting capabilities for National Weather Service (NWS) forecasters and complement operational Geostationary satellites. JPSS will consist of four satellites, JPSS-1 through JPSS-4, where JPSS-1 is due to launch in Fall 2017. A predecessor, prototype and operational risk-reduction for JPSS is the Suomi-National Polar-orbiting Partnership (S-NPP) satellite, launched on 28 October 2011. The following instruments on-board S-NPP will also be hosted on JPSS-1: Visible Infrared Imaging Radiometer Suite (VIIRS), Cross-track Infrared Sounder (CrIS), Advanced Technology Microwave Sounder (ATMS), Ozone Mapping and Profiler Suite (OMPS) and the Clouds and Earth's Radiant Energy System (CERES). JPSS-1 instruments will provide satellite imagery, products and applications to users. The applications include detecting water and ice clouds, snow, sea surface temperatures, fog, fire, severe weather, vegetation health, aerosols, and sensing reflected lunar and emitted visible-wavelength light during the nighttime via the Day/Night Band (DNB) sensor included on VIIRS. Currently, there are only a few polar products that are operational for forecasters, however, more products will become available in the near future via Advanced Weather Interactive Processing System-II (AWIPS-II)-a forecasting analysis software package that forecasters can use to analyze meteorological data. To complement the polar products an wealth of training materials are currently in development. Denoted as the Satellite Foundational Course for JPSS (SatFC-J), this training will benefit NWS forecasters to utilize satellite data in their forecasts and daily operations as they discover their operational value in the NWS forecast process. As JPSS-1 launch nears, training materials will be produced in the form of modules, videos, quick guides, fact sheets, and hands-on exercises.

Forecasting the development of nanotechnology with the help of science and technology indicators

NASA Astrophysics Data System (ADS)

Compañó, Ramón; Hullmann, Angela

2002-06-01

Nanotechnology is supposed to become one of the key enabling technologies of the 21st century. Its economic potential is forecast to be a market of several hundred billion Euros in the next decade. Therefore, nanotechnology has attracted the interest of many industry sectors and many companies redirecting internal activities to prepare themselves for this new challenge. At the same time governmental R&D decision makers all over the world are setting up new nanotechnology-specific research programmes aiming at putting their respective countries in a favourable position for the future. The aim of this paper is to use scientific and technological indicators to make predictions on economic development and to compare the situation in different countries.

Forecasting of the development of professional medical equipment engineering based on neuro-fuzzy algorithms

NASA Astrophysics Data System (ADS)

Vaganova, E. V.; Syryamkin, M. V.

2015-11-01

The purpose of the research is the development of evolutionary algorithms for assessments of promising scientific directions. The main attention of the present study is paid to the evaluation of the foresight possibilities for identification of technological peaks and emerging technologies in professional medical equipment engineering in Russia and worldwide on the basis of intellectual property items and neural network modeling. An automated information system consisting of modules implementing various classification methods for accuracy of the forecast improvement and the algorithm of construction of neuro-fuzzy decision tree have been developed. According to the study result, modern trends in this field will focus on personalized smart devices, telemedicine, bio monitoring, «e-Health» and «m-Health» technologies.

Soft computing prediction of economic growth based in science and technology factors

NASA Astrophysics Data System (ADS)

Marković, Dušan; Petković, Dalibor; Nikolić, Vlastimir; Milovančević, Miloš; Petković, Biljana

2017-01-01

The purpose of this research is to develop and apply the Extreme Learning Machine (ELM) to forecast the gross domestic product (GDP) growth rate. In this study the GDP growth was analyzed based on ten science and technology factors. These factors were: research and development (R&D) expenditure in GDP, scientific and technical journal articles, patent applications for nonresidents, patent applications for residents, trademark applications for nonresidents, trademark applications for residents, total trademark applications, researchers in R&D, technicians in R&D and high-technology exports. The ELM results were compared with genetic programming (GP), artificial neural network (ANN) and fuzzy logic results. Based upon simulation results, it is demonstrated that ELM has better forecasting capability for the GDP growth rate.

Uncertainty quantification and reliability assessment in operational oil spill forecast modeling system.

PubMed

Hou, Xianlong; Hodges, Ben R; Feng, Dongyu; Liu, Qixiao

2017-03-15

As oil transport increasing in the Texas bays, greater risks of ship collisions will become a challenge, yielding oil spill accidents as a consequence. To minimize the ecological damage and optimize rapid response, emergency managers need to be informed with how fast and where oil will spread as soon as possible after a spill. The state-of-the-art operational oil spill forecast modeling system improves the oil spill response into a new stage. However uncertainty due to predicted data inputs often elicits compromise on the reliability of the forecast result, leading to misdirection in contingency planning. Thus understanding the forecast uncertainty and reliability become significant. In this paper, Monte Carlo simulation is implemented to provide parameters to generate forecast probability maps. The oil spill forecast uncertainty is thus quantified by comparing the forecast probability map and the associated hindcast simulation. A HyosPy-based simple statistic model is developed to assess the reliability of an oil spill forecast in term of belief degree. The technologies developed in this study create a prototype for uncertainty and reliability analysis in numerical oil spill forecast modeling system, providing emergency managers to improve the capability of real time operational oil spill response and impact assessment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of advanced technologies to future military transports

NASA Technical Reports Server (NTRS)

Clark, Rodney L.; Lange, Roy H.; Wagner, Richard D.

1990-01-01

Long range military transport technologies are addressed with emphasis of defining the potential benefits of the hybrid laminar flow control (HLFC) concept currently being flight tested. Results of a 1990's global range transport study are presented showing the expected payoff from application of advanced technologies. Technology forecast for military transports is also presented.

Tracking the New Technology. A Summary of the Second Invitational Postsecondary Educational Review Panel.

ERIC Educational Resources Information Center

Sterling, C. H.

The second educational technology review panel addressed problems with forecasting the trends and impact of newer telecomunications technologies in both home and institution of higher education settings, and the role of several grant programs in educational technology. Paul Mertins provided an update on a National Center for Education Statistics…

Integrating observation and statistical forecasts over sub-Saharan Africa to support Famine Early Warning

USGS Publications Warehouse

Funk, Chris; Verdin, James P.; Husak, Gregory

2007-01-01

Famine early warning in Africa presents unique challenges and rewards. Hydrologic extremes must be tracked and anticipated over complex and changing climate regimes. The successful anticipation and interpretation of hydrologic shocks can initiate effective government response, saving lives and softening the impacts of droughts and floods. While both monitoring and forecast technologies continue to advance, discontinuities between monitoring and forecast systems inhibit effective decision making. Monitoring systems typically rely on high resolution satellite remote-sensed normalized difference vegetation index (NDVI) and rainfall imagery. Forecast systems provide information on a variety of scales and formats. Non-meteorologists are often unable or unwilling to connect the dots between these disparate sources of information. To mitigate these problem researchers at UCSB's Climate Hazard Group, NASA GIMMS and USGS/EROS are implementing a NASA-funded integrated decision support system that combines the monitoring of precipitation and NDVI with statistical one-to-three month forecasts. We present the monitoring/forecast system, assess its accuracy, and demonstrate its application in food insecure sub-Saharan Africa.

Technical Progress: Three Ways to Keep Up.

ERIC Educational Resources Information Center

Patterson, J. Wayne; And Others

1988-01-01

The authors analyzed three techniques employed in technological forecasting: (1) brainstorming, (2) extrapolation, and (3) scenario writing. They argue that these techniques have value to practitioners, particularly managers, who are often affected by technological change. (CH)

Forecasting the Technological Future: Directions for Education.

ERIC Educational Resources Information Center

Watkins, Peter

1986-01-01

Recent studies indicate that the popular acceptance of linking education instrumentally to high technology leads to contradictory outcomes (for example, Sweet 1984, Rumberger and Levin 1985). Education is better directed toward the more fundamental skills of criticism and reflection on these technological changes in society. (24 references) (CJH)

Forecasting Financial Priorities for Technology.

ERIC Educational Resources Information Center

Ringle, Martin D.

1997-01-01

Argues that, with technology costs and revenue opportunities changing rapidly, colleges' future financial strategies concerning technology will have to be more agile and adaptable than ever. Presents financial models from 20 independent colleges and universities, and discusses how they have been used to define a financial strategy for technology…

A human judgment approach to epidemiological forecasting

PubMed Central

Farrow, David C.; Brooks, Logan C.; Rosenfeld, Roni

2017-01-01

Infectious diseases impose considerable burden on society, despite significant advances in technology and medicine over the past century. Advanced warning can be helpful in mitigating and preparing for an impending or ongoing epidemic. Historically, such a capability has lagged for many reasons, including in particular the uncertainty in the current state of the system and in the understanding of the processes that drive epidemic trajectories. Presently we have access to data, models, and computational resources that enable the development of epidemiological forecasting systems. Indeed, several recent challenges hosted by the U.S. government have fostered an open and collaborative environment for the development of these technologies. The primary focus of these challenges has been to develop statistical and computational methods for epidemiological forecasting, but here we consider a serious alternative based on collective human judgment. We created the web-based “Epicast” forecasting system which collects and aggregates epidemic predictions made in real-time by human participants, and with these forecasts we ask two questions: how accurate is human judgment, and how do these forecasts compare to their more computational, data-driven alternatives? To address the former, we assess by a variety of metrics how accurately humans are able to predict influenza and chikungunya trajectories. As for the latter, we show that real-time, combined human predictions of the 2014–2015 and 2015–2016 U.S. flu seasons are often more accurate than the same predictions made by several statistical systems, especially for short-term targets. We conclude that there is valuable predictive power in collective human judgment, and we discuss the benefits and drawbacks of this approach. PMID:28282375

A human judgment approach to epidemiological forecasting.

PubMed

Farrow, David C; Brooks, Logan C; Hyun, Sangwon; Tibshirani, Ryan J; Burke, Donald S; Rosenfeld, Roni

2017-03-01

Infectious diseases impose considerable burden on society, despite significant advances in technology and medicine over the past century. Advanced warning can be helpful in mitigating and preparing for an impending or ongoing epidemic. Historically, such a capability has lagged for many reasons, including in particular the uncertainty in the current state of the system and in the understanding of the processes that drive epidemic trajectories. Presently we have access to data, models, and computational resources that enable the development of epidemiological forecasting systems. Indeed, several recent challenges hosted by the U.S. government have fostered an open and collaborative environment for the development of these technologies. The primary focus of these challenges has been to develop statistical and computational methods for epidemiological forecasting, but here we consider a serious alternative based on collective human judgment. We created the web-based "Epicast" forecasting system which collects and aggregates epidemic predictions made in real-time by human participants, and with these forecasts we ask two questions: how accurate is human judgment, and how do these forecasts compare to their more computational, data-driven alternatives? To address the former, we assess by a variety of metrics how accurately humans are able to predict influenza and chikungunya trajectories. As for the latter, we show that real-time, combined human predictions of the 2014-2015 and 2015-2016 U.S. flu seasons are often more accurate than the same predictions made by several statistical systems, especially for short-term targets. We conclude that there is valuable predictive power in collective human judgment, and we discuss the benefits and drawbacks of this approach.

Extreme Wind, Rain, Storm Surge, and Flooding: Why Hurricane Impacts are Difficult to Forecast?

NASA Astrophysics Data System (ADS)

Chen, S. S.

2017-12-01

The 2017 hurricane season is estimated as one of the costliest in the U.S. history. The damage and devastation caused by Hurricane Harvey in Houston, Irma in Florida, and Maria in Puerto Rico are distinctly different in nature. The complexity of hurricane impacts from extreme wind, rain, storm surge, and flooding presents a major challenge in hurricane forecasting. A detailed comparison of the storm impacts from Harvey, Irma, and Maria will be presented using observations and state-of-the-art new generation coupled atmosphere-wave-ocean hurricane forecast model. The author will also provide an overview on what we can expect in terms of advancement in science and technology that can help improve hurricane impact forecast in the near future.

Solar Storm GIC Forecasting: Solar Shield Extension Development of the End-User Forecasting System Requirements

NASA Technical Reports Server (NTRS)

Pulkkinen, A.; Mahmood, S.; Ngwira, C.; Balch, C.; Lordan, R.; Fugate, D.; Jacobs, W.; Honkonen, I.

2015-01-01

A NASA Goddard Space Flight Center Heliophysics Science Division-led team that includes NOAA Space Weather Prediction Center, the Catholic University of America, Electric Power Research Institute (EPRI), and Electric Research and Management, Inc., recently partnered with the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) to better understand the impact of Geomagnetically Induced Currents (GIC) on the electric power industry. This effort builds on a previous NASA-sponsored Applied Sciences Program for predicting GIC, known as Solar Shield. The focus of the new DHS S&T funded effort is to revise and extend the existing Solar Shield system to enhance its forecasting capability and provide tailored, timely, actionable information for electric utility decision makers. To enhance the forecasting capabilities of the new Solar Shield, a key undertaking is to extend the prediction system coverage across Contiguous United States (CONUS), as the previous version was only applicable to high latitudes. The team also leverages the latest enhancements in space weather modeling capacity residing at Community Coordinated Modeling Center to increase the Technological Readiness Level, or Applications Readiness Level of the system http://www.nasa.gov/sites/default/files/files/ExpandedARLDefinitions4813.pdf.

The Increase of Power Efficiency of Underground Coal Mining by the Forecasting of Electric Power Consumption

NASA Astrophysics Data System (ADS)

Efremenko, Vladimir; Belyaevsky, Roman; Skrebneva, Evgeniya

2017-11-01

In article the analysis of electric power consumption and problems of power saving on coal mines are considered. Nowadays the share of conditionally constant costs of electric power for providing safe working conditions underground on coal mines is big. Therefore, the power efficiency of underground coal mining depends on electric power expense of the main technological processes and size of conditionally constant costs. The important direction of increase of power efficiency of coal mining is forecasting of a power consumption and monitoring of electric power expense. One of the main approaches to reducing of electric power costs is increase in accuracy of the enterprise demand in the wholesale electric power market. It is offered to use artificial neural networks to forecasting of day-ahead power consumption with hourly breakdown. At the same time use of neural and indistinct (hybrid) systems on the principles of fuzzy logic, neural networks and genetic algorithms is more preferable. This model allows to do exact short-term forecasts at a small array of input data. A set of the input parameters characterizing mining-and-geological and technological features of the enterprise is offered.

Robotics, Artificial Intelligence, Computer Simulation: Future Applications in Special Education.

ERIC Educational Resources Information Center

Moore, Gwendolyn B.; And Others

The report describes three advanced technologies--robotics, artificial intelligence, and computer simulation--and identifies the ways in which they might contribute to special education. A hybrid methodology was employed to identify existing technology and forecast future needs. Following this framework, each of the technologies is defined,…

Application of Satellite Frost Forecast Technology to Other Parts of the United States Phase II: Introduction

NASA Technical Reports Server (NTRS)

1981-01-01

The history and status of University of Michigan and University of Pennsylvania involvement in determining if P-model for front prediction used in Florida is applicable to those geographic locations is reviewed. The possibility of using the S-model to develop a satellite front forecast system that can recall the distribution of temperatures during previous freezes from a particular area and bring that cold climate climatology to bear on present forecasts is discussed as well as a proposed GOES satellite downlink system to sectionalize the data used in Florida.

An experimental system for flood risk forecasting and monitoring at global scale

NASA Astrophysics Data System (ADS)

Dottori, Francesco; Alfieri, Lorenzo; Kalas, Milan; Lorini, Valerio; Salamon, Peter

2017-04-01

Global flood forecasting and monitoring systems are nowadays a reality and are being applied by a wide range of users and practitioners in disaster risk management. Furthermore, there is an increasing demand from users to integrate flood early warning systems with risk based forecasting, combining streamflow estimations with expected inundated areas and flood impacts. Finally, emerging technologies such as crowdsourcing and social media monitoring can play a crucial role in flood disaster management and preparedness. Here, we present some recent advances of an experimental procedure for near-real time flood mapping and impact assessment. The procedure translates in near real-time the daily streamflow forecasts issued by the Global Flood Awareness System (GloFAS) into event-based flood hazard maps, which are then combined with exposure and vulnerability information at global scale to derive risk forecast. Impacts of the forecasted flood events are evaluated in terms of flood prone areas, potential economic damage, and affected population, infrastructures and cities. To increase the reliability of our forecasts we propose the integration of model-based estimations with an innovative methodology for social media monitoring, which allows for real-time verification and correction of impact forecasts. Finally, we present the results of preliminary tests which show the potential of the proposed procedure in supporting emergency response and management.

Six rules for accurate effective forecasting.

PubMed

Saffo, Paul

2007-01-01

The primary goal of forecasting is to identify the full range of possibilities facing a company, society, or the world at large. In this article, Saffo demythologizes the forecasting process to help executives become sophisticated and participative consumers of forecasts, rather than passive absorbers. He illustrates how to use forecasts to at once broaden understanding of possibilities and narrow the decision space within which one must exercise intuition. The events of 9/11, for example, were a much bigger surprise than they should have been. After all, airliners flown into monuments were the stuff of Tom Clancy novels in the 1990s, and everyone knew that terrorists had a very personal antipathy toward the World Trade Center. So why was 9/11 such a surprise? What can executives do to avoid being blind-sided by other such wild cards, be they radical shifts in markets or the seemingly sudden emergence of disruptive technologies? In describing what forecasters are trying to achieve, Saffo outlines six simple, commonsense rules that smart managers should observe as they embark on a voyage of discovery with professional forecasters. Map a cone of uncertainty, he advises, look for the S curve, embrace the things that don't fit, hold strong opinions weakly, look back twice as far as you look forward, and know when not to make a forecast.

Improving wave forecasting by integrating ensemble modelling and machine learning

NASA Astrophysics Data System (ADS)

O'Donncha, F.; Zhang, Y.; James, S. C.

2017-12-01

Modern smart-grid networks use technologies to instantly relay information on supply and demand to support effective decision making. Integration of renewable-energy resources with these systems demands accurate forecasting of energy production (and demand) capacities. For wave-energy converters, this requires wave-condition forecasting to enable estimates of energy production. Current operational wave forecasting systems exhibit substantial errors with wave-height RMSEs of 40 to 60 cm being typical, which limits the reliability of energy-generation predictions thereby impeding integration with the distribution grid. In this study, we integrate physics-based models with statistical learning aggregation techniques that combine forecasts from multiple, independent models into a single "best-estimate" prediction of the true state. The Simulating Waves Nearshore physics-based model is used to compute wind- and currents-augmented waves in the Monterey Bay area. Ensembles are developed based on multiple simulations perturbing input data (wave characteristics supplied at the model boundaries and winds) to the model. A learning-aggregation technique uses past observations and past model forecasts to calculate a weight for each model. The aggregated forecasts are compared to observation data to quantify the performance of the model ensemble and aggregation techniques. The appropriately weighted ensemble model outperforms an individual ensemble member with regard to forecasting wave conditions.

Tsunami Forecast Progress Five Years After Indonesian Disaster

NASA Astrophysics Data System (ADS)

Titov, Vasily V.; Bernard, Eddie N.; Weinstein, Stuart A.; Kanoglu, Utku; Synolakis, Costas E.

2010-05-01

Almost five years after the 26 December 2004 Indian Ocean tragedy, tsunami warnings are finally benefiting from decades of research toward effective model-based forecasts. Since the 2004 tsunami, two seminal advances have been (i) deep-ocean tsunami measurements with tsunameters and (ii) their use in accurately forecasting tsunamis after the tsunami has been generated. Using direct measurements of deep-ocean tsunami heights, assimilated into numerical models for specific locations, greatly improves the real-time forecast accuracy over earthquake-derived magnitude estimates of tsunami impact. Since 2003, this method has been used to forecast tsunamis at specific harbors for different events in the Pacific and Indian Oceans. Recent tsunamis illustrated how this technology is being adopted in global tsunami warning operations. The U.S. forecasting system was used by both research and operations to evaluate the tsunami hazard. Tests demonstrated the effectiveness of operational tsunami forecasting using real-time deep-ocean data assimilated into forecast models. Several examples also showed potential of distributed forecast tools. With IOC and USAID funding, NOAA researchers at PMEL developed the Community Model Interface for Tsunami (ComMIT) tool and distributed it through extensive capacity-building sessions in the Indian Ocean. Over hundred scientists have been trained in tsunami inundation mapping, leading to the first generation of inundation models for many Indian Ocean shorelines. These same inundation models can also be used for real-time tsunami forecasts as was demonstrated during several events. Contact Information Vasily V. Titov, Seattle, Washington, USA, 98115

Ocean state and uncertainty forecasts using HYCOM with Local Ensemble Transfer Kalman Filter (LETKF)

NASA Astrophysics Data System (ADS)

Wei, Mozheng; Hogan, Pat; Rowley, Clark; Smedstad, Ole-Martin; Wallcraft, Alan; Penny, Steve

2017-04-01

An ensemble forecast system based on the US Navy's operational HYCOM using Local Ensemble Transfer Kalman Filter (LETKF) technology has been developed for ocean state and uncertainty forecasts. One of the advantages is that the best possible initial analysis states for the HYCOM forecasts are provided by the LETKF which assimilates the operational observations using ensemble method. The background covariance during this assimilation process is supplied with the ensemble, thus it avoids the difficulty of developing tangent linear and adjoint models for 4D-VAR from the complicated hybrid isopycnal vertical coordinate in HYCOM. Another advantage is that the ensemble system provides the valuable uncertainty estimate corresponding to every state forecast from HYCOM. Uncertainty forecasts have been proven to be critical for the downstream users and managers to make more scientifically sound decisions in numerical prediction community. In addition, ensemble mean is generally more accurate and skilful than the single traditional deterministic forecast with the same resolution. We will introduce the ensemble system design and setup, present some results from 30-member ensemble experiment, and discuss scientific, technical and computational issues and challenges, such as covariance localization, inflation, model related uncertainties and sensitivity to the ensemble size.

Application of Satellite Frost Forecast Technology to Other Parts of the United States

NASA Technical Reports Server (NTRS)

Martsolf, J. D.; Chen, E. (Principal Investigator)

1981-01-01

Thermal infrared data taken from the GOES satellite over a period of several hours was color enhanced by computer according to temperature. The varying temperatures were then used to assist in frost forecasting. Input from Michigan and Pennsylvania to the cold climate mapping project is emphasized in the report of the second year's activities of a two year effort.

Coastal Foredune Evolution, Part 1: Environmental Factors and Forcing Processes Affecting Morphological Evolution

DTIC Science & Technology

2017-02-01

ERDC/CHL CHETN-II-56 February 2017 Approved for public release; distribution is unlimited. Coastal Foredune Evolution, Part 1: Environmental... Coastal and Hydraulics Engineering Technical Note (CHETN) is the first of two CHETNs focused on improving technologies to forecast coastal foredune...morphodynamic evolution of coastal foredunes. Part 2 reviews modeling approaches to forecast these changes and develops a probabilistic modeling framework to

Solar power satellite system definition study. Volume 1, phase 1: Executive summary

NASA Technical Reports Server (NTRS)

1979-01-01

A systems definition study of the solar satellite system (SPS) is presented. The technical feasibility of solar power satellites based on forecasts of technical capability in the various applicable technologies is assessed. The performance, cost, operational characteristics, reliability, and the suitability of SPS's as power generators for typical commercial electricity grids are discussed. The uncertainties inherent in the system characteristics forecasts are assessed.

San Francisco Bay Area Cargo Forecast.

DTIC Science & Technology

1981-06-01

Though sugar manufacturers face competition from non-nutritive sweetners, high fructose corn syrups , and foreign suppliers, the Hawaiian-San...approach, provides background on recent levels of trade, and presents the baseline, high , and low forecasts for 1985, 1990, 2000 and 2020. The major...cargo sectors is cargo that would be carried by high technology ships such as Ro/Ro vessels and barge carriers. In recent years, these vessel designs

Presenting Critical Space Weather Information to Customers and Stakeholders (Invited)

NASA Astrophysics Data System (ADS)

Viereck, R. A.; Singer, H. J.; Murtagh, W. J.; Rutledge, B.

2013-12-01

Space weather involves changes in the near-Earth space environment that impact technological systems such as electric power, radio communication, satellite navigation (GPS), and satellite opeartions. As with terrestrial weather, there are several different kinds of space weather and each presents unique challenges to the impacted technologies and industries. But unlike terrestrial weather, many customers are not fully aware of space weather or how it impacts their systems. This issue is further complicated by the fact that the largest space weather events occur very infrequently with years going by without severe storms. Recent reports have estimated very large potential costs to the economy and to society if a geomagnetic storm were to cause major damage to the electric power transmission system. This issue has come to the attention of emergency managers and federal agencies including the office of the president. However, when considering space weather impacts, it is essential to also consider uncertainties in the frequency of events and the predicted impacts. The unique nature of space weather storms, the specialized technologies that are impacted by them, and the disparate groups and agencies that respond to space weather forecasts and alerts create many challenges to the task of communicating space weather information to the public. Many customers that receive forecasts and alerts are highly technical and knowledgeable about the subtleties of the space environment. Others know very little and require ongoing education and explanation about how a space weather storm will affect their systems. In addition, the current knowledge and understanding of the space environment that goes into forecasting storms is quite immature. It has only been within the last five years that physics-based models of the space environment have played important roles in predictions. Thus, the uncertainties in the forecasts are quite large. There is much that we don't know about space weather and this influences our forecasts. In this presentation, I will discuss the unique challenges that space weather forecasters face when explaining what we know and what we don't know about space weather events to customers and policy makers.

The Rise of Complexity in Flood Forecasting: Opportunities, Challenges and Tradeoffs

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, M. P.; Nijssen, B.

2017-12-01

Operational flood forecasting is currently undergoing a major transformation. Most national flood forecasting services have relied for decades on lumped, highly calibrated conceptual hydrological models running on local office computing resources, providing deterministic streamflow predictions at gauged river locations that are important to stakeholders and emergency managers. A variety of recent technological advances now make it possible to run complex, high-to-hyper-resolution models for operational hydrologic prediction over large domains, and the US National Weather Service is now attempting to use hyper-resolution models to create new forecast services and products. Yet other `increased-complexity' forecasting strategies also exist that pursue different tradeoffs between model complexity (i.e., spatial resolution, physics) and streamflow forecast system objectives. There is currently a pressing need for a greater understanding in the hydrology community of the opportunities, challenges and tradeoffs associated with these different forecasting approaches, and for a greater participation by the hydrology community in evaluating, guiding and implementing these approaches. Intermediate-resolution forecast systems, for instance, use distributed land surface model (LSM) physics but retain the agility to deploy ensemble methods (including hydrologic data assimilation and hindcast-based post-processing). Fully coupled numerical weather prediction (NWP) systems, another example, use still coarser LSMs to produce ensemble streamflow predictions either at the model scale or after sub-grid scale runoff routing. Based on the direct experience of the authors and colleagues in research and operational forecasting, this presentation describes examples of different streamflow forecast paradigms, from the traditional to the recent hyper-resolution, to illustrate the range of choices facing forecast system developers. We also discuss the degree to which the strengths and weaknesses of each strategy map onto the requirements for different types of forecasting services (e.g., flash flooding, river flooding, seasonal water supply prediction).

Condition Based Maintenance Technology Impact Study: Assessment Methods, Study Design and Interim Results

DTIC Science & Technology

2014-07-01

Unified Theory of Acceptance and Use of Technology, Structuration Model of Technology, UNCLASSIFIED DSTO-TR-2992 UNCLASSIFIED 5 Adaptive...Structuration Theory , Model of Mutual Adaptation, Model of Technology Appropriation, Diffusion/Implementation Model, and Tri-core Model, among others [11...simulation gaming essay/scenario writing genius forecasting role play/acting backcasting swot brainstorming relevance tree/logic chart scenario workshop

The NASA Short-term Prediction Research and Transition (SPoRT) Center: A Collaborative Model for Accelerating Research into Operations

NASA Technical Reports Server (NTRS)

Goodman, S. J.; Lapenta, W.; Jedlovec, G.; Dodge, J.; Bradshaw, T.

2003-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, Alabama was created to accelerate the infusion of NASA earth science observations, data assimilation and modeling research into NWS forecast operations and decision-making. The principal focus of experimental products is on the regional scale with an emphasis on forecast improvements on a time scale of 0-24 hours. The SPoRT Center research is aligned with the regional prediction objectives of the US Weather Research Program dealing with 0-1 day forecast issues ranging from convective initiation to 24-hr quantitative precipitation forecasting. The SPoRT Center, together with its other interagency partners, universities, and the NASA/NOAA Joint Center for Satellite Data Assimilation, provides a means and a process to effectively transition NASA Earth Science Enterprise observations and technology to National Weather Service operations and decision makers at both the global/national and regional scales. This paper describes the process for the transition of experimental products into forecast operations, current products undergoing assessment by forecasters, and plans for the future.

Methods of Technological Forecasting,

DTIC Science & Technology

1977-05-01

Trend Extrapolation Progress Curve Analogy Trend Correlation Substitution Analysis or Substitution Growth Curves Envelope Curve Advances in the State of...the Art Technological Mapping Contextual Mapping Matrix Input-Output Analysis Mathematical Models Simulation Models Dynamic Modelling. CHAPTER IV...Generation Interaction between Needs and Possibilities Map of the Technological Future — (‘ross- Impact Matri x Discovery Matrix Morphological Analysis

Representation of transit ITS in network-based travel models

DOT National Transportation Integrated Search

2005-03-01

The increased use of Intelligent Transportation Systems (ITS) technology in public transit has two major impacts on travel forecasting. First, the technology will often result in an improved volume and quality of data that may be used for planning. S...

Cognitive methodology for forecasting oil and gas industry using pattern-based neural information technologies

NASA Astrophysics Data System (ADS)

Gafurov, O.; Gafurov, D.; Syryamkin, V.

2018-05-01

The paper analyses a field of computer science formed at the intersection of such areas of natural science as artificial intelligence, mathematical statistics, and database theory, which is referred to as "Data Mining" (discovery of knowledge in data). The theory of neural networks is applied along with classical methods of mathematical analysis and numerical simulation. The paper describes the technique protected by the patent of the Russian Federation for the invention “A Method for Determining Location of Production Wells during the Development of Hydrocarbon Fields” [1–3] and implemented using the geoinformation system NeuroInformGeo. There are no analogues in domestic and international practice. The paper gives an example of comparing the forecast of the oil reservoir quality made by the geophysicist interpreter using standard methods and the forecast of the oil reservoir quality made using this technology. The technical result achieved shows the increase of efficiency, effectiveness, and ecological compatibility of development of mineral deposits and discovery of a new oil deposit.

A combination of HARMONIE short time direct normal irradiance forecasts and machine learning: The #hashtdim procedure

NASA Astrophysics Data System (ADS)

Gastón, Martín; Fernández-Peruchena, Carlos; Körnich, Heiner; Landelius, Tomas

2017-06-01

The present work describes the first approach of a new procedure to forecast Direct Normal Irradiance (DNI): the #hashtdim that treats to combine ground information and Numerical Weather Predictions. The system is centered in generate predictions for the very short time. It combines the outputs from the Numerical Weather Prediction Model HARMONIE with an adaptive methodology based on Machine Learning. The DNI predictions are generated with 15-minute and hourly temporal resolutions and presents 3-hourly updates. Each update offers forecasts to the next 12 hours, the first nine hours are generated with 15-minute temporal resolution meanwhile the last three hours present hourly temporal resolution. The system is proved over a Spanish emplacement with BSRN operative station in south of Spain (PSA station). The #hashtdim has been implemented in the framework of the Direct Normal Irradiance Nowcasting methods for optimized operation of concentrating solar technologies (DNICast) project, under the European Union's Seventh Programme for research, technological development and demonstration framework.

Gloom and doom? The future of marine capture fisheries

PubMed Central

Garcia, Serge M.; Grainger, Richard J. R.

2005-01-01

Predicting global fisheries is a high-order challenge but predictions have been made and updates are needed. Past forecasts, present trends and perspectives of key parameters of the fisheries—including potential harvest, state of stocks, supply and demand, trade, fishing technology and governance—are reviewed in detail, as the basis for new forecasts and forecasting performance assessment. The future of marine capture fisheries will be conditioned by the political, social and economic evolution of the world within which they operate. Consequently, recent global scenarios for the future world are reviewed, with the emphasis on fisheries. The main driving forces (e.g. global economic development, demography, environment, public awareness, information technology, energy, ethics) including aquaculture are described. Outlooks are provided for each aspect of the fishery sector. The conclusion puts these elements in perspective and offers the authors’ personal interpretation of the possible future pathway of fisheries, the uncertainty about it and the still unanswered questions of direct relevance in shaping that future. PMID:15713587

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Max; Smith, Sarah J.; Sohn, Michael D.

Fuel cells are both a longstanding and emerging technology for stationary and transportation applications, and their future use will likely be critical for the deep decarbonization of global energy systems. As we look into future applications, a key challenge for policy-makers and technology market forecasters who seek to track and/or accelerate their market adoption is the ability to forecast market costs of the fuel cells as technology innovations are incorporated into market products. Specifically, there is a need to estimate technology learning rates, which are rates of cost reduction versus production volume. Unfortunately, no literature exists for forecasting future learningmore » rates for fuel cells. In this paper, we look retrospectively to estimate learning rates for two fuel cell deployment programs: (1) the micro-combined heat and power (CHP) program in Japan, and (2) the Self-Generation Incentive Program (SGIP) in California. These two examples have a relatively broad set of historical market data and thus provide an informative and international comparison of distinct fuel cell technologies and government deployment programs. We develop a generalized procedure for disaggregating experience-curve cost-reductions in order to disaggregate the Japanese fuel cell micro-CHP market into its constituent components, and we derive and present a range of learning rates that may explain observed market trends. Finally, we explore the differences in the technology development ecosystem and market conditions that may have contributed to the observed differences in cost reduction and draw policy observations for the market adoption of future fuel cell technologies. The scientific and policy contributions of this paper are the first comparative experience curve analysis of past fuel cell technologies in two distinct markets, and the first quantitative comparison of a detailed cost model of fuel cell systems with actual market data. The resulting approach is applicable to analyzing other fuel cell markets and other energy-related technologies, and highlights the data needed for cost modeling and quantitative assessment of key cost reduction components.« less

SWIFT2: Software for continuous ensemble short-term streamflow forecasting for use in research and operations

NASA Astrophysics Data System (ADS)

Perraud, Jean-Michel; Bennett, James C.; Bridgart, Robert; Robertson, David E.

2016-04-01

Research undertaken through the Water Information Research and Development Alliance (WIRADA) has laid the foundations for continuous deterministic and ensemble short-term forecasting services. One output of this research is the software Short-term Water Information Forecasting Tools version 2 (SWIFT2). SWIFT2 is developed for use in research on short term streamflow forecasting techniques as well as operational forecasting services at the Australian Bureau of Meteorology. The variety of uses in research and operations requires a modular software system whose components can be arranged in applications that are fit for each particular purpose, without unnecessary software duplication. SWIFT2 modelling structures consist of sub-areas of hydrologic models, nodes and links with in-stream routing and reservoirs. While this modelling structure is customary, SWIFT2 is built from the ground up for computational and data intensive applications such as ensemble forecasts necessary for the estimation of the uncertainty in forecasts. Support for parallel computation on multiple processors or on a compute cluster is a primary use case. A convention is defined to store large multi-dimensional forecasting data and its metadata using the netCDF library. SWIFT2 is written in modern C++ with state of the art software engineering techniques and practices. A salient technical feature is a well-defined application programming interface (API) to facilitate access from different applications and technologies. SWIFT2 is already seamlessly accessible on Windows and Linux via packages in R, Python, Matlab and .NET languages such as C# and F#. Command line or graphical front-end applications are also feasible. This poster gives an overview of the technology stack, and illustrates the resulting features of SWIFT2 for users. Research and operational uses share the same common core C++ modelling shell for consistency, but augmented by different software modules suitable for each context. The accessibility via interactive modelling languages is particularly amenable to using SWIFT2 in exploratory research, with a dynamic and versatile experimental modelling workflow. This does not come at the expense of the stability and reliability required for use in operations, where only mature and stable components are used.

A patent survey case: how could technological forecasting help cosmetic chemists with product innovation?

PubMed

Domicio Da Silva Souza, Ivan; Juliana Pinheiro, Bárbara; Passarini Takahashi, Vania

2012-01-01

Patents represent a free and open source of data for studying innovation and forecasting technological trends. Thus, we suggest that new discussions about the role of patent information are needed. To illustrate the relevance of this issue, we performed a survey of patents involving skin care products, which were granted by the United States Patent and Trademark Office (USPTO) between 2006 and 2010, to identify opportunities for innovation and technological trends. We quantified the use of technologies in 333 patents. We plotted a life cycle of technologies related to natural ingredients. We also determined the cross impact of the technologies identified. We observed technologies related to processes applied to cosmetics (2.2%), functional packaging and applicators (2.9%), excipients and active compounds (21.5%), and cosmetic preparations (73.5%). Further, 21.6% of the patents were related to the use of natural ingredients. Several opportunities for innovation were discussed throughout this paper, for example, the use of peptides as active compounds or intracellular carriers (only 3.9% of the technologies in cosmetic preparations). We also observed technological cross impacts that suggested a trend toward multifunctional cosmetics, among others. Patent surveys may help researchers with product innovation because they allow us to identify available and unexplored technologies and turn them into whole new concepts.

Verification of Meteorological and Oceanographic Ensemble Forecasts in the U.S. Navy

NASA Astrophysics Data System (ADS)

Klotz, S.; Hansen, J.; Pauley, P.; Sestak, M.; Wittmann, P.; Skupniewicz, C.; Nelson, G.

2013-12-01

The Navy Ensemble Forecast Verification System (NEFVS) has been promoted recently to operational status at the U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). NEFVS processes FNMOC and National Centers for Environmental Prediction (NCEP) meteorological and ocean wave ensemble forecasts, gridded forecast analyses, and innovation (observational) data output by FNMOC's data assimilation system. The NEFVS framework consists of statistical analysis routines, a variety of pre- and post-processing scripts to manage data and plot verification metrics, and a master script to control application workflow. NEFVS computes metrics that include forecast bias, mean-squared error, conditional error, conditional rank probability score, and Brier score. The system also generates reliability and Receiver Operating Characteristic diagrams. In this presentation we describe the operational framework of NEFVS and show examples of verification products computed from ensemble forecasts, meteorological observations, and forecast analyses. The construction and deployment of NEFVS addresses important operational and scientific requirements within Navy Meteorology and Oceanography. These include computational capabilities for assessing the reliability and accuracy of meteorological and ocean wave forecasts in an operational environment, for quantifying effects of changes and potential improvements to the Navy's forecast models, and for comparing the skill of forecasts from different forecast systems. NEFVS also supports the Navy's collaboration with the U.S. Air Force, NCEP, and Environment Canada in the North American Ensemble Forecast System (NAEFS) project and with the Air Force and the National Oceanic and Atmospheric Administration (NOAA) in the National Unified Operational Prediction Capability (NUOPC) program. This program is tasked with eliminating unnecessary duplication within the three agencies, accelerating the transition of new technology, such as multi-model ensemble forecasting, to U.S. Department of Defense use, and creating a superior U.S. global meteorological and oceanographic prediction capability. Forecast verification is an important component of NAEFS and NUOPC. Distribution Statement A: Approved for Public Release; distribution is unlimited

Verification of Meteorological and Oceanographic Ensemble Forecasts in the U.S. Navy

NASA Astrophysics Data System (ADS)

Klotz, S. P.; Hansen, J.; Pauley, P.; Sestak, M.; Wittmann, P.; Skupniewicz, C.; Nelson, G.

2012-12-01

The Navy Ensemble Forecast Verification System (NEFVS) has been promoted recently to operational status at the U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). NEFVS processes FNMOC and National Centers for Environmental Prediction (NCEP) meteorological and ocean wave ensemble forecasts, gridded forecast analyses, and innovation (observational) data output by FNMOC's data assimilation system. The NEFVS framework consists of statistical analysis routines, a variety of pre- and post-processing scripts to manage data and plot verification metrics, and a master script to control application workflow. NEFVS computes metrics that include forecast bias, mean-squared error, conditional error, conditional rank probability score, and Brier score. The system also generates reliability and Receiver Operating Characteristic diagrams. In this presentation we describe the operational framework of NEFVS and show examples of verification products computed from ensemble forecasts, meteorological observations, and forecast analyses. The construction and deployment of NEFVS addresses important operational and scientific requirements within Navy Meteorology and Oceanography (METOC). These include computational capabilities for assessing the reliability and accuracy of meteorological and ocean wave forecasts in an operational environment, for quantifying effects of changes and potential improvements to the Navy's forecast models, and for comparing the skill of forecasts from different forecast systems. NEFVS also supports the Navy's collaboration with the U.S. Air Force, NCEP, and Environment Canada in the North American Ensemble Forecast System (NAEFS) project and with the Air Force and the National Oceanic and Atmospheric Administration (NOAA) in the National Unified Operational Prediction Capability (NUOPC) program. This program is tasked with eliminating unnecessary duplication within the three agencies, accelerating the transition of new technology, such as multi-model ensemble forecasting, to U.S. Department of Defense use, and creating a superior U.S. global meteorological and oceanographic prediction capability. Forecast verification is an important component of NAEFS and NUOPC.

Technology Alignment and Portfolio Prioritization (TAPP)

NASA Technical Reports Server (NTRS)

Funaro, Gregory V.; Alexander, Reginald A.

2015-01-01

Technology Alignment and Portfolio Prioritization (TAPP) is a method being developed by the Advanced Concepts Office, at NASA Marshall Space Flight Center. The TAPP method expands on current technology assessment methods by incorporating the technological structure underlying technology development, e.g., organizational structures and resources, institutional policy and strategy, and the factors that motivate technological change. This paper discusses the methods ACO is currently developing to better perform technology assessments while taking into consideration Strategic Alignment, Technology Forecasting, and Long Term Planning.

Medium- and long-term electric power demand forecasting based on the big data of smart city

NASA Astrophysics Data System (ADS)

Wei, Zhanmeng; Li, Xiyuan; Li, Xizhong; Hu, Qinghe; Zhang, Haiyang; Cui, Pengjie

2017-08-01

Based on the smart city, this paper proposed a new electric power demand forecasting model, which integrates external data such as meteorological information, geographic information, population information, enterprise information and economic information into the big database, and uses an improved algorithm to analyse the electric power demand and provide decision support for decision makers. The data mining technology is used to synthesize kinds of information, and the information of electric power customers is analysed optimally. The scientific forecasting is made based on the trend of electricity demand, and a smart city in north-eastern China is taken as a sample.

NASA Launches NOAA Weather Satellite to Improve Forecasts

NASA Image and Video Library

2017-11-18

Early on the morning of Saturday, Nov. 18, NASA successfully launched for the National Oceanic and Atmospheric Administration (NOAA) the first in a series of four advanced polar-orbiting satellites, equipped with next-generation technology and designed to improve the accuracy of U.S. weather forecasts out to seven days. The Joint Polar Satellite System-1 (JPSS-1) lifted off on a United Launch Alliance Delta II rocket from Vandenberg Air Force Base on California’s central coast. JPSS-1 data will improve weather forecasting and help agencies involved with post-storm recovery by visualizing storm damage and the geographic extent of power outages.

The MST radar technique: Requirements for operational weather forecasting

NASA Technical Reports Server (NTRS)

Larsen, M. F.

1983-01-01

There is a feeling that the accuracy of mesoscale forecasts for spatial scales of less than 1000 km and time scales of less than 12 hours can be improved significantly if resources are applied to the problem in an intensive effort over the next decade. Since the most dangerous and damaging types of weather occur at these scales, there are major advantages to be gained if such a program is successful. The interest in improving short term forecasting is evident. The technology at the present time is sufficiently developed, both in terms of new observing systems and the computing power to handle the observations, to warrant an intensive effort to improve stormscale forecasting. An assessment of the extent to which the so-called MST radar technique fulfills the requirements for an operational mesoscale observing network is reviewed and the extent to which improvements in various types of forecasting could be expected if such a network is put into operation are delineated.

Study on Battery Capacity for Grid-connection Power Planning with Forecasts in Clustered Photovoltaic Systems

NASA Astrophysics Data System (ADS)

Shimada, Takae; Kawasaki, Norihiro; Ueda, Yuzuru; Sugihara, Hiroyuki; Kurokawa, Kosuke

This paper aims to clarify the battery capacity required by a residential area with densely grid-connected photovoltaic (PV) systems. This paper proposes a planning method of tomorrow's grid-connection power from/to the external electric power system by using demand power forecasting and insolation forecasting for PV power predictions, and defines a operation method of the electricity storage device to control the grid-connection power as planned. A residential area consisting of 389 houses consuming 2390 MWh/year of electricity with 2390kW PV systems is simulated based on measured data and actual forecasts. The simulation results show that 8.3MWh of battery capacity is required in the conditions of half-hour planning and 1% or less of planning error ratio and PV output limiting loss ratio. The results also show that existing technologies of forecasting reduce required battery capacity to 49%, and increase the allowable installing PV amount to 210%.

Biological Invasions: A Challenge In Ecological Forecasting

NASA Technical Reports Server (NTRS)

Schnase, J. L.; Smith, J. A.; Stohlgren, T. J.; Graves, S.; Trees, C.; Rood, Richard (Technical Monitor)

2002-01-01

The spread of invasive species is one of the most daunting environmental, economic, and human-health problems facing the United States and the World today. It is one of several grand challenge environmental problems being considered by NASA's Earth Science Vision for 2025. The invasive species problem is complex and presents many challenges. Developing an invasive species predictive capability could significantly advance the science and technology of ecological forecasting.

Informing policy makers about future health spending: a comparative analysis of forecasting methods in OECD countries.

PubMed

Astolfi, Roberto; Lorenzoni, Luca; Oderkirk, Jillian

2012-09-01

Concerns about health care expenditure growth and its long-term sustainability have risen to the top of the policy agenda in many OECD countries. As continued growth in spending places pressure on government budgets, health services provision and patients' personal finances, policy makers have launched forecasting projects to support policy planning. This comparative analysis reviewed 25 models that were developed for policy analysis in OECD countries by governments, research agencies, academics and international organisations. We observed that the policy questions that need to be addressed drive the choice of forecasting model and the model's specification. By considering both the level of aggregation of the units analysed and the level of detail of health expenditure to be projected, we identified three classes of models: micro, component-based, and macro. Virtually all models account for demographic shifts in the population, while two important influences on health expenditure growth that are the least understood include technological innovation and health-seeking behaviour. The landscape for health forecasting models is dynamic and evolving. Advances in computing technology and increases in data granularity are opening up new possibilities for the generation of system of models which become an on-going decision support tool capable of adapting to new questions as they arise. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Using constructed analogs to improve the skill of National Multi-Model Ensemble March–April–May precipitation forecasts in equatorial East Africa

USGS Publications Warehouse

Shukla, Shraddhanand; Funk, Christopher C.; Hoell, Andrew

2014-01-01

In this study we implement and evaluate a simple 'hybrid' forecast approach that uses constructed analogs (CA) to improve the National Multi-Model Ensemble's (NMME) March–April–May (MAM) precipitation forecasts over equatorial eastern Africa (hereafter referred to as EA, 2°S to 8°N and 36°E to 46°E). Due to recent declines in MAM rainfall, increases in population, land degradation, and limited technological advances, this region has become a recent epicenter of food insecurity. Timely and skillful precipitation forecasts for EA could help decision makers better manage their limited resources, mitigate socio-economic losses, and potentially save human lives. The 'hybrid approach' described in this study uses the CA method to translate dynamical precipitation and sea surface temperature (SST) forecasts over the Indian and Pacific Oceans (specifically 30°S to 30°N and 30°E to 270°E) into terrestrial MAM precipitation forecasts over the EA region. In doing so, this approach benefits from the post-1999 teleconnection that exists between precipitation and SSTs over the Indian and tropical Pacific Oceans (Indo-Pacific) and EA MAM rainfall. The coupled atmosphere-ocean dynamical forecasts used in this study were drawn from the NMME. We demonstrate that while the MAM precipitation forecasts (initialized in February) skill of the NMME models over the EA region itself is negligible, the ranked probability skill score of hybrid CA forecasts based on Indo-Pacific NMME precipitation and SST forecasts reach up to 0.45.

Improved potential fishing zone forecast along East coast of India.

NASA Astrophysics Data System (ADS)

Srinivasa Rao, N.; Rao, M. V.; Chowdhary, S. B.; Rao, K. H.; Ramana, I. V.

Marine fisheries provide support to millions of fishermen community in terms of their living and livelihood Remote sensing technology proved to be useful for successful fishing in reducing time fuel and manpower because of its synoptic coverage Potential Fishing Zone PFZ forecast is being provided to the fishing industry in near-real time since 1992 using SST data derived from NOAA AVHRR thermal IR channel Retrieval of chlorophyll and its mapping has been done over Bay of Bengal from IRS-P4 OCM data Synergetic study of SST and chlorophyll has been established and implemented recently for an improved PFZ forecast The validation of these forecasts revealed 2-3 fold increases in fish catch along east coast of India This program provides socio-economic benefits to the fishermen living all along the Indian coast

Forecast of jet engine exhaust emissions for future high altitude commercial aircraft

NASA Technical Reports Server (NTRS)

Grobman, J.; Ingebo, R. D.

1974-01-01

Projected minimum levels of engine exhaust emissions that may be practicably achievable for future commercial aircraft operating at high altitude cruise conditions are presented. The forecasts are based on: (1) current knowledge of emission characteristics of combustors and augmentors; (2) the current status of combustion research in emission reduction technology; (3) predictable trends in combustion systems and operating conditions as required for projected engine designs that are candidates for advanced subsonic or supersonic commercial aircraft. Results are presented for cruise conditions in terms of an emission index, g pollutant/kg fuel. Two sets of engine exhaust emission predictions are presented: the first, based on an independent NASA study and the second, based on the consensus of an ad hoc committee composed of industry, university, and government representatives. The consensus forecasts are in general agreement with the NASA forecasts.

Forecast of jet engine exhaust emissions for future high altitude commercial aircraft

NASA Technical Reports Server (NTRS)

Grobman, J.; Ingebo, R. D.

1974-01-01

Projected minimum levels of engine exhaust emissions that may be practicably achievable for future commercial aircraft operating at high altitude cruise conditions are presented. The forecasts are based on: (1) current knowledge of emission characteristics of combustors and augmentors; (2) the current status of combustion research in emission reduction technology; and (3) predictable trends in combustion systems and operating conditions as required for projected engine designs that are candidates for advanced subsonic or supersonic commercial aircraft. Results are presented for cruise conditions in terms of an emission index, g pollutant/kg fuel. Two sets of engine exhaust emission predictions are presented: the first, based on an independent NASA study and the second, based on the consensus of an ad hoc committee composed of industry, university, and government representatives. The consensus forecasts are in general agreement with the NASA forecasts.

The impact of earth resources exploration from space. [technology assessment/LANDSAT satellites -technological forecasting

NASA Technical Reports Server (NTRS)

Nordberg, W.

1975-01-01

The use of Earth Resources Technology Satellites in solving global problems is examined. Topics discussed are: (1) management of food, water, and fiber resources; (2) exploration and management of energy and mineral resources; (3) protection of the environment; (4) protection of life and property; and (5) improvements in shipping and navigation.

Robotic Technology: An Assessment and Forecast,

DTIC Science & Technology

1984-07-01

Research Associates# Inc. Dr. Roger Nagel# Lehigh University Dr. Charles Rosen# Machine Intelligence Corporations and Mr. Jack Thornton# Robot Insider...amr (Subcontractors: systems for assembly and Adopt Technology# inspection Stanford University. SRI) AFSC MANTECH o McDonnell Douglas o Machine ...supervisory controls man- machine interaction and system integration. - .. _ - Foreign R& The U.S. faces a strong technological challenge in robotics from

32 CFR Appendix F to Part 651 - Glossary

Code of Federal Regulations, 2013 CFR

2013-07-01

.... ASA(AL&T) Assistant Secretary of the Army (Acquisition, Logistics, and Technology). ASA(FM) Assistant.../Cost Analysis. EICS Environmental Impact Computer System. EIFS Economic Impact Forecast System. EIS... Record of Non-Applicability. RSC Regional Support Command. S&T Science and Technology. SA Secretary of...

32 CFR Appendix F to Part 651 - Glossary

Code of Federal Regulations, 2012 CFR

2012-07-01

.... ASA(AL&T) Assistant Secretary of the Army (Acquisition, Logistics, and Technology). ASA(FM) Assistant.../Cost Analysis. EICS Environmental Impact Computer System. EIFS Economic Impact Forecast System. EIS... Record of Non-Applicability. RSC Regional Support Command. S&T Science and Technology. SA Secretary of...

32 CFR Appendix F to Part 651 - Glossary

Code of Federal Regulations, 2014 CFR

2014-07-01

.... ASA(AL&T) Assistant Secretary of the Army (Acquisition, Logistics, and Technology). ASA(FM) Assistant.../Cost Analysis. EICS Environmental Impact Computer System. EIFS Economic Impact Forecast System. EIS... Record of Non-Applicability. RSC Regional Support Command. S&T Science and Technology. SA Secretary of...

New technology for using meteorological information in forest insect pest forecast and warning systems.

PubMed

Qin, Jiang-Lin; Yang, Xiu-Hao; Yang, Zhong-Wu; Luo, Ji-Tong; Lei, Xiu-Feng

2017-12-01

Near surface air temperature and rainfall are major weather factors affecting forest insect dynamics. The recent developments in remote sensing retrieval and geographic information system spatial analysis techniques enable the utilization of weather factors to significantly enhance forest pest forecasting and warning systems. The current study focused on building forest pest digital data structures as a platform of correlation analysis between weather conditions and forest pest dynamics for better pest forecasting and warning systems using the new technologies. The study dataset contained 3 353 425 small polygons with 174 defined attributes covering 95 counties of Guangxi province of China currently registering 292 forest pest species. Field data acquisition and information transfer systems were established with four software licences that provided 15-fold improvement compared to the systems currently used in China. Nine technical specifications were established including codes of forest districts, pest species and host tree species, and standard practices of forest pest monitoring and information management. Attributes can easily be searched using ArcGIS9.3 and/or the free QGIS2.16 software. Small polygons with pest relevant attributes are a new tool of precision farming and detailed forest insect pest management that are technologically advanced. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Analysis of Science and Technology Trend Based on Word Usage in Digitized Books

NASA Astrophysics Data System (ADS)

Yun, Jinhyuk; Kim, Pan-Jun; Jeong, Hawoong

2013-03-01

Throughout mankind's history, forecasting and predicting future has been a long-lasting interest to our society. Many fortune-tellers have tried to forecast the future by ``divine'' items. Sci-fi writers have also imagined what the future would look like. However most of them have been illogical and unscientific. Meanwhile, scientists have also attempted to discover future trend of science. Many researchers have used quantitative models to study how new ideas are used and spread. Besides the modeling works, in the early 21st century, the rise of data science has provided another prospect of forecasting future. However many studies have focused on very limited set of period or age, due to the limitations of dataset. Hence, many questions still remained unanswered. Fortunately, Google released a new dataset named ``Google N-Gram Dataset.'' This dataset provides us with 5 million words worth of literature dating from 1520 to 2008, and this is nearly 4% of publications ever printed. With this new time-varying dataset, we studied the spread and development of technologies by searching ``Science and Technology'' related words from 1800 to 2000. By statistical analysis, some general scaling laws were discovered. And finally, we determined factors that strongly affect the lifecycle of a word.

Sensor network based solar forecasting using a local vector autoregressive ridge framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, J.; Yoo, S.; Heiser, J.

2016-04-04

The significant improvements and falling costs of photovoltaic (PV) technology make solar energy a promising resource, yet the cloud induced variability of surface solar irradiance inhibits its effective use in grid-tied PV generation. Short-term irradiance forecasting, especially on the minute scale, is critically important for grid system stability and auxiliary power source management. Compared to the trending sky imaging devices, irradiance sensors are inexpensive and easy to deploy but related forecasting methods have not been well researched. The prominent challenge of applying classic time series models on a network of irradiance sensors is to address their varying spatio-temporal correlations duemore » to local changes in cloud conditions. We propose a local vector autoregressive framework with ridge regularization to forecast irradiance without explicitly determining the wind field or cloud movement. By using local training data, our learned forecast model is adaptive to local cloud conditions and by using regularization, we overcome the risk of overfitting from the limited training data. Our systematic experimental results showed an average of 19.7% RMSE and 20.2% MAE improvement over the benchmark Persistent Model for 1-5 minute forecasts on a comprehensive 25-day dataset.« less

STAR 21, Technology Forecast Assessments. Strategic Technologies for the Army of the Twenty-First Century

DTIC Science & Technology

1993-01-01

offspring with the desired combinations of characteristics) and protected from diseases and insects through antibiotics and pesticides . Biotechnology...William D. Stephens, U.S. Army Missile Command Systems Panels Airborne Systems Panel Richard S. Shevell (Chairman), Stanford University Basil S. Papadales

No Computer Left Behind

ERIC Educational Resources Information Center

Cohen, Daniel J.; Rosenzweig, Roy

2006-01-01

The combination of the Web and the cell phone forecasts the end of the inexpensive technologies of multiple-choice tests and grading machines. These technological developments are likely to bring the multiple-choice test to the verge of obsolescence, mounting a substantial challenge to the presentation of history and other disciplines.

Methods for Predicting and Assessing the Impact of Technology on Human Resource Parameters: Report of the Literature. Final Report.

ERIC Educational Resources Information Center

Potter, Norman R.; Dieterly, Duncan L.

The literature review was undertaken to establish the current status of the methodology for forecasting and assessing technology and for quantizing human resource parameters with respect to the impact of incoming technologies. The review of 140 selected documents applicable to the study was undertaken with emphasis on the identification of methods…

Economic and Technology Forecasts for the 80's: Implications for Careers. Proceedings of the Patterns Conference (Rochester Institute of Technology, May 1979).

ERIC Educational Resources Information Center

Nystrom, Dennis; And Others

Selected technological and research areas that may affect emerging careers and work expectations were discussed in the five seminar presentations contained in this proceedings. In the introductory section, Dennis Nystrom outlines the goals of the conference and suggests possible implications. Sar Levitan, in the keynote address, examines the…

Forecasting the impact of virtual environment technology on maintenance training

NASA Technical Reports Server (NTRS)

Schlager, Mark S.; Boman, Duane; Piantanida, Tom; Stephenson, Robert

1993-01-01

To assist NASA and the Air Force in determining how and when to invest in virtual environment (VE) technology for maintenance training, we identified possible roles for VE technology in such training, assessed its cost-effectiveness relative to existing technologies, and formulated recommendations for a research agenda that would address instructional and system development issues involved in fielding a VE training system. In the first phase of the study, we surveyed VE developers to forecast capabilities, maturity, and estimated costs for VE component technologies. We then identified maintenance tasks and their training costs through interviews with maintenance technicians, instructors, and training developers. Ten candidate tasks were selected from two classes of maintenance tasks (seven aircraft maintenance and three space maintenance) using five criteria developed to identify types of tasks most likely to benefit from VE training. Three tasks were used as specific cases for cost-benefit analysis. In formulating research recommendations, we considered three aspects of feasibility: technological considerations, cost-effectiveness, and anticipated R&D efforts. In this paper, we describe the major findings in each of these areas and suggest research efforts that we believe will help achieve the goal of a cost-effective VE maintenance training system by the next decade.

A Historical Review of Brayton and Stirling Power Conversion Technologies for Space Applications

NASA Technical Reports Server (NTRS)

Mason, Lee S.; Schreiber, Jeffrey G.

2007-01-01

Dynamic power conversion technologies, such as closed Brayton and free-piston Stirling, offer many advantages for space power applications including high efficiency, long life, and attractive scaling characteristics. This paper presents a historical review of Brayton and Stirling power conversion technology for space and discusses on-going development activities in order to illustrate current technology readiness. The paper also presents a forecast of potential future space uses of these power technologies.

Development of predictive weather scenarios for early prediction of rice yield in South Korea

NASA Astrophysics Data System (ADS)

Shin, Y.; Cho, J.; Jung, I.

2017-12-01

International grain prices are becoming unstable due to frequent occurrence of abnormal weather phenomena caused by climate change. Early prediction of grain yield using weather forecast data is important for stabilization of international grain prices. The APEC Climate Center (APCC) is providing seasonal forecast data based on monthly climate prediction models for global seasonal forecasting services. The 3-month and 6-month seasonal forecast data using the multi-model ensemble (MME) technique are provided in their own website, ADSS (APCC Data Service System, http://adss.apcc21.org/). The spatial resolution of seasonal forecast data for each individual model is 2.5°×2.5°(about 250km) and the time scale is created as monthly. In this study, we developed customized weather forecast scenarios that are combined seasonal forecast data and observational data apply to early rice yield prediction model. Statistical downscale method was applied to produce meteorological input data of crop model because field scale crop model (ORYZA2000) requires daily weather data. In order to determine whether the forecasting data is suitable for the crop model, we produced spatio-temporal downscaled weather scenarios and evaluated the predictability by comparison with observed weather data at 57 ASOS stations in South Korea. The customized weather forecast scenarios can be applied to various application fields not only early rice yield prediction. Acknowledgement This work was carried out with the support of "Cooperative Research Program for Agriculture Science and Technology Development (Project No: PJ012855022017)" Rural Development Administration, Republic of Korea.

Practical Application of Modern Forecasting and Decision Tools at an Operational River Management Agency

NASA Astrophysics Data System (ADS)

Jawdy, C. M.; Carney, S.; Barber, N. M.; Balk, B. C.; Miller, G. A.

2017-12-01

The Tennessee Valley Authority (TVA) recently completed a complete overhaul of our River Forecast System (RFS). This modernization effort encompassed: uplift or addition of 89 data feeds calibration of a 140 subbasin rainfall-runoff model calibration of over 650 miles of hydraulic routings implementation of a decision optimization routine for 29 reservoirs implementation of hydrothermal forecast models for five river-cooled thermal plants creation of decision-friendly displays creation of a user-friendly wiki creation of a robust reporting system This talk will walk attendees through how a 24x7 river and grid management agency made decisions around how to operationalize the latest technologies in hydrology, hydraulics, decision science and information technology. The tradeoffs inherent in such an endeavor will be discussed so that research-oriented attendees can understand how best to align their research if they desire adoption within industry. More industry-oriented attendees can learn about the mechanics of how to succeed at such a large and complex project. Following the description of the modernization project, I can discuss TVA's plans for future growth of the system. We plan to add the following capabilities in the coming years: forecast verification tools to communicate floodplain risk tools to choose the best possible model forcings ensemble inflow modelling a river policy that allows for more reasonable tradeoff of benefits river decisions based on ensembles The iterative staging of such improvements is highly fraught with technical, political and operational risks. I will discuss how TVA's is using what we learned in the RFS modernization effort to grow further into delivering on the promise of these additional technologies.

Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

NASA Astrophysics Data System (ADS)

Mishra, D.; Goyal, P.

2014-12-01

Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

Tech Review and Forecast for 2013

ERIC Educational Resources Information Center

Breeding, Marshall

2012-01-01

As another year draws to a close, the author reflects on the trends in play related to library technologies and attempts to anticipate their trajectory going forward. The library economy has not necessarily achieved full recovery from the recent downturn. Nevertheless, the author expects that investments in technology will expand next year. For…

Benefit assessment of NASA space technology goals

NASA Technical Reports Server (NTRS)

1976-01-01

The socio-economic benefits to be derived from system applications of space technology goals developed by NASA were assessed. Specific studies include: electronic mail; personal telephone communications; weather and climate monitoring, prediction, and control; crop production forecasting and water availability; planetary engineering of the planet Venus; and planetary exploration.

How Reliable is the Temperature Forecast?

ERIC Educational Resources Information Center

Christmann, Edwin P.

2005-01-01

Project 2061 suggests "technology provides the eyes and ears of science--and some of the muscle too. The electronic computer, for example, has led to substantial progress in the study of weather systems...." Obviously, now that teachers have access to a kaleidoscope of technological advancements, middle school science teachers can engage students…

The Information Highway as Revolution or Evolution?

ERIC Educational Resources Information Center

Esrock, Stuart L.

1997-01-01

Suggests that society is more likely in the midst of an information evolution, rather than a revolution. Uses new media technology and forecasting literatures as a framework to evaluate current technology developments and public discussion about the information highway. Compares the hopeful rhetoric that surrounds the information highway to…

Application of Neural Network Technologies for Price Forecasting in the Liberalized Electricity Market

NASA Astrophysics Data System (ADS)

Gerikh, Valentin; Kolosok, Irina; Kurbatsky, Victor; Tomin, Nikita

2009-01-01

The paper presents the results of experimental studies concerning calculation of electricity prices in different price zones in Russia and Europe. The calculations are based on the intelligent software "ANAPRO" that implements the approaches based on the modern methods of data analysis and artificial intelligence technologies.

STEM: Science Technology Engineering Mathematics. State-Level Analysis

ERIC Educational Resources Information Center

Carnevale, Anthony P.; Smith, Nicole; Melton, Michelle

2011-01-01

The science, technology, engineering, and mathematics (STEM) state-level analysis provides policymakers, educators, state government officials, and others with details on the projections of STEM jobs through 2018. This report delivers a state-by-state snapshot of the demand for STEM jobs, including: (1) The number of forecast net new and…

Editorial: Global Science and Technology in Undergraduate Science and Engineering Education.

ERIC Educational Resources Information Center

Paldy, Lester G., Ed.

1984-01-01

Offers reasons why students should be exposed to and understand the implications of the global character of science and technology. Examples of scientific/technical issues and problems which are global in their scope are long-term atmospheric warming trends, weather forecasting, desertification, earthquake prediction, acid rain, and nuclear…

Bridging the Gap Between Research and Operations in the National Weather Service: The Huntsville Model

NASA Technical Reports Server (NTRS)

Darden, C.; Carroll, B.; Lapenta, W.; Jedlovec, G.; Goodman, S.; Bradshaw, T.; Gordon, J.; Arnold, James E. (Technical Monitor)

2002-01-01

The National Weather Service Office (WFO) in Huntsville, Alabama (HUN) is slated to begin full-time operations in early 2003. With the opening of the Huntsville WFO, a unique opportunity has arisen for close and productive collaboration with scientists at NASA Marshall Space Flight Center (MSFC) and the University of Alabama Huntsville (UAH). As a part of the collaboration effort, NASA has developed the Short-term Prediction Research and Transition (SPoRT) Center. The mission of the SPoRT center is to incorporate NASA earth science technology and research into the NWS operational environment. Emphasis will be on improving mesoscale and short-term forecasting in the first 24 hours of the forecast period. As part of the collaboration effort, the NWS and NASA will develop an implementation and evaluation plan to streamline the integration of the latest technologies and techniques into the operational forecasting environment. The desire of WFO HUN, NASA, and UAH is to provide a model for future collaborative activities between research and operational communities across the country.

Logical design of a decision support system to forecast technology, prices and costs for the national communications system

NASA Astrophysics Data System (ADS)

Williams, K. A.; Partridge, E. C., III

1984-09-01

Originally envisioned as a means to integrate the many systems found throughout the government, the general mission of the NCS continues to be to ensure the survivability of communications during and subsequent to any national emergency. In order to accomplish this mission the NCS is an arrangement of heterogeneous telecommunications systems which are provided by their sponsor Federal agencies. The physical components of Federal telecommunications systems and networks include telephone and digital data switching facilities and primary common user communications centers; Special purpose local delivery message switching and exchange facilities; Government owned or leased radio systems; Technical control facilities which are under exclusive control of a government agency. This thesis describes the logical design of a proposed decision support system for use by the National Communications System in forecasting technology, prices, and costs. It is general in nature and only includes those forecasting models which are suitable for computer implementation. Because it is a logical design it can be coded and applied in many different hardware and/or software configurations.

Space Weather Forecasting: An Enigma

NASA Astrophysics Data System (ADS)

Sojka, J. J.

2012-12-01

The space age began in earnest on October 4, 1957 with the launch of Sputnik 1 and was fuelled for over a decade by very strong national societal concerns. Prior to this single event the adverse effects of space weather had been registered on telegraph lines as well as interference on early WWII radar systems, while for countless eons the beauty of space weather as mid-latitude auroral displays were much appreciated. These prior space weather impacts were in themselves only a low-level science puzzle pursued by a few dedicated researchers. The technology boost and innovation that the post Sputnik era generated has almost single handedly defined our present day societal technology infrastructure. During the decade following Neil's walk on the moon on July 21, 1969 an international thrust to understand the science of space, and its weather, was in progress. However, the search for scientific understand was parsed into independent "stove pipe" categories: The ionosphere-aeronomy, the magnetosphere, the heliosphere-sun. The present day scientific infrastructure of funding agencies, learned societies, and international organizations are still hampered by these 1960's logical divisions which today are outdated in the pursuit of understanding space weather. As this era of intensive and well funded scientific research progressed so did societies innovative uses for space technologies and space "spin-offs". Well over a decade ago leaders in technology, science, and the military realized that there was indeed an adverse side to space weather that with each passing year became more severe. In 1994 several U.S. agencies established the National Space Weather Program (NSWP) to focus scientific attention on the system wide issue of the adverse effects of space weather on society and its technologies. Indeed for the past two decades a significant fraction of the scientific community has actively engaged in understanding space weather and hence crossing the "stove-pipe" disciplines. The perceived progress in space weather understanding differs significantly depending upon which community (scientific, technology, forecaster, society) is addressing the question. Even more divergent are these thoughts when the question is how valuable is the scientific capability of forecasting space weather. This talk will discuss present day as well as future potential for forecasting space weather for a few selected examples. The author will attempt to straddle the divergent community opinions.

Feasibility of Virtual Machine and Cloud Computing Technologies for High Performance Computing

DTIC Science & Technology

2014-05-01

Hat Enterprise Linux SaaS software as a service VM virtual machine vNUMA virtual non-uniform memory access WRF weather research and forecasting...previously mentioned in Chapter I Section B1 of this paper, which is used to run the weather research and forecasting ( WRF ) model in their experiments...against a VMware virtualization solution of WRF . The experiment consisted of running WRF in a standard configuration between the D-VTM and VMware while

Job Forecasting. Hearings before the Subcommittee on Investigations and Oversight of the Committee on Science and Technology, U.S. House of Representatives, Ninety-Eighth Congress, First Session (April 6-7, 1983).

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. House Committee on Science and Technology.

This is a report of congressional hearings that focus on an examination of job forecasting methods to learn how accurately future jobs can be predicted and the kinds of skills and training American workers will need to fill them. Testimony includes statements and prepared statements of the majority leader of the House of Representatives and…

Forecasting waste compositions: A case study on plastic waste of electronic display housings.

PubMed

Peeters, Jef R; Vanegas, Paul; Kellens, Karel; Wang, Feng; Huisman, Jaco; Dewulf, Wim; Duflou, Joost R

2015-12-01

Because of the rapid succession of technological developments, the architecture and material composition of many products used in daily life have drastically changed over the last decades. As a result, well-adjusted recycling technologies need to be developed and installed to cope with these evolutions. This is essential to guarantee continued access to materials and to reduce the ecological impact of our material consumption. However, limited information is currently available on the material composition of arising waste streams and even less on how these waste streams will evolve. Therefore, this paper presents a methodology to forecast trends in the material composition of waste streams. To demonstrate the applicability and value of the proposed methodology, it is applied to forecast the evolution of plastic housing waste from flat panel display (FPD) TVs, FPD monitors, cathode ray tube (CRT) TVs and CRT monitors. The results of the presented forecasts indicate that a wide variety of plastic types and additives, such as flame retardants, are found in housings of similar products. The presented case study demonstrates that the proposed methodology allows the identification of trends in the evolution of the material composition of waste streams. In addition, it is demonstrated that the recycling sector will need to adapt its processes to deal with the increasing complexity of plastics of end-of-life electronic displays while respecting relevant directives. Copyright © 2015 Elsevier Ltd. All rights reserved.

Forecast Informed Reservoir Operations: Bringing Science and Decision-Makers Together to Explore Use of Hydrometeorological Forecasts to Support Future Reservoir Operations

NASA Astrophysics Data System (ADS)

Ralph, F. M.; Jasperse, J.

2017-12-01

Forecast Informed Reservoir Operations (FIRO) is a proposed strategy that is exploring inorporation of improved hydrometeorological forecasts of land-falling atmospheric rivers on the U.S. West Coast into reservoir operations. The first testbed for this strategy is Lake Mendocino, which is located in the East Fork of the 1485 mi2 Russian River Watershed in northern California. This project is guided by the Lake Mendocino FIRO Steering Committee (SC). The SC is an ad hoc committee that consists of water managers and scientists from several federal, state, and local agencies, and universities who have teamed to evaluate whether current or improved technology and scientific understanding can be utilized to improve water supply reliability, enhance flood mitigation and support recovery of listed salmon for the Russian River of northern California. In 2015, the SC created a detailed work plan, which included a Preliminary Viability Assessment, which has now been completed. The SC developed a vision that operational efficiency would be improved by using forecasts to inform decisions about releasing or storing water. FIRO would use available reservoir storage in an efficient manner by (1) better forecasting inflow (or lack of inflow) with enhanced technology, and (2) adapting operation in real time to meet the need for storage, rather than making storage available just in case it is needed. The envisioned FIRO strategy has the potential to simultaneously improve water supply reliability, flood protection, and ecosystem outcomes through a more efficient use of existing infrastructure while requiring minimal capital improvements in the physical structure of the dam. This presentation will provide an overview of the creation of the FIRO SC and how it operates, and describes the lessons learned through this partnership. Results in the FIRO Preliminary Viability Assessment will be summarized and next steps described.

Benefits of seasonal forecasts of crop yields

NASA Astrophysics Data System (ADS)

Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

2017-12-01

Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

Forecasting Higher Education's Future.

ERIC Educational Resources Information Center

Boyken, Don; Buck, Tina S.; Kollie, Ellen; Przyborowski, Danielle; Rondinelli, Joseph A.; Hunter, Jeff; Hanna, Jeff

2003-01-01

Offers predictions on trends in higher education to accommodate changing needs, lower budgets, and increased enrollment. They involve campus construction, security, administration, technology, interior design, athletics, and transportation. (EV)

Challenges and potential solutions for European coastal ocean modelling

NASA Astrophysics Data System (ADS)

She, Jun; Stanev, Emil

2017-04-01

Coastal operational oceanography is a science and technological platform to integrate and transform the outcomes in marine monitoring, new knowledge generation and innovative technologies into operational information products and services in the coastal ocean. It has been identified as one of the four research priorities by EuroGOOS (She et al. 2016). Coastal modelling plays a central role in such an integration and transformation. A next generation coastal ocean forecasting system should have following features: i) being able to fully exploit benefits from future observations, ii) generate meaningful products in finer scales e.g., sub-mesoscale and in estuary-coast-sea continuum, iii) efficient parallel computing and model grid structure, iv) provide high quality forecasts as forcing to NWP and coastal climate models, v) resolving correctly inter-basin and inter-sub-basin water exchange, vi) resolving synoptic variability and predictability in marine ecosystems, e.g., for algae bloom, vi) being able to address critical and relevant issues in coastal applications, e.g., marine spatial planning, maritime safety, marine pollution protection, disaster prevention, offshore wind energy, climate change adaptation and mitigation, ICZM (integrated coastal zone management), the WFD (Water Framework Directive), and the MSFD (Marine Strategy Framework Directive), especially on habitat, eutrophication, and hydrographic condition descriptors. This presentation will address above challenges, identify limits of current models and propose correspondent research needed. The proposed roadmap will address an integrated monitoring-modelling approach and developing Unified European Coastal Ocean Models. In the coming years, a few new developments in European Sea observations can expected, e.g., more near real time delivering on profile observations made by research vessels, more shallow water Argo floats and bio-Argo floats deployed, much more high resolution sea level data from SWOT and on-going altimetry missions, contributing to resolving (sub-)mesoscale eddies, more currents measurements from ADCPs and HF radars, geostationary data for suspended sediment and diurnal observations from satellite SST products. These developments will make it possible to generate new knowledge and build up new capacities for modelling and forecasting systems, e.g., improved currents forecast, improved water skin temperature and surface winds forecast, improved modelling and forecast of (sub) mesoscale activities and drift forecast, new forecast capabilities on SPM (Suspended Particle Matter) and algae bloom. There will be much more in-situ and satellite data available for assimilation. The assimilation of sea level, chl-a, ferrybox and profile observations will greatly improves the ocean-ice-ecosystem forecast quality.

The NASA Short-term Prediction and Research Transition (SPoRT) Center: A Research to Operations Test Bed

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.

2005-01-01

Over the last three years, NASA/MSFC scientists have embarked on an effort to transition unique NASA EOS data/products and research technology to selected NWSEOs in the southeast U.S. This activity, called the Short-term Prediction and - Research Transition (SPoRT) program, supports the NASA Science Mission Directorate and its Earth-Sun System Mission to develop a scientific understanding of the Earth System and its response to natural or human-induced changes that will enable improved prediction capability for climate, weather, and natural hazards. The overarching question related to weather prediction is "How well can weather forecasting duration and reliability be improved by new space-based observations, data assimilation, and modeling?" The transition activity has included the real-time delivery of MODIS data and products to several NWS Forecast Offices. Local NWS FOs have used the MODIS data to complement the coarse resolution GOES data for a number of applications. Specialized products have also been developed and made available to local and remote offices for their weather applications. Data from &e Lightning Mapping Array (LMA) network has been used in severe storm forecasts at several offices in the region. At the regional scale and forecast horizons from 0-1 day, the next generation of high-resolution mesoscale forecast and data assimilation models have been used to provide local offices with unique weather forecasts not otherwise available. The continued use of near red-time infusion of NASA science products into high-resolution mesoscale forecast and decision-making models can be expected to improve the model initialization as well as short-term forecasts. A current focus of SPoRT is to expand collaborations to include contributions from the assimilation of AMSR-E data in the ADASIARPS forecast system (OU), inclusion of MODIS SSTs and AIRS thermodynamic profiles in the WRF, and to extend the distribution of real-time MODIS and AMSR-E data and products to the Florida coastal WFOs. A SPoRT Test bed, together with input from other interagency and university partners, will provide a means and a process to effectively transition ESE observations and technology to NWS operations and decision makers at both the globdnational and regional scales. The transition of emerging experimental products into operations through the SPoRT infrastructure will allow NASA to foster and accelerate the progress of this Science Mission Directorate research strategy over the coming years.

[Sequencing technology in gene diagnosis and its application].

PubMed

Yibin, Guo

2014-11-01

The study of gene mutation is one of the hot topics in the field of life science nowadays, and the related detection methods and diagnostic technology have been developed rapidly. Sequencing technology plays an indispensable role in the definite diagnosis and classification of genetic diseases. In this review, we summarize the research progress in sequencing technology, evaluate the advantages and disadvantages of 1(st) ~3(rd) generation of sequencing technology, and describe its application in gene diagnosis. Also we made forecasts and prospects on its development trend.

Operational Impact of Data Collected from the Global Hawk Unmanned Aircraft During SHOUT

NASA Astrophysics Data System (ADS)

Wick, G. A.; Dunion, J. P.; Sippel, J.; Cucurull, L.; Aksoy, A.; Kren, A.; Christophersen, H.; Black, P.

2017-12-01

The primary scientific goal of the Sensing Hazards with Operational Unmanned Technology (SHOUT) Project was to determine the potential utility of observations from high-altitude, long-endurance unmanned aircraft systems such as the Global Hawk (GH) aircraft to improve operational forecasts of high-impact weather events or mitigate potential degradation of forecasts in the event of a future gap in satellite coverage. Hurricanes and tropical cyclones are among the most potentially destructive high-impact weather events and pose a major forecasting challenge to NOAA. Major winter storms over the Pacific Ocean, including atmospheric river events, which make landfall and bring strong winds and extreme precipitation to the West Coast and Alaska are also important to forecast accurately because of their societal impact in those parts of the country. In response, the SHOUT project supported three field campaigns with the GH aircraft and dedicated data impact studies exploring the potential for the real-time data from the aircraft to improve the forecasting of both tropical cyclones and landfalling Pacific storms. Dropsonde observations from the GH aircraft were assimilated into the operational Hurricane Weather Research and Forecasting (HWRF) and Global Forecast System (GFS) models. The results from several diverse but complementary studies consistently demonstrated significant positive forecast benefits spanning the regional and global models. Forecast skill improvements within HWRF reached up to about 9% for track and 14% for intensity. Within GFS, track skill improvements for multi-storm averages exceeded 10% and improvements for individual storms reached over 20% depending on forecast lead time. Forecasted precipitation was also improved. Impacts for Pacific winter storms were smaller but still positive. The results are highly encouraging and support the potential for operational utilization of data from a platform like the GH. This presentation summarizes the observations collected and highlights the multiple impact studies completed.

Exploring the calibration of a wind forecast ensemble for energy applications

NASA Astrophysics Data System (ADS)

Heppelmann, Tobias; Ben Bouallegue, Zied; Theis, Susanne

2015-04-01

In the German research project EWeLiNE, Deutscher Wetterdienst (DWD) and Fraunhofer Institute for Wind Energy and Energy System Technology (IWES) are collaborating with three German Transmission System Operators (TSO) in order to provide the TSOs with improved probabilistic power forecasts. Probabilistic power forecasts are derived from probabilistic weather forecasts, themselves derived from ensemble prediction systems (EPS). Since the considered raw ensemble wind forecasts suffer from underdispersiveness and bias, calibration methods are developed for the correction of the model bias and the ensemble spread bias. The overall aim is to improve the ensemble forecasts such that the uncertainty of the possible weather deployment is depicted by the ensemble spread from the first forecast hours. Additionally, the ensemble members after calibration should remain physically consistent scenarios. We focus on probabilistic hourly wind forecasts with horizon of 21 h delivered by the convection permitting high-resolution ensemble system COSMO-DE-EPS which has become operational in 2012 at DWD. The ensemble consists of 20 ensemble members driven by four different global models. The model area includes whole Germany and parts of Central Europe with a horizontal resolution of 2.8 km and a vertical resolution of 50 model levels. For verification we use wind mast measurements around 100 m height that corresponds to the hub height of wind energy plants that belong to wind farms within the model area. Calibration of the ensemble forecasts can be performed by different statistical methods applied to the raw ensemble output. Here, we explore local bivariate Ensemble Model Output Statistics at individual sites and quantile regression with different predictors. Applying different methods, we already show an improvement of ensemble wind forecasts from COSMO-DE-EPS for energy applications. In addition, an ensemble copula coupling approach transfers the time-dependencies of the raw ensemble to the calibrated ensemble. The calibrated wind forecasts are evaluated first with univariate probabilistic scores and additionally with diagnostics of wind ramps in order to assess the time-consistency of the calibrated ensemble members.

Waste Information Management System: One Year After Web Deployment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shoffner, P.A.; Geisler, T.J.; Upadhyay, H.

2008-07-01

The implementation of the Department of Energy (DOE) mandated accelerated cleanup program created significant potential technical impediments. The schedule compression required close coordination and a comprehensive review and prioritization of the barriers that impeded treatment and disposition of the waste streams at each site. Many issues related to site waste treatment and disposal were potential critical path issues under the accelerated schedules. In order to facilitate accelerated cleanup initiatives, waste managers at DOE field sites and at DOE Headquarters in Washington, D.C., needed timely waste forecast information regarding the volumes and types of waste that would be generated by DOEmore » sites over the next 30 years. Each local DOE site has historically collected, organized, and displayed site waste forecast information in separate and unique systems. However, waste information from all sites needed a common application to allow interested parties to understand and view the complete complex-wide picture. A common application allows identification of total waste volumes, material classes, disposition sites, choke points, and technological or regulatory barriers to treatment and disposal. The Applied Research Center (ARC) at Florida International University (FIU) in Miami, Florida, has completed the deployment of this fully operational, web-based forecast system. New functional modules and annual waste forecast data updates have been added to ensure the long-term viability and value of this system. In conclusion: WIMS continues to successfully accomplish the goals and objectives set forth by DOE for this project. WIMS has replaced the historic process of each DOE site gathering, organizing, and reporting their waste forecast information utilizing different database and display technologies. In addition, WIMS meets DOE's objective to have the complex-wide waste forecast information available to all stakeholders and the public in one easy-to-navigate system. The enhancements to WIMS made over the year since its web deployment include the addition of new DOE sites, an updated data set, and the ability to easily print the forecast data tables, the disposition maps, and the GIS maps. Future enhancements will include a high-level waste summary, a display of waste forecast by mode of transportation, and a user help module. The waste summary display module will provide a high-level summary view of the waste forecast data based on the selection of sites, facilities, material types, and forecast years. The waste summary report module will allow users to build custom filtered reports in a variety of formats, such as MS Excel, MS Word, and PDF. The user help module will provide a step-by-step explanation of various modules, using screen shots and general tutorials. The help module will also provide instructions for printing and margin/layout settings to assist users in using their local printers to print maps and reports. (authors)« less

Extravehicular Activity (EVA) Technology Development Status and Forecast

NASA Technical Reports Server (NTRS)

Chullen, Cinda; Westheimer, David T.

2010-01-01

Beginning in Fiscal Year (FY) 2011, Extravehicular activity (EVA) technology development became a technology foundational domain under a new program Enabling Technology Development and Demonstration. The goal of the EVA technology effort is to further develop technologies that will be used to demonstrate a robust EVA system that has application for a variety of future missions including microgravity and surface EVA. Overall the objectives will be reduce system mass, reduce consumables and maintenance, increase EVA hardware robustness and life, increase crew member efficiency and autonomy, and enable rapid vehicle egress and ingress. Over the past several years, NASA realized a tremendous increase in EVA system development as part of the Exploration Technology Development Program and the Constellation Program. The evident demand for efficient and reliable EVA technologies, particularly regenerable technologies was apparent under these former programs and will continue to be needed as future mission opportunities arise. The technological need for EVA in space has been realized over the last several decades by the Gemini, Apollo, Skylab, Space Shuttle, and the International Space Station (ISS) programs. EVAs were critical to the success of these programs. Now with the ISS extension to 2028 in conjunction with a current forecasted need of at least eight EVAs per year, the EVA technology life and limited availability of the EMUs will become a critical issue eventually. The current Extravehicular Mobility Unit (EMU) has vastly served EVA demands by performing critical operations to assemble the ISS and provide repairs of satellites such as the Hubble Space Telescope. However, as the life of ISS and the vision for future mission opportunities are realized, a new EVA systems capability could be an option for the future mission applications building off of the technology development over the last several years. Besides ISS, potential mission applications include EVAs for missions to Near Earth Objects (NEO), Phobos, or future surface missions. Surface missions could include either exploration of the Moon or Mars. Providing an EVA capability for these types of missions enables in-space construction of complex vehicles or satellites, hands on exploration of new parts of our solar system, and engages the public through the inspiration of knowing that humans are exploring places that they have never been before. This paper offers insight into what is currently being developed and what the potential opportunities are in the forecast

Development of an Adaptable Display and Diagnostic System for the Evaluation of Tropical Cyclone Forecasts

NASA Astrophysics Data System (ADS)

Kucera, P. A.; Burek, T.; Halley-Gotway, J.

2015-12-01

NCAR's Joint Numerical Testbed Program (JNTP) focuses on the evaluation of experimental forecasts of tropical cyclones (TCs) with the goal of developing new research tools and diagnostic evaluation methods that can be transitioned to operations. Recent activities include the development of new TC forecast verification methods and the development of an adaptable TC display and diagnostic system. The next generation display and diagnostic system is being developed to support evaluation needs of the U.S. National Hurricane Center (NHC) and broader TC research community. The new hurricane display and diagnostic capabilities allow forecasters and research scientists to more deeply examine the performance of operational and experimental models. The system is built upon modern and flexible technology that includes OpenLayers Mapping tools that are platform independent. The forecast track and intensity along with associated observed track information are stored in an efficient MySQL database. The system provides easy-to-use interactive display system, and provides diagnostic tools to examine forecast track stratified by intensity. Consensus forecasts can be computed and displayed interactively. The system is designed to display information for both real-time and for historical TC cyclones. The display configurations are easily adaptable to meet the needs of the end-user preferences. Ongoing enhancements include improving capabilities for stratification and evaluation of historical best tracks, development and implementation of additional methods to stratify and compute consensus hurricane track and intensity forecasts, and improved graphical display tools. The display is also being enhanced to incorporate gridded forecast, satellite, and sea surface temperature fields. The presentation will provide an overview of the display and diagnostic system development and demonstration of the current capabilities.

World market: A survey of opportunities for advanced coal-fired systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holt, N.A.H.

1995-06-01

Although there is a wide range of forecasts for the future of World energy demand and consumption over the next 25 years, all forecasts show marked increases being required for all forms of fossil fuels even when optimistic projections are made for the future adoption of Nuclear and Renewable energy. It is also generally expected that coal usage will in this period experience its greatest growth (a doubling) in the Asia-Pacific region dominated demographically by China and India. In this paper, energy projections and the extent and nature of the coal reserves available worldwide are examined. While most coal technologiesmore » can handle a variety of feedstocks, there are often economic factors that will determine the preferred selection. The matching of technology to coal type and other factors is examined with particular reference to the Asia Pacific region. Oil usage is similarly forecast to experience a comparable growth in this region. Over 70% of the World`s oil reserves are heavy oils and refinery crudes are increasing in gravity and sulfur content. The clean coal technologies of gasification and fluid bed combustion can also use low value petroleum residuals as feedstocks. There is therefore a nearer term market opportunity to incorporate such technologies into cogeneration and coproduction schemes adjacent to refineries resulting in extremely efficient use of these resources.« less

Battery Energy Storage State-of-Charge Forecasting: Models, Optimization, and Accuracy

DOE PAGES

Rosewater, David; Ferreira, Summer; Schoenwald, David; ...

2018-01-25

Battery energy storage systems (BESS) are a critical technology for integrating high penetration renewable power on an intelligent electrical grid. As limited energy restricts the steady-state operational state-of-charge (SoC) of storage systems, SoC forecasting models are used to determine feasible charge and discharge schedules that supply grid services. Smart grid controllers use SoC forecasts to optimize BESS schedules to make grid operation more efficient and resilient. This study presents three advances in BESS state-of-charge forecasting. First, two forecasting models are reformulated to be conducive to parameter optimization. Second, a new method for selecting optimal parameter values based on operational datamore » is presented. Last, a new framework for quantifying model accuracy is developed that enables a comparison between models, systems, and parameter selection methods. The accuracies achieved by both models, on two example battery systems, with each method of parameter selection are then compared in detail. The results of this analysis suggest variation in the suitability of these models for different battery types and applications. Finally, the proposed model formulations, optimization methods, and accuracy assessment framework can be used to improve the accuracy of SoC forecasts enabling better control over BESS charge/discharge schedules.« less

Demand for satellite-provided domestic communications services up to the year 2000

NASA Technical Reports Server (NTRS)

Stevenson, S.; Poley, W.; Lekan, J.; Salzman, J. A.

1984-01-01

Three fixed service telecommunications demand assessment studies were completed for NASA by The Western Union Telegraph Company and the U.S. Telephone and Telegraph Corporation. They provided forecasts of the total U.S. domestic demand, from 1980 to the year 2000, for voice, data, and video services. That portion that is technically and economically suitable for transmission by satellite systems, both large trunking systems and customer premises services (CPS) systems was also estimated. In order to provide a single set of forecasts a NASA synthesis of the above studies was conducted. The services, associated forecast techniques, and data bases employed by both contractors were examined, those elements of each judged to be the most appropriate were selected, and new forecasts were made. The demand for voice, data, and video services was first forecast in fundamental units of call-seconds, bits/year, and channels, respectively. Transmission technology characteristics and capabilities were then forecast, and the fundamental demand converted to an equivalent transmission capacity. The potential demand for satellite-provided services was found to grow by a factor of 6, from 400 to 2400 equivalent 36 MHz satellite transponders over the 20-year period. About 80 percent of this was found to be more appropriate for trunking systems and 20 percent CPS.

Battery Energy Storage State-of-Charge Forecasting: Models, Optimization, and Accuracy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosewater, David; Ferreira, Summer; Schoenwald, David

Battery energy storage systems (BESS) are a critical technology for integrating high penetration renewable power on an intelligent electrical grid. As limited energy restricts the steady-state operational state-of-charge (SoC) of storage systems, SoC forecasting models are used to determine feasible charge and discharge schedules that supply grid services. Smart grid controllers use SoC forecasts to optimize BESS schedules to make grid operation more efficient and resilient. This study presents three advances in BESS state-of-charge forecasting. First, two forecasting models are reformulated to be conducive to parameter optimization. Second, a new method for selecting optimal parameter values based on operational datamore » is presented. Last, a new framework for quantifying model accuracy is developed that enables a comparison between models, systems, and parameter selection methods. The accuracies achieved by both models, on two example battery systems, with each method of parameter selection are then compared in detail. The results of this analysis suggest variation in the suitability of these models for different battery types and applications. Finally, the proposed model formulations, optimization methods, and accuracy assessment framework can be used to improve the accuracy of SoC forecasts enabling better control over BESS charge/discharge schedules.« less

Demand for satellite-provided domestic communications services up to the year 2000

NASA Astrophysics Data System (ADS)

Stevenson, S.; Poley, W.; Lekan, J.; Salzman, J. A.

1984-11-01

Three fixed service telecommunications demand assessment studies were completed for NASA by The Western Union Telegraph Company and the U.S. Telephone and Telegraph Corporation. They provided forecasts of the total U.S. domestic demand, from 1980 to the year 2000, for voice, data, and video services. That portion that is technically and economically suitable for transmission by satellite systems, both large trunking systems and customer premises services (CPS) systems was also estimated. In order to provide a single set of forecasts a NASA synthesis of the above studies was conducted. The services, associated forecast techniques, and data bases employed by both contractors were examined, those elements of each judged to be the most appropriate were selected, and new forecasts were made. The demand for voice, data, and video services was first forecast in fundamental units of call-seconds, bits/year, and channels, respectively. Transmission technology characteristics and capabilities were then forecast, and the fundamental demand converted to an equivalent transmission capacity. The potential demand for satellite-provided services was found to grow by a factor of 6, from 400 to 2400 equivalent 36 MHz satellite transponders over the 20-year period. About 80 percent of this was found to be more appropriate for trunking systems and 20 percent CPS.

Using Enabling Technologies to Facilitate the Comparison of Satellite Observations with the Model Forecasts for Hurricane Study

NASA Astrophysics Data System (ADS)

Li, P.; Knosp, B.; Hristova-Veleva, S. M.; Niamsuwan, N.; Johnson, M. P.; Shen, T. P. J.; Tanelli, S.; Turk, J.; Vu, Q. A.

2014-12-01

Due to their complexity and volume, the satellite data are underutilized in today's hurricane research and operations. To better utilize these data, we developed the JPL Tropical Cyclone Information System (TCIS) - an Interactive Data Portal providing fusion between Near-Real-Time satellite observations and model forecasts to facilitate model evaluation and improvement. We have collected satellite observations and model forecasts in the Atlantic Basin and the East Pacific for the hurricane seasons since 2010 and supported the NASA Airborne Campaigns for Hurricane Study such as the Genesis and Rapid Intensification Processes (GRIP) in 2010 and the Hurricane and Severe Storm Sentinel (HS3) from 2012 to 2014. To enable the direct inter-comparisons of the satellite observations and the model forecasts, the TCIS was integrated with the NASA Earth Observing System Simulator Suite (NEOS3) to produce synthetic observations (e.g. simulated passive microwave brightness temperatures) from a number of operational hurricane forecast models (HWRF and GFS). An automated process was developed to trigger NEOS3 simulations via web services given the location and time of satellite observations, monitor the progress of the NEOS3 simulations, display the synthetic observation and ingest them into the TCIS database when they are done. In addition, three analysis tools, the joint PDF analysis of the brightness temperatures, ARCHER for finding the storm-center and the storm organization and the Wave Number Analysis tool for storm asymmetry and morphology analysis were integrated into TCIS to provide statistical and structural analysis on both observed and synthetic data. Interactive tools were built in the TCIS visualization system to allow the spatial and temporal selections of the datasets, the invocation of the tools with user specified parameters, and the display and the delivery of the results. In this presentation, we will describe the key enabling technologies behind the design of the TCIS interactive data portal and analysis tools, including the spatial database technology for the representation and query of the level 2 satellite data, the automatic process flow using web services, the interactive user interface using the Google Earth API, and a common and expandable Python wrapper to invoke the analysis tools.

Rapid weather information dissemination in Florida

NASA Technical Reports Server (NTRS)

Martsolf, J. D.; Heinemann, P. H.; Gerber, J. F.; Crosby, F. L.; Smith, D. L.

1984-01-01

The development of the Florida Agricultural Services and Technology (FAST) plan to provide ports for users to call for weather information is described. FAST is based on the Satellite Frost Forecast System, which makes a broad base of weather data available to its users. The methods used for acquisition and dissemination of data from various networks under the FAST plan are examined. The system provides color coded IR or thermal maps, precipitation maps, and textural forecast information. A diagram of the system is provided.

Waste to Watts and Water: Enabling Self-Contained Facilities Using Microbial Fuel Cells

DTIC Science & Technology

2009-03-01

will require in future facilities is the ability to operate apart from the infrastructure net- work and line of communications (LOC) in a clean and ef...in future technologies, observes that “forecasters are im- prisoned by their times.”33 Humans tend to look at today’s crisis and project it into the...2030. In 2007 the United States Department of Energy (DOE) forecast international power demand to double by 2030.34 Today’s energy crisis is well

Using Flow Charts to Visualize the Decision-Making Process in Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Aung, M. T. Y.; Myat, T.; Zheng, Y.; Mays, M. L.; Ngwira, C.; Damas, M. C.

2016-12-01

Our society today relies heavily on technological systems such as satellites, navigation systems, power grids and aviation. These systems are very sensitive to space weather disturbances. When Earth-directed space weather driven by the Sun arrives at the Earth, it causes changes to the Earth's radiation environment and the magnetosphere. Strong disturbances in the magnetosphere of the Earth are responsible for geomagnetic storms that can last from hours to days depending on strength of storms. Geomagnetic storms can severely impact critical infrastructure on Earth, such as the electric power grid, and Solar Energetic Particles that can endanger life in outer space. How can we lessen these adverse effects? They can be lessened through the early warning signals sent by space weather forecasters before CME or high-speed stream arrives. A space weather forecaster's duty is to send predicted notifications to high-tech industries and NASA missions so that they could take extra measures for protection. NASA space weather forecasters make prediction decisions by following certain steps and processes from the time an event occurs at the sun all the way to the impact locations. However, there has never been a tool that helps these forecasters visualize the decision process until now. A flow chart is created to help forecasters visualize the decision process. This flow chart provides basic knowledge of space weather and can be used to train future space weather forecasters. It also helps to cut down the training period and increase consistency in forecasting. The flow chart is also a great reference for people who are already familiar with space weather.

Analysis of technology requirements and potential demand for general aviation avionics systems in the 1980's. [technology assessment and technological forecasting of the aircraft industry

NASA Technical Reports Server (NTRS)

Cohn, D. M.; Kayser, J. H.; Senko, G. M.; Glenn, D. R.

1974-01-01

The trend for the increasing need for aircraft-in-general as a major source of transportation in the United States is presented (military and commercial aircraft are excluded). Social, political, and economic factors that affect the aircraft industry are considered, and cost estimates are given. Aircraft equipment and navigation systems are discussed.

Extravehicular Activity Technology Development Status and Forecast

NASA Technical Reports Server (NTRS)

Chullen, Cinda; Westheimer, David T.

2011-01-01

The goal of NASA s current EVA technology effort is to further develop technologies that will be used to demonstrate a robust EVA system that has application for a variety of future missions including microgravity and surface EVA. Overall the objectives will be to reduce system mass, reduce consumables and maintenance, increase EVA hardware robustness and life, increase crew member efficiency and autonomy, and enable rapid vehicle egress and ingress. Over the past several years, NASA realized a tremendous increase in EVA system development as part of the Exploration Technology Development Program and the Constellation Program. The evident demand for efficient and reliable EVA technologies, particularly regenerable technologies was apparent under these former programs and will continue to be needed as future mission opportunities arise. The technological need for EVA in space has been realized over the last several decades by the Gemini, Apollo, Skylab, Space Shuttle, and the International Space Station (ISS) programs. EVAs were critical to the success of these programs. Now with the ISS extension to 2028 in conjunction with a current forecasted need of at least eight EVAs per year, the EVA hardware life and limited availability of the Extravehicular Mobility Units (EMUs) will eventually become a critical issue. The current EMU has successfully served EVA demands by performing critical operations to assemble the ISS and provide repairs of satellites such as the Hubble Space Telescope. However, as the life of ISS and the vision for future mission opportunities are realized, a new EVA systems capability will be needed and the current architectures and technologies under development offer significant improvements over the current flight systems. In addition to ISS, potential mission applications include EVAs for missions to Near Earth Objects (NEO), Phobos, or future surface missions. Surface missions could include either exploration of the Moon or Mars. Providing an EVA capability for these types of missions enables in-space construction of complex vehicles or satellites, hands on exploration of new parts of our solar system, and engages the public through the inspiration of knowing that humans are exploring places that they have never been before. This paper offers insight into what is currently being developed and what the potential opportunities are in the forecast.

The GOES-R Geostationary Lightning Mapper (GLM) and the Global Observing System for Total Lightning

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, R. J.; Koshak, W.; Buechler, D.; Carey, L.; Chronis, T.; Mach, D.; Bateman, M.; Peterson, H.; McCaul, E. W., Jr.;

Aging in America in the Twenty-first Century: Demographic Forecasts from the MacArthur Foundation Research Network on an Aging Society

PubMed Central

Olshansky, S Jay; Goldman, Dana P; Zheng, Yuhui; Rowe, John W

2009-01-01

Context: The aging of the baby boom generation, the extension of life, and progressive increases in disability-free life expectancy have generated a dramatic demographic transition in the United States. Official government forecasts may, however, have inadvertently underestimated life expectancy, which would have major policy implications, since small differences in forecasts of life expectancy produce very large differences in the number of people surviving to an older age. This article presents a new set of population and life expectancy forecasts for the United States, focusing on transitions that will take place by midcentury. Methods: Forecasts were made with a cohort-components methodology, based on the premise that the risk of death will be influenced in the coming decades by accelerated advances in biomedical technology that either delay the onset and age progression of major fatal diseases or that slow the aging process itself. Findings: Results indicate that the current forecasts of the U.S. Social Security Administration and U.S. Census Bureau may underestimate the rise in life expectancy at birth for men and women combined, by 2050, from 3.1 to 7.9 years. Conclusions: The cumulative outlays for Medicare and Social Security could be higher by $3.2 to $8.3 trillion relative to current government forecasts. This article discusses the implications of these results regarding the benefits and costs of an aging society and the prospect that health disparities could attenuate some of these changes. PMID:20021588

An economic model of the manufacturers' aircraft production and airline earnings potential, volume 3

NASA Technical Reports Server (NTRS)

Kneafsey, J. T.; Hill, R. M.

1978-01-01

A behavioral explanation of the process of technological change in the U. S. aircraft manufacturing and airline industries is presented. The model indicates the principal factors which influence the aircraft (airframe) manufacturers in researching, developing, constructing and promoting new aircraft technology; and the financial requirements which determine the delivery of new aircraft to the domestic trunk airlines. Following specification and calibration of the model, the types and numbers of new aircraft were estimated historically for each airline's fleet. Examples of possible applications of the model to forecasting an individual airline's future fleet also are provided. The functional form of the model is a composite which was derived from several preceding econometric models developed on the foundations of the economics of innovation, acquisition, and technological change and represents an important contribution to the improved understanding of the economic and financial requirements for aircraft selection and production. The model's primary application will be to forecast the future types and numbers of new aircraft required for each domestic airline's fleet.

Flood Forecast Accuracy and Decision Support System Approach: the Venice Case

NASA Astrophysics Data System (ADS)

Canestrelli, A.; Di Donato, M.

2016-02-01

In the recent years numerical models for weather predictions have experienced continuous advances in technology. As a result, all the disciplines making use of weather forecasts have made significant steps forward. In the case of the Safeguard of Venice, a large effort has been put in order to improve the forecast of tidal levels. In this context, the Istituzione Centro Previsioni e Segnalazioni Maree (ICPSM) of the Venice Municipality has developed and tested many different forecast models, both of the statistical and deterministic type, and has shown to produce very accurate forecasts. For Venice, the maximum admissible forecast error should be (ideally) of the order of ten centimeters at 24 hours. The entity of the forecast error clearly affects the decisional process, which mainly consists of alerting the population, activating the movable barriers installed at the three tidal inlets and contacting the port authority. This process becomes more challenging whenever the weather predictions, and therefore the water level forecasts, suddenly change. These new forecasts have to be quickly transformed into operational tasks. Therefore, it is of the utter importance to set up scheduled alerts and emergency plans by means of easy-to-follow procedures. On this direction, Technital has set up a Decision Support System based on expert procedures that minimizes the human mistakes and, as a consequence, reduces the risk of flooding of the historical center. Moreover, the Decision Support System can communicate predefined alerts to all the interested subjects. The System uses the water levels forecasts produced by the ICPSM by taking into account the accuracy at different leading times. The Decision Support System has been successfully tested with 8 years of data, 6 of them in real time. Venice experience shows that the Decision Support System is an essential tool which assesses the risks associated with a particular event, provides clear operational procedures and minimizes the impact of natural floods on human lives, private properties and historical monuments.

A cross impact methodology for the assessment of US telecommunications system with application to fiber optics development: Executive summary

NASA Technical Reports Server (NTRS)

Martino, J. P.; Lenz, R. C., Jr.; Chen, K. L.

1979-01-01

A cross impact model of the U.S. telecommunications system was developed. For this model, it was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impacts). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics, throughout the telecommunications system.

Assessment of the Charging Policy in Energy Efficiency of the Enterprise

NASA Astrophysics Data System (ADS)

Shutov, E. A.; E Turukina, T.; Anisimov, T. S.

2017-04-01

The forecasting problem for energy facilities with a power exceeding 670 kW is currently one of the main. In connection with rules of the retail electricity market such customers also pay for actual energy consumption deviations from plan value. In compliance with the hierarchical stages of the electricity market a guaranteeing supplier is to respect the interests of distribution and generation companies that require load leveling. The answer to this question for industrial enterprise is possible only within technological process through implementation of energy-efficient processing chains with the adaptive function and forecasting tool. In such a circumstance the primary objective of a forecasting is reduce the energy consumption costs by taking account of the energy cost correlation for 24 hours for forming of pumping unit work schedule. The pumping unit virtual model with the variable frequency drive is considered. The forecasting tool and the optimizer are integrated into typical control circuit. Economic assessment of the optimization method was estimated.

Modeling and Computing of Stock Index Forecasting Based on Neural Network and Markov Chain

PubMed Central

Dai, Yonghui; Han, Dongmei; Dai, Weihui

2014-01-01

The stock index reflects the fluctuation of the stock market. For a long time, there have been a lot of researches on the forecast of stock index. However, the traditional method is limited to achieving an ideal precision in the dynamic market due to the influences of many factors such as the economic situation, policy changes, and emergency events. Therefore, the approach based on adaptive modeling and conditional probability transfer causes the new attention of researchers. This paper presents a new forecast method by the combination of improved back-propagation (BP) neural network and Markov chain, as well as its modeling and computing technology. This method includes initial forecasting by improved BP neural network, division of Markov state region, computing of the state transition probability matrix, and the prediction adjustment. Results of the empirical study show that this method can achieve high accuracy in the stock index prediction, and it could provide a good reference for the investment in stock market. PMID:24782659

A cross impact methodology for the assessment of US telecommunications system with application to fiber optics development, volume 1

NASA Technical Reports Server (NTRS)

Martino, J. P.; Lenz, R. C., Jr.; Chen, K. L.; Kahut, P.; Sekely, R.; Weiler, J.

1979-01-01

A cross impact model of the U.S. telecommunications system was developed. It was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impact). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics throughout the telecommunications system.

'Emerging technologies for the changing global market' - Prioritization methodology for chemical replacement

NASA Technical Reports Server (NTRS)

Cruit, Wendy; Schutzenhofer, Scott; Goldberg, Ben; Everhart, Kurt

1993-01-01

This project served to define an appropriate methodology for effective prioritization of technology efforts required to develop replacement technologies mandated by imposed and forecast legislation. The methodology used is a semiquantitative approach derived from quality function deployment techniques (QFD Matrix). This methodology aims to weight the full environmental, cost, safety, reliability, and programmatic implications of replacement technology development to allow appropriate identification of viable candidates and programmatic alternatives. The results will be implemented as a guideline for consideration for current NASA propulsion systems.

Emerging technologies for the changing global market

NASA Technical Reports Server (NTRS)

Cruit, Wendy; Schutzenhofer, Scott; Goldberg, Ben; Everhart, Kurt

1993-01-01

This project served to define an appropriate methodology for effective prioritization of technology efforts required to develop replacement technologies mandated by imposed and forecast legislation. The methodology used is a semi-quantative approach derived from quality function deployment techniques (QFD Matrix). This methodology aims to weight the full environmental, cost, safety, reliability, and programmatic implications of replacement technology development to allow appropriate identification of viable candidates and programmatic alternatives. The results will be implemented as a guideline for consideration for current NASA propulsion systems.

Towards smart energy systems: application of kernel machine regression for medium term electricity load forecasting.

PubMed

Alamaniotis, Miltiadis; Bargiotas, Dimitrios; Tsoukalas, Lefteri H

2016-01-01

Integration of energy systems with information technologies has facilitated the realization of smart energy systems that utilize information to optimize system operation. To that end, crucial in optimizing energy system operation is the accurate, ahead-of-time forecasting of load demand. In particular, load forecasting allows planning of system expansion, and decision making for enhancing system safety and reliability. In this paper, the application of two types of kernel machines for medium term load forecasting (MTLF) is presented and their performance is recorded based on a set of historical electricity load demand data. The two kernel machine models and more specifically Gaussian process regression (GPR) and relevance vector regression (RVR) are utilized for making predictions over future load demand. Both models, i.e., GPR and RVR, are equipped with a Gaussian kernel and are tested on daily predictions for a 30-day-ahead horizon taken from the New England Area. Furthermore, their performance is compared to the ARMA(2,2) model with respect to mean average percentage error and squared correlation coefficient. Results demonstrate the superiority of RVR over the other forecasting models in performing MTLF.

Improved Modeling Tools Development for High Penetration Solar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Washom, Byron; Meagher, Kevin

2014-12-11

One of the significant objectives of the High Penetration solar research is to help the DOE understand, anticipate, and minimize grid operation impacts as more solar resources are added to the electric power system. For Task 2.2, an effective, reliable approach to predicting solar energy availability for energy generation forecasts using the University of California, San Diego (UCSD) Sky Imager technology has been demonstrated. Granular cloud and ramp forecasts for the next 5 to 20 minutes over an area of 10 square miles were developed. Sky images taken every 30 seconds are processed to determine cloud locations and cloud motionmore » vectors yielding future cloud shadow locations respective to distributed generation or utility solar power plants in the area. The performance of the method depends on cloud characteristics. On days with more advective cloud conditions, the developed method outperforms persistence forecasts by up to 30% (based on mean absolute error). On days with dynamic conditions, the method performs worse than persistence. Sky Imagers hold promise for ramp forecasting and ramp mitigation in conjunction with inverter controls and energy storage. The pre-commercial Sky Imager solar forecasting algorithm was documented with licensing information and was a Sunshot website highlight.« less

Forecasting Behavior in Smart Homes Based on Sleep and Wake Patterns

PubMed Central

Williams, Jennifer A.; Cook, Diane J.

2017-01-01

Background The goal of this research is to use smart home technology to assist people who are recovering from injuries or coping with disabilities to live independently. Objective We introduce an algorithm to model and forecast wake and sleep behaviors that are exhibited by the participant. Furthermore, we propose that sleep behavior is impacted by and can be modeled from wake behavior, and vice versa. Methods This paper describes the Behavior Forecasting (BF) algorithm. BF consists of 1) defining numeric values that reflect sleep and wake behavior, 2) forecasting wake and sleep values from past behavior, 3) analyzing the effect of wake behavior on sleep and vice versa, and 4) improving prediction performance by using both wake and sleep scores. Results The BF method was evaluated with data collected from 20 smart homes. We found that regardless of the forecasting method utilized, wake behavior and sleep behavior can be modeled with a minimum accuracy of 84%. Additionally, normalizing the wake and sleep scores drastically improves the accuracy to 99%. Conclusions The results show that we can effectively model wake and sleep behaviors in a smart environment. Furthermore, wake behaviors can be predicted from sleep behaviors and vice versa. PMID:27689555

Forecasting behavior in smart homes based on sleep and wake patterns.

PubMed

Williams, Jennifer A; Cook, Diane J

2017-01-01

The goal of this research is to use smart home technology to assist people who are recovering from injuries or coping with disabilities to live independently. We introduce an algorithm to model and forecast wake and sleep behaviors that are exhibited by the participant. Furthermore, we propose that sleep behavior is impacted by and can be modeled from wake behavior, and vice versa. This paper describes the Behavior Forecasting (BF) algorithm. BF consists of 1) defining numeric values that reflect sleep and wake behavior, 2) forecasting wake and sleep values from past behavior, 3) analyzing the effect of wake behavior on sleep and vice versa, and 4) improving prediction performance by using both wake and sleep scores. The BF method was evaluated with data collected from 20 smart homes. We found that regardless of the forecasting method utilized, wake behavior and sleep behavior can be modeled with a minimum accuracy of 84%. Additionally, normalizing the wake and sleep scores drastically improves the accuracy to 99%. The results show that we can effectively model wake and sleep behaviors in a smart environment. Furthermore, wake behaviors can be predicted from sleep behaviors and vice versa.

Unstructured Grid Adaptation: Status, Potential Impacts, and Recommended Investments Toward CFD Vision 2030

NASA Technical Reports Server (NTRS)

Park, Michael A.; Krakos, Joshua A.; Michal, Todd; Loseille, Adrien; Alonso, Juan J.

2016-01-01

Unstructured grid adaptation is a powerful tool to control discretization error for Computational Fluid Dynamics (CFD). It has enabled key increases in the accuracy, automation, and capacity of some fluid simulation applications. Slotnick et al. provides a number of case studies in the CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences to illustrate the current state of CFD capability and capacity. The authors forecast the potential impact of emerging High Performance Computing (HPC) environments forecast in the year 2030 and identify that mesh generation and adaptivity continue to be significant bottlenecks in the CFD work flow. These bottlenecks may persist because very little government investment has been targeted in these areas. To motivate investment, the impacts of improved grid adaptation technologies are identified. The CFD Vision 2030 Study roadmap and anticipated capabilities in complementary disciplines are quoted to provide context for the progress made in grid adaptation in the past fifteen years, current status, and a forecast for the next fifteen years with recommended investments. These investments are specific to mesh adaptation and impact other aspects of the CFD process. Finally, a strategy is identified to diffuse grid adaptation technology into production CFD work flows.

Mixed Single/Double Precision in OpenIFS: A Detailed Study of Energy Savings, Scaling Effects, Architectural Effects, and Compilation Effects

NASA Astrophysics Data System (ADS)

Fagan, Mike; Dueben, Peter; Palem, Krishna; Carver, Glenn; Chantry, Matthew; Palmer, Tim; Schlacter, Jeremy

2017-04-01

It has been shown that a mixed precision approach that judiciously replaces double precision with single precision calculations can speed-up global simulations. In particular, a mixed precision variation of the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) showed virtually the same quality model results as the standard double precision version (Vana et al., Single precision in weather forecasting models: An evaluation with the IFS, Monthly Weather Review, in print). In this study, we perform detailed measurements of savings in computing time and energy using a mixed precision variation of the -OpenIFS- model. The mixed precision variation of OpenIFS is analogous to the IFS variation used in Vana et al. We (1) present results for energy measurements for simulations in single and double precision using Intel's RAPL technology, (2) conduct a -scaling- study to quantify the effects that increasing model resolution has on both energy dissipation and computing cycles, (3) analyze the differences between single core and multicore processing, and (4) compare the effects of different compiler technologies on the mixed precision OpenIFS code. In particular, we compare intel icc/ifort with gnu gcc/gfortran.

Military, Charter, Unreported Domestic Traffic and General Aviation 1976, 1984, 1992, and 2015 Emission Scenarios

NASA Technical Reports Server (NTRS)

Mortlock, Alan; VanAlstyne, Richard

1998-01-01

The report describes development of databases estimating aircraft engine exhaust emissions for the years 1976 and 1984 from global operations of Military, Charter, historic Soviet and Chinese, Unreported Domestic traffic, and General Aviation (GA). These databases were developed under the National Aeronautics and Space Administration's (NASA) Advanced Subsonic Assessment (AST). McDonnell Douglas Corporation's (MDC), now part of the Boeing Company has previously estimated engine exhaust emissions' databases for the baseline year of 1992 and a 2015 forecast year scenario. Since their original creation, (Ward, 1994 and Metwally, 1995) revised technology algorithms have been developed. Additionally, GA databases have been created and all past NIDC emission inventories have been updated to reflect the new technology algorithms. Revised data (Baughcum, 1996 and Baughcum, 1997) for the scheduled inventories have been used in this report to provide a comparison of the total aviation emission forecasts from various components. Global results of two historic years (1976 and 1984), a baseline year (1992) and a forecast year (2015) are presented. Since engine emissions are directly related to fuel usage, an overview of individual aviation annual global fuel use for each inventory component is also given in this report.

Understanding and Applying the Technology Forecast of the 2010 Horizon Report

ERIC Educational Resources Information Center

Becker, Bernd W.

2010-01-01

At the beginning of each year the New Media Consortium releases the "Horizon Report", which aims to identify and describe emerging technologies that will "likely have a large impact on teaching, learning, or creative inquiry on college and university campuses within the next five years" (Johnson, Levine, Smith, & Stone 2010, 3). In this issue of…

Developing a Pre-Engineering Curriculum for 3D Printing Skills for High School Technology Education

ERIC Educational Resources Information Center

Chien, Yu-Hung

2017-01-01

This study developed an integrated-STEM CO[subscript 2] dragster design course using 3D printing technology. After developing a pre-engineering curriculum, we conducted a teaching experiment to assess students' differences in creativity, race forecast accuracy, and learning performance. We compared student performance in both 3D printing and…

Outlook for Biomass Ethanol Production and Demand

EIA Publications

2000-01-01

This paper presents a midterm forecast for biomass ethanol production under three different technology cases for the period 2000 to 2020, based on projections developed from the Energy Information Administration's National Energy Modeling System. An overview of cellulose conversion technology and various feedstock options and a brief history of ethanol usage in the United States are also presented.

The microwave radiometer spacecraft: A design study

NASA Technical Reports Server (NTRS)

Wright, R. L. (Editor)

1981-01-01

A large passive microwave radiometer spacecraft with near all weather capability of monitoring soil moisture for global crop forecasting was designed. The design, emphasizing large space structures technology, characterized the mission hardware at the conceptual level in sufficient detail to identify enabling and pacing technologies. Mission and spacecraft requirements, design and structural concepts, electromagnetic concepts, and control concepts are addressed.

Proceedings. National Seminar on Educating the Engineer of the Future (Bangalore, India, January 7-10, 1979).

ERIC Educational Resources Information Center

Institution of Engineers (India).

This volume of proceedings contains the keynote addresses, theme papers, and reports of the various technical sessions of the National Seminar on Educating the Engineers of the Future. A total of 10 technical sessions were held. Areas addressed included: (1) social and technological scenarios and technological forecasting; (2) technologies…

Power Grid Maintenance Scheduling Intelligence Arrangement Supporting System Based on Power Flow Forecasting

NASA Astrophysics Data System (ADS)

Xie, Chang; Wen, Jing; Liu, Wenying; Wang, Jiaming

With the development of intelligent dispatching, the intelligence level of network control center full-service urgent need to raise. As an important daily work of network control center, the application of maintenance scheduling intelligent arrangement to achieve high-quality and safety operation of power grid is very important. By analyzing the shortages of the traditional maintenance scheduling software, this paper designs a power grid maintenance scheduling intelligence arrangement supporting system based on power flow forecasting, which uses the advanced technologies in maintenance scheduling, such as artificial intelligence, online security checking, intelligent visualization techniques. It implements the online security checking of maintenance scheduling based on power flow forecasting and power flow adjusting based on visualization, in order to make the maintenance scheduling arrangement moreintelligent and visual.

Model documentation report: Residential sector demand module of the national energy modeling system

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This reference document provides a detailed description for energy analysts, other users, and the public. The NEMS Residential Sector Demand Module is currently used for mid-term forecasting purposes and energy policy analysis over the forecast horizon of 1993 through 2020. The model generates forecasts of energy demand for the residential sector by service, fuel, and Census Division. Policy impacts resulting from new technologies,more » market incentives, and regulatory changes can be estimated using the module. 26 refs., 6 figs., 5 tabs.« less

Statistical security for Social Security.

PubMed

Soneji, Samir; King, Gary

2012-08-01

The financial viability of Social Security, the single largest U.S. government program, depends on accurate forecasts of the solvency of its intergenerational trust fund. We begin by detailing information necessary for replicating the Social Security Administration's (SSA's) forecasting procedures, which until now has been unavailable in the public domain. We then offer a way to improve the quality of these procedures via age- and sex-specific mortality forecasts. The most recent SSA mortality forecasts were based on the best available technology at the time, which was a combination of linear extrapolation and qualitative judgments. Unfortunately, linear extrapolation excludes known risk factors and is inconsistent with long-standing demographic patterns, such as the smoothness of age profiles. Modern statistical methods typically outperform even the best qualitative judgments in these contexts. We show how to use such methods, enabling researchers to forecast using far more information, such as the known risk factors of smoking and obesity and known demographic patterns. Including this extra information makes a substantial difference. For example, by improving only mortality forecasting methods, we predict three fewer years of net surplus, $730 billion less in Social Security Trust Funds, and program costs that are 0.66% greater for projected taxable payroll by 2031 compared with SSA projections. More important than specific numerical estimates are the advantages of transparency, replicability, reduction of uncertainty, and what may be the resulting lower vulnerability to the politicization of program forecasts. In addition, by offering with this article software and detailed replication information, we hope to marshal the efforts of the research community to include ever more informative inputs and to continue to reduce uncertainties in Social Security forecasts.

Waste Information Management System-2012 - 12114

DOE Office of Scientific and Technical Information (OSTI.GOV)

Upadhyay, H.; Quintero, W.; Shoffner, P.

2012-07-01

The Waste Information Management System (WIMS) -2012 was updated to support the Department of Energy (DOE) accelerated cleanup program. The schedule compression required close coordination and a comprehensive review and prioritization of the barriers that impeded treatment and disposition of the waste streams at each site. Many issues related to waste treatment and disposal were potential critical path issues under the accelerated schedule. In order to facilitate accelerated cleanup initiatives, waste managers at DOE field sites and at DOE Headquarters in Washington, D.C., needed timely waste forecast and transportation information regarding the volumes and types of radioactive waste that wouldmore » be generated by DOE sites over the next 40 years. Each local DOE site historically collected, organized, and displayed waste forecast information in separate and unique systems. In order for interested parties to understand and view the complete DOE complex-wide picture, the radioactive waste and shipment information of each DOE site needed to be entered into a common application. The WIMS application was therefore created to serve as a common application to improve stakeholder comprehension and improve DOE radioactive waste treatment and disposal planning and scheduling. WIMS allows identification of total forecasted waste volumes, material classes, disposition sites, choke points, technological or regulatory barriers to treatment and disposal, along with forecasted waste transportation information by rail, truck and inter-modal shipments. The Applied Research Center (ARC) at Florida International University (FIU) in Miami, Florida, developed and deployed the web-based forecast and transportation system and is responsible for updating the radioactive waste forecast and transportation data on a regular basis to ensure the long-term viability and value of this system. WIMS continues to successfully accomplish the goals and objectives set forth by DOE for this project. It has replaced the historic process of each DOE site gathering, organizing, and reporting their waste forecast information utilizing different databases and display technologies. In addition, WIMS meets DOE's objective to have the complex-wide waste forecast and transportation information available to all stakeholders and the public in one easy-to-navigate system. The enhancements to WIMS made since its initial deployment include the addition of new DOE sites and facilities, an updated waste and transportation information, and the ability to easily display and print customized waste forecast, the disposition maps, GIS maps and transportation information. The system also allows users to customize and generate reports over the web. These reports can be exported to various formats, such as Adobe{sup R} PDF, Microsoft Excel{sup R}, and Microsoft Word{sup R} and downloaded to the user's computer. Future enhancements will include database/application migration to the next level. A new data import interface will be developed to integrate 2012-13 forecast waste streams. In addition, the application is updated on a continuous basis based on DOE feedback. (authors)« less

The value of improved wind power forecasting: Grid flexibility quantification, ramp capability analysis, and impacts of electricity market operation timescales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Qin; Wu, Hongyu; Florita, Anthony R.

The value of improving wind power forecasting accuracy at different electricity market operation timescales was analyzed by simulating the IEEE 118-bus test system as modified to emulate the generation mixes of the Midcontinent, California, and New England independent system operator balancing authority areas. The wind power forecasting improvement methodology and error analysis for the data set were elaborated. Production cost simulation was conducted on the three emulated systems with a total of 480 scenarios, considering the impacts of different generation technologies, wind penetration levels, and wind power forecasting improvement timescales. The static operational flexibility of the three systems was comparedmore » through the diversity of generation mix, the percentage of must-run baseload generators, as well as the available ramp rate and the minimum generation levels. The dynamic operational flexibility was evaluated by the real-time upward and downward ramp capacity. Simulation results show that the generation resource mix plays a crucial role in evaluating the value of improved wind power forecasting at different timescales. In addition, the changes in annual operational electricity generation costs were mostly influenced by the dominant resource in the system. Lastly, the impacts of pumped-storage resources, generation ramp rates, and system minimum generation level requirements on the value of improved wind power forecasting were also analyzed.« less

Development of a WRF-RTFDDA-based high-resolution hybrid data-assimilation and forecasting system toward to operation in the Middle East

NASA Astrophysics Data System (ADS)

Liu, Y.; Wu, W.; Zhang, Y.; Kucera, P. A.; Liu, Y.; Pan, L.

2012-12-01

Weather forecasting in the Middle East is challenging because of its complicated geographical nature including massive coastal area and heterogeneous land, and regional spare observational network. Strong air-land-sea interactions form multi-scale weather regimes in the area, which require a numerical weather prediction model capable of properly representing multi-scale atmospheric flow with appropriate initial conditions. The WRF-based Real-Time Four Dimensional Data Assimilation (RTFDDA) system is one of advanced multi-scale weather analysis and forecasting facilities developed at the Research Applications Laboratory (RAL) of NCAR. The forecasting system is applied for the Middle East with careful configuration. To overcome the limitation of the very sparsely available conventional observations in the region, we develop a hybrid data assimilation algorithm combining RTFDDA and WRF-3DVAR, which ingests remote sensing data from satellites and radar. This hybrid data assimilation blends Newtonian nudging FDDA and 3DVAR technology to effectively assimilate both conventional observations and remote sensing measurements and provide improved initial conditions for the forecasting system. For brevity, the forecasting system is called RTF3H (RTFDDA-3DVAR Hybrid). In this presentation, we will discuss the hybrid data assimilation algorithm, and its implementation, and the applications for high-impact weather events in the area. Sensitivity studies are conducted to understand the strength and limitations of this hybrid data assimilation algorithm.

The value of improved wind power forecasting: Grid flexibility quantification, ramp capability analysis, and impacts of electricity market operation timescales

DOE PAGES

Wang, Qin; Wu, Hongyu; Florita, Anthony R.; ...

2016-11-11

The value of improving wind power forecasting accuracy at different electricity market operation timescales was analyzed by simulating the IEEE 118-bus test system as modified to emulate the generation mixes of the Midcontinent, California, and New England independent system operator balancing authority areas. The wind power forecasting improvement methodology and error analysis for the data set were elaborated. Production cost simulation was conducted on the three emulated systems with a total of 480 scenarios, considering the impacts of different generation technologies, wind penetration levels, and wind power forecasting improvement timescales. The static operational flexibility of the three systems was comparedmore » through the diversity of generation mix, the percentage of must-run baseload generators, as well as the available ramp rate and the minimum generation levels. The dynamic operational flexibility was evaluated by the real-time upward and downward ramp capacity. Simulation results show that the generation resource mix plays a crucial role in evaluating the value of improved wind power forecasting at different timescales. In addition, the changes in annual operational electricity generation costs were mostly influenced by the dominant resource in the system. Lastly, the impacts of pumped-storage resources, generation ramp rates, and system minimum generation level requirements on the value of improved wind power forecasting were also analyzed.« less

Data Mining for Forecasting Mississippi Cropland Data Layers

NASA Astrophysics Data System (ADS)

Shore, F. L.; Gregory, T. L.

2011-12-01

In 1999, Mississippi became an early adopter of the National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) program. With the support of the NASS Spatial Analysis Research Section (SARS), we have progressed from an annual crop picture to a pixel by pixel history of Mississippi farming. Much of our early work for Mississippi agriculture is now easily provided from the web based application CropScape, released by SARS in 2011. In this study, pixel history data from CDLs has been mined to give forecasts of Mississippi crop acres. Traditionally, such agricultural data mining emphasizes the trends of early adopters driven by factors such as global warming, technology, practices, or the marketplace. These studies provide forecasted CDL products produced using See5° and Imagine°, the same software used in Mississippi CDL production since 2006. Mississippi CDL forecasts were made using historical information available as soon as the CDL for the previous year was completed. For example, the CDL forecast for winter wheat, produced at a date when winter wheat was planted but not most crops, gave results of 104.6 +/- 5.4% of the official NASS estimates for winter wheat for the years 2009-2011. In 2012, all of the states of the contiguous US will have the historical CDL data to do this type of study. A CDL forecast is proposed as a useful addition to CropScape.

A View of Hurricane Katrina with Early 2lSt Century Technology

NASA Technical Reports Server (NTRS)

Lin, Xin; Li, J.-L.; Suarez, M. J.; Tompkins, A. M.; Waliser, D. E.; Rienecker, M. M.; Bacmeister, J.; Jiang, J.; Wu, H.-T.; Tassone, C. M.

2006-01-01

Recent advances in space-borne observations and numerical weather prediction models provide new opportunities for improving hurricane forecasts. In this study, state-of-the-art satellite observations are used to document the evolution of one of the most devastating tropical cyclones ever to hit the United States: Hurricane Katrina. The ECMWF and NASA global high-resolution forecasts, the latter being run in experimental mode, are compared with satellite observations, with a focus on precipitation and cloud processes. Future directions on modeling and observations are briefly discussed.

Storms in Space

NASA Astrophysics Data System (ADS)

Freeman, John W.

2012-11-01

Introduction; The cast of characters; Vignettes of the storm; 1. Two kinds of weather; 2. The saga of the storm; 3. Weather stations in space; 4. Lights in the night: the signature of the storm; 5. A walking tour of the magnetosphere; 6. The sun: where it all begins; 7. Nowcasting and forecasting storms in space; 8. Technology and the risks from storms in space; 9. A conversation with Joe Allen; 10. Manned exploration and space weather hazards; 11. The present and future of space weather forecasting; Mathematical appendix. A closer look; Glossary; Figure captions.

Surface Water and Flood Extent Mapping, Monitoring, and Modeling Products and Services for the SERVIR Regions

NASA Technical Reports Server (NTRS)

Anderson, Eric

2016-01-01

SERVIR is a joint NASA - US Agency for International Development (USAID) project to improve environmental decision-making using Earth observations and geospatial technologies. A common need identified among SERVIR regions has been improved information for disaster risk reduction and in specific surface water and flood extent mapping, monitoring and forecasting. Of the 70 SERVIR products (active, complete, and in development), 4 are related to surface water and flood extent mapping, monitoring or forecasting. Visit http://www.servircatalog.net for more product details.

First in new environmental spacecraft series to be launched

NASA Technical Reports Server (NTRS)

1978-01-01

A series of operational meteorological monitoring satellites (TIROS-N) is described. Emphasis is placed on environmental monitoring instruments onboard the satellites that provide technological advances over previous sensors. Benefits in the areas of weather forecasting, oceanography, water resource management, and flood forecasting are discussed along with the operational capability to collect and transmit environmental data from platforms on land, at sea, and airborne, and to track stations motion. The participation of Canada, Great Britain, and France is mentioned and a description of the launch vehicle is included.

The large area crop inventory experiment: A major demonstration of space remote sensing

NASA Technical Reports Server (NTRS)

Macdonald, R. B.; Hall, F. G.

1977-01-01

Strategies are presented in agricultural technology to increase the resistance of crops to a wider range of meteorological conditions in order to reduce year-to-year variations in crop production. Uncertainties in agricultral production, together with the consumer demands of an increasing world population, have greatly intensified the need for early and accurate annual global crop production forecasts. These forecasts must predict fluctuation with an accuracy, timeliness and known reliability sufficient to permit necessary social and economic adjustments, with as much advance warning as possible.

A prospective approach to coastal geography from satellite. [technological forecasting

NASA Technical Reports Server (NTRS)

Munday, J. C., Jr.

1981-01-01

A forecasting protocol termed the "prospective approach' was used to examine probable futures relative to coastal applications of satellite data. Significant variables include the energy situation, the national economy, national Earth satellite programs, and coastal zone research, commercial activity, and regulatory activity. Alternative scenarios for the period until 1986 are presented. Possible response by state/local remote sensing centers include operational applications for users, input to geo-base information systems (GIS), development of decision-making algorithms using GIS data, and long term research programs for coastal management using merged satellite and traditional data.

A state of the art regarding urban air quality prediction models

NASA Astrophysics Data System (ADS)

Croitoru, Cristiana; Nastase, Ilinca

2018-02-01

Urban pollution represents an increasing risk to residents of urban regions, particularly in large, over-industrialized cities knowing that the traffic is responsible for more than 25% of air gaseous pollutants and dust particles. Air quality modelling plays an important role in addressing air pollution control and management approaches by providing guidelines for better and more efficient air quality forecasting, along with smart monitoring sensor networks. The advances in technology regarding simulations, forecasting and monitoring are part of the new smart cities which offers a healthy environment for their occupants.

Technological change, depletion and environmental policy in the offshore oil and gas industry

NASA Astrophysics Data System (ADS)

Managi, Shunsuke

Technological change is central to maintaining standards of living in modern economies with finite resources and increasingly stringent environmental goals. Successful environmental policies can contribute to efficiency by encouraging, rather than inhibiting, technological innovation. However, little research to date has focused on the design and implementation of environmental regulations that encourage technological progress, or in insuring productivity improvements in the face of depletion of natural resources and increasing stringency of environmental regulations. This study models and measures productivity change, with an application to offshore oil and gas production in the Gulf of Mexico using Data Envelopment Analysis. This is an important application because energy resources are central to sustaining our economy. The net effects of technological progress and depletion on productivity of offshore oil and gas production are measured using a unique field-level set of data of production from all wells in the Gulf of Mexico over the time period from 1946--1998. Results are consistent with the hypothesis that technological progress has mitigated depletion effects over the study period, but the pattern differs from the conventional wisdom for nonrenewable resource industries. The Porter Hypothesis was recast, and revised version was tested. The Porter Hypothesis states that well designed environmental regulations can potentially contribute to productive efficiency in the long run by encouraging innovation. The Porter Hypothesis was recast to include market and nonmarket outputs. Our results support the recast version of Porter hypothesis, which examine productivity of joint production of market and environmental outputs. But we find no evidence for the standard formulation of the Porter hypothesis, that increased stringency of environmental regulation lead to increased productivity of market outputs and therefore increased industry profits. The model is used to forecast market and environmental outputs under alternative policy scenarios. Reliable baseline forecast and response to different policy actions of production and pollution are critical to the formation of sound energy and environmental policy. Forecast of production and pollution until year 2050 are generated from the model. Detailed policy scenarios provide quantitative assessments of potential benefits that indicate the significance of potential benefits of technological change and well-designed environmental policy.

A Research on Development of The Multi-mode Flood Forecasting System Version Management

NASA Astrophysics Data System (ADS)

Shen, J.-C.; Chang, C. H.; Lien, H. C.; Wu, S. J.; Horng, M. J.

2009-04-01

With the global economy and technological development, the degree of urbanization and population density relative to raise. At the same time, a natural buffer space and resources year after year, the situation has been weakened, not only lead to potential environmental disasters, more and more serious, disaster caused by the economy, loss of natural environment at all levels has been expanded. In view of this, the active participation of all countries in the world cross-sectoral integration of disaster prevention technology research and development, in addition, the specialized field of disaster prevention technology, science and technology development, network integration technology, high-speed data transmission and information to support the establishment of mechanisms for disaster management The decision-making and cross-border global disaster information network building and other related technologies, has become the international anti-disaster science and technology development trends, this trend. Naturally a few years in Taiwan, people's lives and property losses caused by many problems related to natural disaster prevention and disaster prevention and the establishment of applications has become a very important. For FEWS_Taiwan, flood warning system developed by the Delft Hydraulics and introduced the Water Resources Agency (WRA), it provides those functionalities for users to modify contents to add the basins, regions, data sources, models and etc. Despite this advantage, version differences due to different users or different teams yet bring about the difficulties on synchronization and integration.At the same time in different research teams will also add different modes of meteorological and hydrological data. From the government perspective of WRA, the need to plan standard operation procedures for system integration demands that the effort for version control due to version differences must be cost down or yet canceled out. As for FEWS_Taiwan, this paper proposed the feasible avenues and solutions to smoothly integrate different configurations from different teams. In the current system has been completed by 20 of Taiwan's main rivers in the building of the basic structure of the flood forecasting. And regular updating of the relevant parameters, using the new survey results, in order to have a better flood forecasting results.

Analysis on the application of background parameters on remote sensing classification

NASA Astrophysics Data System (ADS)

Qiao, Y.

Drawing accurate crop cultivation acreage, dynamic monitoring of crops growing and yield forecast are some important applications of remote sensing to agriculture. During the 8th 5-Year Plan period, the task of yield estimation using remote sensing technology for the main crops in major production regions in China once was a subtopic to the national research task titled "Study on Application of Remote sensing Technology". In 21 century in a movement launched by Chinese Ministry of Agriculture to combine high technology to farming production, remote sensing has given full play to farm crops' growth monitoring and yield forecast. And later in 2001 Chinese Ministry of Agriculture entrusted the Northern China Center of Agricultural Remote Sensing to forecast yield of some main crops like wheat, maize and rice in rather short time to supply information for the government decision maker. Present paper is a report for this task. It describes the application of background parameters in image recognition, classification and mapping with focuses on plan of the geo-science's theory, ecological feature and its cartographical objects or scale, the study of phrenology for image optimal time for classification of the ground objects, the analysis of optimal waveband composition and the application of background data base to spatial information recognition ;The research based on the knowledge of background parameters is indispensable for improving the accuracy of image classification and mapping quality and won a secondary reward of tech-science achievement from Chinese Ministry of Agriculture. Keywords: Spatial image; Classification; Background parameter

From Forecasters to the General Public: A Communication Tool to Understand Decision-making Challenges in Weather-related Early Warning Systems

NASA Astrophysics Data System (ADS)

Terti, G.; Ruin, I.; Kalas, M.; Lorini, V.; Sabbatini, T.; i Alonso, A. C.

2017-12-01

New technologies are currently adopted worldwide to improve weather forecasts and communication of the corresponding warnings to the end-users. "EnhANcing emergency management and response to extreme WeatHER and climate Events" (ANYWHERE) project is an innovating action that aims at developing and implementing a European decision-support platform for weather-related risks integrating cutting-edge forecasting technology. The initiative is built in a collaborative manner where researchers, developers, potential users and other stakeholders meet frequently to define needs, capabilities and challenges. In this study, we propose a role-playing game to test the added value of the ANYWHERE platform on i) the decision-making process and the choice of warning levels under uncertainty, ii) the management of the official emergency response and iii) the crisis communication and triggering of protective actions at different levels of the warning system (from hazard detection to citizen response). The designed game serves as an interactive communication tool. Here, flood and flash flood focused simulations seek to enhance participant's understanding of the complexities and challenges embedded in various levels of the decision-making process under the threat of weather disasters (e.g., forecasting/warnings, official emergency actions, self-protection). Also, we facilitate collaboration and coordination between the participants who belong to different national or local agencies/authorities across Europe. The game is first applied and tested in ANYWHERE's workshop in Helsinki (September, 2017) where about 30-50 people, including researchers, forecasters, civil protection and representatives of related companies, are anticipated to play the simulation. The main idea is to provide to the players a virtual case study that well represents realistic uncertainties and dilemmas embedded in the real-time forecasting-warning processes. At the final debriefing step the participants are encouraged to exchange knowledge, thoughts and insights on their capability or difficulty to decide and communicate their action based on the available information and given constrains. Such feedback will be analyzed and presented and future potentialities for the application of the game will be discussed.

Application of Regional Drought and Crop Yield Information System to enhance drought monitoring and forecasting in Lower Mekong region

NASA Astrophysics Data System (ADS)

Jayasinghe, S.; Dutta, R.; Basnayake, S. B.; Granger, S. L.; Andreadis, K. M.; Das, N.; Markert, K. N.; Cutter, P. G.; Towashiraporn, P.; Anderson, E.

2017-12-01

The Lower Mekong Region has been experiencing frequent and prolonged droughts resulting in severe damage to agricultural production leading to food insecurity and impacts on livelihoods of the farming communities. Climate variability further complicates the situation by making drought harder to forecast. The Regional Drought and Crop Yield Information System (RDCYIS), developed by SERVIR-Mekong, helps decision makers to take effective measures through monitoring, analyzing and forecasting of drought conditions and providing early warnings to farmers to make adjustments to cropping calendars. The RDCYIS is built on regionally calibrated Regional Hydrologic Extreme Assessment System (RHEAS) framework that integrates the Variable Infiltration Capacity (VIC) and Decision Support System for Agro-technology Transfer (DSSAT) models, allowing both nowcast and forecast of drought. The RHEAS allows ingestion of numerus freely available earth observation and ground observation data to generate and customize drought related indices, variables and crop yield information for better decision making. The Lower Mekong region has experienced severe drought in 2016 encompassing the region's worst drought in 90 years. This paper presents the simulation of the 2016 drought event using RDCYIS based on its hindcast and forecast capabilities. The regionally calibrated RDCYIS can help capture salient features of drought through a variety of drought indices, soil variables, energy balance variables and water balance variables. The RDCYIS is capable of assimilating soil moisture data from different satellite products and perform ensemble runs to further reduce the uncertainty of it outputs. The calibrated results have correlation coefficient around 0.73 and NSE between 0.4-0.5. Based on the acceptable results of the retrospective runs, the system has the potential to generate reliable drought monitoring and forecasting information to improve decision-makings at operational, technological and institutional level of mandated institutes of lower Mekong countries. This is turn would help countries to prepare for and respond to drought situations by taking short and long-term risk mitigation measures such as adjusting cropping calendars, rainwater harvesting, and so on.

Astrophysics space systems critical technology needs

NASA Technical Reports Server (NTRS)

Gartrell, C. F.

1982-01-01

This paper addresses an independent assessment of space system technology needs for future astrophysics flight programs contained within the NASA Space Systems Technology Model. The critical examination of the system needs for the approximately 30 flight programs in the model are compared to independent technology forecasts and possible technology deficits are discussed. These deficits impact the developments needed for spacecraft propulsion, power, materials, structures, navigation, guidance and control, sensors, communications and data processing. There are also associated impacts upon in-orbit assembly technology and space transportation systems. A number of under-utilized technologies are highlighted which could be exploited to reduce cost and enhance scientific return.

Analysis of the Climate Change Technology Initiative

EIA Publications

1999-01-01

Analysis of the impact of specific policies on the reduction of carbon emissions and their impact on U.S. energy use and prices in the 2008-2012 time frame. Also, analyzes the impact of the President's Climate Change Technology Initiative, as defined for the 2000 budget, on reducing carbon emissions from the levels forecast in the Annual Energy Outlook 1999 reference case.

Identification of Occupational Areas for Indiana's Future. Final Report of the Technology Forecasting Task Force.

ERIC Educational Resources Information Center

Indiana State Commission on Vocational and Technical Education, Indianapolis.

A task force representing the Indiana private sector was convened for two purposes: to (1) identify the impact of technology on required worker skills, the labor market, and the vocational education, training, and employment system; and (2) identify occupational areas that should be future growth areas for the state. Task force members reviewed…

GSFC Technology Development Center Report

NASA Technical Reports Server (NTRS)

Himwich, Ed; Gipson, John

2013-01-01

This report summarizes the activities of the GSFC Technology Development Center (TDC) for 2012 and forecasts planned activities for 2013. The GSFC TDC develops station software including the Field System (FS), scheduling software (SKED), hardware including tools for station timing and meteorology, scheduling algorithms, and operational procedures. It provides a pool of individuals to assist with station implementation, check-out, upgrades, and training.

STAPOL: A Simulation of the Impact of Policy, Values, and Technological and Societal Developments upon the Quality of Life.

ERIC Educational Resources Information Center

Little, Dennis; Feller, Richard

The Institute for the Future has been conducting research in technological and societal forecasting, social indicators, value change, and simulation gaming. This paper describes an effort to bring together parts of that research into a simulation game ("State Policy," or STAPOL) for analysis of the impact of government policy, social values, and…

AgRISTARS: Agriculture and resources inventory surveys through aerospace remote sensing

NASA Technical Reports Server (NTRS)

1982-01-01

The rationale, objectives, participants, and approach of the AgRISTARS program are described. Progress is reported in activities related to early warning and crop condition assessment; inventory technology development (formerly foreign commodity production forecasting); yield model development; supporting research; soil moisture; renewable resources inventory; domestic crops and land cover; and conservation and pollution. Emphasis is on technological highlights.

Report of the Workshop on Magnetic Information Technology - MINT (Washington, D.C., June 22-24, 1983).

ERIC Educational Resources Information Center

Bortz, Alfred B.; Dunkle, Susan B.

Magnetic Information Technology (MINT), which involves use of magnetic techniques and materials to store information, is a critical growth industry in the United States. However, experts from both industry and academe forecast the inability of the United States to meet demand in this area. According to these experts, growth of magnetic information…

How accurate are the weather forecasts for Bierun (southern Poland)?

NASA Astrophysics Data System (ADS)

Gawor, J.

2012-04-01

Weather forecast accuracy has increased in recent times mainly thanks to significant development of numerical weather prediction models. Despite the improvements, the forecasts should be verified to control their quality. The evaluation of forecast accuracy can also be an interesting learning activity for students. It joins natural curiosity about everyday weather and scientific process skills: problem solving, database technologies, graph construction and graphical analysis. The examination of the weather forecasts has been taken by a group of 14-year-old students from Bierun (southern Poland). They participate in the GLOBE program to develop inquiry-based investigations of the local environment. For the atmospheric research the automatic weather station is used. The observed data were compared with corresponding forecasts produced by two numerical weather prediction models, i.e. COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) developed by Naval Research Laboratory Monterey, USA; it runs operationally at the Interdisciplinary Centre for Mathematical and Computational Modelling in Warsaw, Poland and COSMO (The Consortium for Small-scale Modelling) used by the Polish Institute of Meteorology and Water Management. The analysed data included air temperature, precipitation, wind speed, wind chill and sea level pressure. The prediction periods from 0 to 24 hours (Day 1) and from 24 to 48 hours (Day 2) were considered. The verification statistics that are commonly used in meteorology have been applied: mean error, also known as bias, for continuous data and a 2x2 contingency table to get the hit rate and false alarm ratio for a few precipitation thresholds. The results of the aforementioned activity became an interesting basis for discussion. The most important topics are: 1) to what extent can we rely on the weather forecasts? 2) How accurate are the forecasts for two considered time ranges? 3) Which precipitation threshold is the most predictable? 4) Why are some weather elements easier to verify than others? 5) What factors may contribute to the quality of the weather forecast?

NASA Office of Aeronautics and Space Technology Summer Workshop. Volume 8: Thermal control panel

NASA Technical Reports Server (NTRS)

1975-01-01

Technology deficiencies in the area of thermal control for future space missions are identified with emphasis on large space structures and cold controlled environments. Thermal control surfaces, heat pipes, and contamination are considered along with cryogenics, insulation, and design techniques. Major directions forecast for thermal control technology development and space experiments are: (1) extend the useful lifetime of cryogenic systems for space, (2) reduce temperature gradients, and (3) improve temperature stability.

Long-Term Electronic Technology Trends: Forecasted Impacts on Education. Paper presented to Congress of the United States, House of Representatives, Committee on Education and Labor, Subcommittee on Elementary, Secondary, and Vocational Education (April 25, 1979).

ERIC Educational Resources Information Center

Joseph, Earl C.

The technological-driven future will evolve through the next decades to massively impact elementary and secondary education, starting in the 1980 decade and building toward revolutionizing education in the 1990 decade. The evolving "silicon revolution" is producing a continuing list of new electronic technology poised at the threshold for massive…

The FAST-T approach for operational, real time, short term hydrological forecasting: Results from the Betania Hydropower Reservoir case study

NASA Astrophysics Data System (ADS)

Domínguez, Efraín; Angarita, Hector; Rosmann, Thomas; Mendez, Zulma; Angulo, Gustavo

2013-04-01

A viable quantitative hydrological forecasting service is a combination of technological elements, personnel and knowledge, working together to establish a stable operational cycle of forecasts emission, dissemination and assimilation; hence, the process for establishing such system usually requires significant resources and time to reach an adequate development and integration in order to produce forecasts with acceptable levels of performance. Here are presented the results of this process for the recently implemented Operational Forecast Service for the Betania's Hydropower Reservoir - or SPHEB, located at the Upper-Magdalena River Basin (Colombia). The current scope of the SPHEB includes forecasting of water levels and discharge for the three main streams affluent to the reservoir, for lead times between +1 to +57 hours, and +1 to +10 days. The core of the SPHEB is the Flexible, Adaptive, Simple and Transient Time forecasting approach, namely FAST-T. This comprises of a set of data structures, mathematical kernel, distributed computing and network infrastructure designed to provide seamless real-time operational forecast and automatic model adjustment in case of failures in data transmission or assimilation. Among FAST-T main features are: an autonomous evaluation and detection of the most relevant information for the later configuration of forecasting models; an adaptively linearized mathematical kernel, the optimal adaptive linear combination or OALC, which provides a computationally simple and efficient algorithm for real-time applications; and finally, a meta-model catalog, containing prioritized forecast models at given stream conditions. The SPHEB is at present feed by the fraction of hydrological monitoring network installed at the basin that has telemetric capabilities via NOAA-GOES satellites (8 stages, approximately 47%) with data availability of about a 90% at one hour intervals. However, there is a dense network of 'conventional' hydro-meteorological stages -read manually once or twice per day - that, despite not ideal in the context of real-time system, improve model performance significantly, and therefore are entered into the system by manual input. At its current configuration, the SPHEB performance objectives are fulfilled for 90% of the forecasts with lead times up to +2 days and +15 hours (using the predictability criteria of the Russian Hydrometeorological Center S/?Δ) and the average accuracy is in the range 70-99% ( r2 criteria). However, longer lead times are at present not satisfactory in terms of forecasts accuracy.

Evaluation of Thompson-type trend and monthly weather data models for corn yields in Iowa, Illinois, and Indiana

NASA Technical Reports Server (NTRS)

French, V. (Principal Investigator)

1982-01-01

An evaluation was made of Thompson-Type models which use trend terms (as a surrogate for technology), meteorological variables based on monthly average temperature, and total precipitation to forecast and estimate corn yields in Iowa, Illinois, and Indiana. Pooled and unpooled Thompson-type models were compared. Neither was found to be consistently superior to the other. Yield reliability indicators show that the models are of limited use for large area yield estimation. The models are objective and consistent with scientific knowledge. Timely yield forecasts and estimates can be made during the growing season by using normals or long range weather forecasts. The models are not costly to operate and are easy to use and understand. The model standard errors of prediction do not provide a useful current measure of modeled yield reliability.

Forecasting techno-social systems: how physics and computing help to fight off global pandemics

NASA Astrophysics Data System (ADS)

Vespignani, Alessandro

2010-03-01

The crucial issue when planning for adequate public health interventions to mitigate the spread and impact of epidemics is risk evaluation and forecast. This amount to the anticipation of where, when and how strong the epidemic will strike. In the last decade advances in performance in computer technology, data acquisition, statistical physics and complex networks theory allow the generation of sophisticated simulations on supercomputer infrastructures to anticipate the spreading pattern of a pandemic. For the first time we are in the position of generating real time forecast of epidemic spreading. I will review the history of the current H1N1 pandemic, the major road-blocks the community has faced in its containment and mitigation and how physics and computing provide predictive tools that help us to battle epidemics.

Development of modelling algorithm of technological systems by statistical tests

NASA Astrophysics Data System (ADS)

Shemshura, E. A.; Otrokov, A. V.; Chernyh, V. G.

2018-03-01

The paper tackles the problem of economic assessment of design efficiency regarding various technological systems at the stage of their operation. The modelling algorithm of a technological system was performed using statistical tests and with account of the reliability index allows estimating the level of machinery technical excellence and defining the efficiency of design reliability against its performance. Economic feasibility of its application shall be determined on the basis of service quality of a technological system with further forecasting of volumes and the range of spare parts supply.

Hydrocarbon Rocket Technology Impact Forecasting

NASA Technical Reports Server (NTRS)

Stuber, Eric; Prasadh, Nishant; Edwards, Stephen; Mavris, Dimitri N.

2012-01-01

Ever since the Apollo program ended, the development of launch propulsion systems in the US has fallen drastically, with only two new booster engine developments, the SSME and the RS-68, occurring in the past few decades.1 In recent years, however, there has been an increased interest in pursuing more effective launch propulsion technologies in the U.S., exemplified by the NASA Office of the Chief Technologist s inclusion of Launch Propulsion Systems as the first technological area in the Space Technology Roadmaps2. One area of particular interest to both government agencies and commercial entities has been the development of hydrocarbon engines; NASA and the Air Force Research Lab3 have expressed interest in the use of hydrocarbon fuels for their respective SLS Booster and Reusable Booster System concepts, and two major commercially-developed launch vehicles SpaceX s Falcon 9 and Orbital Sciences Antares feature engines that use RP-1 kerosene fuel. Compared to engines powered by liquid hydrogen, hydrocarbon-fueled engines have a greater propellant density (usually resulting in a lighter overall engine), produce greater propulsive force, possess easier fuel handling and loading, and for reusable vehicle concepts can provide a shorter turnaround time between launches. These benefits suggest that a hydrocarbon-fueled launch vehicle would allow for a cheap and frequent means of access to space.1 However, the time and money required for the development of a new engine still presents a major challenge. Long and costly design, development, testing and evaluation (DDT&E) programs underscore the importance of identifying critical technologies and prioritizing investment efforts. Trade studies must be performed on engine concepts examining the affordability, operability, and reliability of each concept, and quantifying the impacts of proposed technologies. These studies can be performed through use of the Technology Impact Forecasting (TIF) method. The Technology Impact Forecasting method is a normative forecasting technique that allows the designer to quantify the effects of adding new technologies on a given design. This method can be used to assess and identify the necessary technological improvements needed to close the gap that exists between the current design and one that satisfies all constraints imposed on the design. The TIF methodology allows for more design knowledge to be brought to the earlier phases of the design process, making use of tools such as Quality Function Deployments, Morphological Matrices, Response Surface Methodology, and Monte Carlo Simulations.2 This increased knowledge allows for more informed decisions to be made earlier in the design process, resulting in shortened design cycle time. This paper will investigate applying the TIF method, which has been widely used in aircraft applications, to the conceptual design of a hydrocarbon rocket engine. In order to reinstate a manned presence in space, the U.S. must develop an affordable and sustainable launch capability. Hydrocarbon-fueled rockets have drawn interest from numerous major government and commercial entities because they offer a low-cost heavy-lift option that would allow for frequent launches1. However, the development of effective new hydrocarbon rockets would likely require new technologies in order to overcome certain design constraints. The use of advanced design methods, such as the TIF method, enables the designer to identify key areas in need of improvement, allowing one to dial in a proposed technology and assess its impact on the system. Through analyses such as this one, a conceptual design for a hydrocarbon-fueled vehicle that meets all imposed requirements can be achieved.

SCADA-based Operator Support System for Power Plant Equipment Fault Forecasting

NASA Astrophysics Data System (ADS)

Mayadevi, N.; Ushakumari, S. S.; Vinodchandra, S. S.

2014-12-01

Power plant equipment must be monitored closely to prevent failures from disrupting plant availability. Online monitoring technology integrated with hybrid forecasting techniques can be used to prevent plant equipment faults. A self learning rule-based expert system is proposed in this paper for fault forecasting in power plants controlled by supervisory control and data acquisition (SCADA) system. Self-learning utilizes associative data mining algorithms on the SCADA history database to form new rules that can dynamically update the knowledge base of the rule-based expert system. In this study, a number of popular associative learning algorithms are considered for rule formation. Data mining results show that the Tertius algorithm is best suited for developing a learning engine for power plants. For real-time monitoring of the plant condition, graphical models are constructed by K-means clustering. To build a time-series forecasting model, a multi layer preceptron (MLP) is used. Once created, the models are updated in the model library to provide an adaptive environment for the proposed system. Graphical user interface (GUI) illustrates the variation of all sensor values affecting a particular alarm/fault, as well as the step-by-step procedure for avoiding critical situations and consequent plant shutdown. The forecasting performance is evaluated by computing the mean absolute error and root mean square error of the predictions.

Operational Forecasting and Warning systems for Coastal hazards in Korea

NASA Astrophysics Data System (ADS)

Park, Kwang-Soon; Kwon, Jae-Il; Kim, Jin-Ah; Heo, Ki-Young; Jun, Kicheon

2017-04-01

Coastal hazards caused by both Mother Nature and humans cost tremendous social, economic and environmental damages. To mitigate these damages many countries have been running the operational forecasting or warning systems. Since 2009 Korea Operational Oceanographic System (KOOS) has been developed by the leading of Korea Institute of Ocean Science and Technology (KIOST) in Korea and KOOS has been operated in 2012. KOOS is consists of several operational modules of numerical models and real-time observations and produces the basic forecasting variables such as winds, tides, waves, currents, temperature and salinity and so on. In practical application systems include storm surges, oil spills, and search and rescue prediction models. In particular, abnormal high waves (swell-like high-height waves) have occurred in the East coast of Korea peninsula during winter season owing to the local meteorological condition over the East Sea, causing property damages and the loss of human lives. In order to improve wave forecast accuracy even very local wave characteristics, numerical wave modeling system using SWAN is established with data assimilation module using 4D-EnKF and sensitivity test has been conducted. During the typhoon period for the prediction of sever waves and the decision making support system for evacuation of the ships, a high-resolution wave forecasting system has been established and calibrated.

Assimilation of Feng-Yun-3B satellite microwave humidity sounder data over land

NASA Astrophysics Data System (ADS)

Chen, Keyi; Bormann, Niels; English, Stephen; Zhu, Jiang

2018-03-01

The ECMWF has been assimilating Feng-Yun-3B (FY-3B) satellite microwave humidity sounder (MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz (vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS (Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.

Satellites, tweets, forecasts: the future of flood disaster management?

NASA Astrophysics Data System (ADS)

Dottori, Francesco; Kalas, Milan; Lorini, Valerio; Wania, Annett; Pappenberger, Florian; Salamon, Peter; Ramos, Maria Helena; Cloke, Hannah; Castillo, Carlos

2017-04-01

Floods have devastating effects on lives and livelihoods around the world. Structural flood defence measures such as dikes and dams can help protect people. However, it is the emerging science and technologies for flood disaster management and preparedness, such as increasingly accurate flood forecasting systems, high-resolution satellite monitoring, rapid risk mapping, and the unique strength of social media information and crowdsourcing, that are most promising for reducing the impacts of flooding. Here, we describe an innovative framework which integrates in real-time two components of the Copernicus Emergency mapping services, namely the European Flood Awareness System and the satellite-based Rapid Mapping, with new procedures for rapid risk assessment and social media and news monitoring. The integrated framework enables improved flood impact forecast, thanks to the real-time integration of forecasting and monitoring components, and increases the timeliness and efficiency of satellite mapping, with the aim of capturing flood peaks and following the evolution of flooding processes. Thanks to the proposed framework, emergency responders will have access to a broad range of timely and accurate information for more effective and robust planning, decision-making, and resource allocation.

A probabilistic approach to the drag-based model

NASA Astrophysics Data System (ADS)

Napoletano, Gianluca; Forte, Roberta; Moro, Dario Del; Pietropaolo, Ermanno; Giovannelli, Luca; Berrilli, Francesco

2018-02-01

The forecast of the time of arrival (ToA) of a coronal mass ejection (CME) to Earth is of critical importance for our high-technology society and for any future manned exploration of the Solar System. As critical as the forecast accuracy is the knowledge of its precision, i.e. the error associated to the estimate. We propose a statistical approach for the computation of the ToA using the drag-based model by introducing the probability distributions, rather than exact values, as input parameters, thus allowing the evaluation of the uncertainty on the forecast. We test this approach using a set of CMEs whose transit times are known, and obtain extremely promising results: the average value of the absolute differences between measure and forecast is 9.1h, and half of these residuals are within the estimated errors. These results suggest that this approach deserves further investigation. We are working to realize a real-time implementation which ingests the outputs of automated CME tracking algorithms as inputs to create a database of events useful for a further validation of the approach.

Current gaps in understanding and predicting space weather: An operations perspective

NASA Astrophysics Data System (ADS)

Murtagh, W. J.

2016-12-01

The NOAA Space Weather Prediction Center (SWPC), one of the nine National Weather Service (NWS) National Centers for Environmental Prediction, is the Nation's official source for space weather alerts and warnings. Space weather effects the technology that forms the backbone of global economic vitality and national security, including satellite and airline operations, communications networks, and the electric power grid. Many of SWPC's over 48,000 subscribers rely on space weather forecasts for critical decision making. But extraordinary gaps still exist in our ability to meet customer needs for accurate and timely space weather forecasts and warnings. The 2015 National Space Weather Strategy recognizes that it is imperative that we improve the fundamental understanding of space weather and increase the accuracy, reliability, and timeliness of space-weather observations and forecasts in support of the growing demands. In this talk we provide a broad perspective of the key challenges that currently limit the forecaster's ability to better understand and predict space weather. We also examine the impact of these limitations on the end-user community.

The use of real-time off-site observations as a methodology for increasing forecast skill in prediction of large wind power ramps one or more hours ahead of their impact on a wind plant.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin Wilde, Principal Investigator

2012-12-31

ABSTRACT Application of Real-Time Offsite Measurements in Improved Short-Term Wind Ramp Prediction Skill Improved forecasting performance immediately preceding wind ramp events is of preeminent concern to most wind energy companies, system operators, and balancing authorities. The value of near real-time hub height-level wind data and more general meteorological measurements to short-term wind power forecasting is well understood. For some sites, access to onsite measured wind data - even historical - can reduce forecast error in the short-range to medium-range horizons by as much as 50%. Unfortunately, valuable free-stream wind measurements at tall tower are not typically available at most windmore » plants, thereby forcing wind forecasters to rely upon wind measurements below hub height and/or turbine nacelle anemometry. Free-stream measurements can be appropriately scaled to hub-height levels, using existing empirically-derived relationships that account for surface roughness and turbulence. But there is large uncertainty in these relationships for a given time of day and state of the boundary layer. Alternatively, forecasts can rely entirely on turbine anemometry measurements, though such measurements are themselves subject to wake effects that are not stationary. The void in free-stream hub-height level measurements of wind can be filled by remote sensing (e.g., sodar, lidar, and radar). However, the expense of such equipment may not be sustainable. There is a growing market for traditional anemometry on tall tower networks, maintained by third parties to the forecasting process (i.e., independent of forecasters and the forecast users). This study examines the value of offsite tall-tower data from the WINDataNOW Technology network for short-horizon wind power predictions at a wind farm in northern Montana. The presentation shall describe successful physical and statistical techniques for its application and the practicality of its application in an operational setting. It shall be demonstrated that when used properly, the real-time offsite measurements materially improve wind ramp capture and prediction statistics, when compared to traditional wind forecasting techniques and to a simple persistence model.« less

Sources of information for tsunami forecasting in New Zealand

NASA Astrophysics Data System (ADS)

Barberopoulou, A.; Ristau, J. P.; D'Anastasio, E.; Wang, X.

2013-12-01

Tsunami science has evolved considerably in the last two decades due to technological advancements which also helped push for better numerical modelling of the tsunami phases (generation to inundation). The deployment of DART buoys has also been a considerable milestone in tsunami forecasting. Tsunami forecasting is one of the parts that tsunami modelling feeds into and is related to response, preparedness and planning. Usually tsunami forecasting refers to short-term forecasting that takes place in real-time after a tsunami has or appears to have been generated. In this report we refer to all types of forecasting (short-term or long-term) related to work in advance of a tsunami impacting a coastline that would help in response, planning or preparedness. We look at the standard types of data (seismic, GPS, water level) that are available in New Zealand for tsunami forecasting, how they are currently being used, other ways to use these data and provide recommendations for better utilisation. The main findings are: -Current investigations of the use of seismic parameters quickly obtained after an earthquake, have potential to provide critical information about the tsunamigenic potential of earthquakes. Further analysis of the most promising methods should be undertaken to determine a path to full implementation. -Network communication of the largest part of the GPS network is not currently at a stage that can provide sufficient data early enough for tsunami warning. It is believed that it has potential, but changes including data transmission improvements may have to happen before real-time processing oriented to tsunami early warning is implemented on the data that is currently provided. -Tide gauge data is currently under-utilised for tsunami forecasting. Spectral analysis, modal analysis based on identified modes and arrival times extracted from the records can be useful in forecasting. -The current study is by no means exhaustive of the ways the different types of data can be used. We are only presenting an overview of what can be done. More extensive studies with each one of the types of data collected by GeoNet and other relevant networks will help improve tsunami forecasting in New Zealand.

The value of the North American Multi Model Ensemble phase 2 for sub-seasonal hydrological forecasting

NASA Astrophysics Data System (ADS)

Wanders, Niko; Wood, Eric

2016-04-01

Sub-seasonal to seasonal weather and hydrological forecasts have the potential to provide vital information for a variety of water-related decision makers. For example, seasonal forecasts of drought risk can enable farmers to make adaptive choices on crop varieties, labour usage, and technology investments. Seasonal and sub-seasonal predictions can increase preparedness to hydrological extremes that regularly occur in all regions of the world with large impacts on society. We investigated the skill of six seasonal forecast models from the NMME-2 ensemble coupled to two global hydrological models (VIC and PCRGLOBWB) for the period 1982-2012. The 31 years of NNME-2 hindcast data is used in combination with an ensemble mean and ESP forecast, to forecast important hydrological variables (e.g. soil moisture, groundwater storage, snow, reservoir levels and river discharge). By using two global hydrological models we are able to quantify both the uncertainty in the meteorological input and the uncertainty created by the different hydrological models. We show that the NMME-2 forecast outperforms the ESP forecasts in terms of anomaly correlation and brier skill score for all forecasted hydrological variables, with a low uncertainty in the performance amongst the hydrological models. However, the continuous ranked probability score (CRPS) of the NMME-2 ensemble is inferior to the ESP due to a large spread between the individual ensemble members. We use a cost analysis to show that the damage caused by floods and droughts in large scale rivers can globally be reduced by 48% (for leads from 1-2 months) to 20% (for leads between 6-9 months) when precautions are taken based on the NMME-2 ensemble instead of an ESP forecast. In collaboration with our local partner in West Africa (AGHRYMET), we looked at the performance of the sub-seasonal forecasts for crop planting dates and high flow season in West Africa. We show that the uncertainty in the optimal planting date is reduced from 30 days to 12 days (2.5 month lead) and an increased predictability of the high flow season from 45 days to 20 days (3-4 months lead). Additionally, we show that snow accumulation and melt onset in the Northern hemisphere can be forecasted with an uncertainty of 10 days (2.5 months lead). Both the overall skill, and the skill found in these last two examples, indicates that the new NMME-2 forecast dataset is valuable for sub-seasonal forecast applications. The high temporal resolution (daily), long leads (one year leads) and large hindcast archive enable new sub-seasonal forecasting applications to be explored. We show that the NMME-2 has a large potential for sub-seasonal hydrological forecasting and other potential hydrological applications (e.g. reservoir management), which could benefit from these new forecasts.

Development of statistical models to forecast crossing times of commercial vehicles.

DOT National Transportation Integrated Search

2011-07-01

Border crossing time measurement systems for commercial vehicles are being implemented throughout : the U.S.-Mexico border. These systems are based on radio frequency identification (RFID) technology. : With funding from the Federal Highway Administr...

The Future Revisited.

ERIC Educational Resources Information Center

Mason, Marilyn Gell

1996-01-01

Reviews earlier predictions about technological change in libraries, finds that providing equal access to information remains the library's mission, and forecasts the future. Topics include ownership versus access, electronic resources, information infrastructure, users, levels of service fees, circulation, librarians as "information…

INTEGRATED SCIENCE FOR ECOSYSTEM CHALLENGES - ISEC

EPA Science Inventory

In support of the National Science and Technology Council's cross-Agency priority of Integrated Science for Ecological Challenges (ISEC) EPA is conducting research to improve capabilities in the area of regional vulnerability assessment and ecological forecasting. EPA's research...

Practical operational implementation of Teton Pass avalanche monitoring infrasound system.

DOT National Transportation Integrated Search

2008-12-01

Highway snow avalanche forecasting programs typically rely on weather and field observations to make road closure and hazard : evaluations. Recently, infrasonic avalanche monitoring technology has been developed for practical use near Teton Pass, WY ...

Five Year Computer Technology Forecast

DOT National Transportation Integrated Search

1972-12-01

The report delineates the various computer system components and extrapolates past trends in light of industry goals and physical limitations to predict what individual components and entire systems will look like in the second half of this decade. T...

The 2017 Hurricane Season: A Revolution in Geostationary Weather Satellite Imaging and Data Processing

NASA Astrophysics Data System (ADS)

Weiner, A. M.; Gundy, J.; Brown-Bertold, B.; Yates, H.; Dobler, J. T.

2017-12-01

Since their introduction, geostationary weather satellites have enabled us to track hurricane life-cycle movement from development to dissipation. During the 2017 hurricane season, the new GOES-16 geostationary satellite demonstrated just how far we have progressed technologically in geostationary satellite imaging, with hurricane imagery showing never-before-seen detail of the hurricane eye and eyewall structure and life cycle. In addition, new ground system technology, leveraging high-performance computing, delivered imagery and data to forecasters with unprecedented speed—and with updates as often as every 30 seconds. As additional satellites and new products become operational, forecasters will be able to track hurricanes with even greater accuracy and assist in aftermath evaluations. This presentation will present glimpses into the past, a look at the present, and a prediction for the future utilization of geostationary satellites with respect to all facets of hurricane support.

Recent Progress of Solar Weather Forecasting at Naoc

NASA Astrophysics Data System (ADS)

He, Han; Wang, Huaning; Du, Zhanle; Zhang, Liyun; Huang, Xin; Yan, Yan; Fan, Yuliang; Zhu, Xiaoshuai; Guo, Xiaobo; Dai, Xinghua

The history of solar weather forecasting services at National Astronomical Observatories, Chinese Academy of Sciences (NAOC) can be traced back to 1960s. Nowadays, NAOC is the headquarters of the Regional Warning Center of China (RWC-China), which is one of the members of the International Space Environment Service (ISES). NAOC is responsible for exchanging data, information and space weather forecasts of RWC-China with other RWCs. The solar weather forecasting services at NAOC cover short-term prediction (within two or three days), medium-term prediction (within several weeks), and long-term prediction (in time scale of solar cycle) of solar activities. Most efforts of the short-term prediction research are concentrated on the solar eruptive phenomena, such as flares, coronal mass ejections (CMEs) and solar proton events, which are the key driving sources of strong space weather disturbances. Based on the high quality observation data of the latest space-based and ground-based solar telescopes and with the help of artificial intelligence techniques, new numerical models with quantitative analyses and physical consideration are being developed for the predictions of solar eruptive events. The 3-D computer simulation technology is being introduced for the operational solar weather service platform to visualize the monitoring of solar activities, the running of the prediction models, as well as the presenting of the forecasting results. A new generation operational solar weather monitoring and forecasting system is expected to be constructed in the near future at NAOC.

Effect of advanced aircraft noise reduction technology on the 1990 projected noise environment around Patrick Henry Airport. [development of noise exposure forecast contours for projected traffic volume and aircraft types

NASA Technical Reports Server (NTRS)

Cawthorn, J. M.; Brown, C. G.

1974-01-01

A study has been conducted of the future noise environment of Patric Henry Airport and its neighboring communities projected for the year 1990. An assessment was made of the impact of advanced noise reduction technologies which are currently being considered. These advanced technologies include a two-segment landing approach procedure and aircraft hardware modifications or retrofits which would add sound absorbent material in the nacelles of the engines or which would replace the present two- and three-stage fans with a single-stage fan of larger diameter. Noise Exposure Forecast (NEF) contours were computed for the baseline (nonretrofitted) aircraft for the projected traffic volume and fleet mix for the year 1990. These NEF contours are presented along with contours for a variety of retrofit options. Comparisons of the baseline with the noise reduction options are given in terms of total land area exposed to 30 and 40 NEF levels. Results are also presented of the effects on noise exposure area of the total number of daily operations.

Dogs That Haven't Barked: Towards an Understanding of the Absence of Expected Technological Threats Workshop Bibliography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roseman, Mallory; Zikry, Fareeda

Lawrence Livermore National Laboratory’s Center for Global Security Research hosted a workshop to investigate why some consistently predicted threats from science and technology (S&T) have not manifested with the impacts to international security as forecasted. During the workshop, “Dogs That Haven’t Barked: Towards an Understanding of the Absence of Expected Technological Threats,” participants used two specific cases to focus the discussion: biotechnology and man-portable air defense systems (MANPADS).

Power, Performance, and Perception (P3): Integrating Usability Metrics and Technology Acceptance Determinants to Validate a New Model for Predicting System Usage

DTIC Science & Technology

1999-12-01

Ajzen , I . and M . Fishbein . Understanding Attitudes and Predicting Social Behavior. ’ Prentice-Hall, Englewood Cliffs, NJ: 1980. Alwang, Greg. "Speech...Decline: Computer Introduction in the Financial Industry." Technology Forecasting and Social Change. 31: 143-154. Fishbein , M . and I . Ajzen . Belief...Theory of Reasoned Action (TRA) ( Fishbein and Ajzen , 1980) 13 3. Theory of Planned Behavior (TPB) ( Ajzen , 1991) 15 4. Technology Acceptance Model

[Innovation guidelines and strategies for pharmaceutical engineering of Chinese medicine and their industrial translation].

PubMed

Cheng, Yi-Yu; Qu, Hai-Bin; Zhang, Bo-Li

2013-01-01

This paper briefly analyzes the bottlenecks and major technical requirements for pharmaceutical industry of Chinese medicine, providing current status of pharmaceutical engineering of Chinese medicine. The innovation directions and strategies of the pharmaceutical engineering for manufacturing Chinese medicine are proposed along with the framework of their core technology. As a consequence, the development of the third-generation pharmaceutical technology for Chinese medicine, featured as "precision, digital and intelligent", is recommended. The prospects of the pharmaceutical technology are also forecasted.

High Resolution Wind Direction and Speed Information for Support of Fire Operations

Treesearch

B.W. Butler; J.M. Forthofer; M.A. Finney; L.S. Bradshaw; R. Stratton

2006-01-01

Computational Fluid Dynamics (CFD) technology has been used to model wind speed and direction in mountainous terrain at a relatively high resolution compared to other readily available technologies. The process termed “gridded wind” is not a forecast, but rather represents a method for calculating the influence of terrain on general wind flows. Gridded wind simulations...

JPRS Report, Science & Technology, China.

DTIC Science & Technology

1992-12-08

impor- tance of the computer information industry to the develop- ment of the national economy and the people’s standard of living. Forecasts call...past several years, and the application of computers has permeated every trade and industry , providing powerful SCIENCE & TECHNOLOGY POLICY JPRS...system and ample human talent; market potential is large; and it has potential for low cost develop- ment. However, the scale of its industrial

Truth, Perception, and Consequences (Proteus Monograph Series, Volume 1, Issue 1, November 2007)

DTIC Science & Technology

2007-11-01

Affective and Intellectual Autonomy in Schwartz, “Beyond individualism/ collectivism.” 56. Hofstede, Cultures and Organizations. 57. MacNulty and...strategic planning for cultural change, technology forecasting, and technology assessment. She consults at to the most senior levels within the...Department of Defense. Her current DoD projects bring together her knowledge of strategy, cultures , and cognition to help in understanding our

Assessment of Wearable Sensor Technologies for Biosurveillance

DTIC Science & Technology

2014-11-01

used in the field. By building devices that leverage elements such as more efficient operating systems and lower power requirements, developers may...technology into the hands of nearly every citizen. Mid-term forecasts for this sector anticipate the development and approval of more precise medical...Batteries with different shapes Paper USB intelliPaper A “smart” paper business card bearing a detachable paper USB drive Deep Tissue Power

Policy Challenges of Accelerating Technological Change: Security Policy and Strategy Implications of Parallel Scientific Revolutions

DTIC Science & Technology

2014-09-01

generation, exotic storage technologies, smart power grid management, and better power sources for directed-energy weapons (DEW). Accessible partner nation...near term will help to mitigate risks and improve outcomes. 2 Forecasting typically extrapolates predictions based...eventually, diminished national power . Within this context, this paper examines policy, legal, ethical, and strategy implications for DoD from the impact

Ionosphere monitoring and forecast activities within the IAG working group "Ionosphere Prediction"

NASA Astrophysics Data System (ADS)

Hoque, Mainul; Garcia-Rigo, Alberto; Erdogan, Eren; Cueto Santamaría, Marta; Jakowski, Norbert; Berdermann, Jens; Hernandez-Pajares, Manuel; Schmidt, Michael; Wilken, Volker

2017-04-01

Ionospheric disturbances can affect technologies in space and on Earth disrupting satellite and airline operations, communications networks, navigation systems. As the world becomes ever more dependent on these technologies, ionospheric disturbances as part of space weather pose an increasing risk to the economic vitality and national security. Therefore, having the knowledge of ionospheric state in advance during space weather events is becoming more and more important. To promote scientific cooperation we recently formed a Working Group (WG) called "Ionosphere Predictions" within the International Association of Geodesy (IAG) under Sub-Commission 4.3 "Atmosphere Remote Sensing" of the Commission 4 "Positioning and Applications". The general objective of the WG is to promote the development of ionosphere prediction algorithm/models based on the dependence of ionospheric characteristics on solar and magnetic conditions combining data from different sensors to improve the spatial and temporal resolution and sensitivity taking advantage of different sounding geometries and latency. Our presented work enables the possibility to compare total electron content (TEC) prediction approaches/results from different centers contributing to this WG such as German Aerospace Center (DLR), Universitat Politècnica de Catalunya (UPC), Technische Universität München (TUM) and GMV. DLR developed a model-assisted TEC forecast algorithm taking benefit from actual trends of the TEC behavior at each grid point. Since during perturbations, characterized by large TEC fluctuations or ionization fronts, this approach may fail, the trend information is merged with the current background model which provides a stable climatological TEC behavior. The presented solution is a first step to regularly provide forecasted TEC services via SWACI/IMPC by DLR. UPC forecast model is based on applying linear regression to a temporal window of TEC maps in the Discrete Cosine Transform (DCT) domain. Performance tests are being conducted at the moment in order to improve UPC predicted products for 1-, 2-days ahead. In addition, UPC is working to enable short-term predictions based on UPC real-time GIMs (labelled URTG) and implementing an improved prediction approach. TUM developed a forecast method based on a time series analysis of TEC products which are either B-spline coefficients estimated by a Kalman filter or TEC grid maps derived from the B-spline coefficients. The forecast method uses a Fourier series expansion to extract the trend functions from the estimated TEC product. Then the trend functions are carried out to provide predicted TEC products. The forecast algorithm developed by GMV is based on the ionospheric delay estimation from previous epochs using GNSS data and the main dependence of ionospheric delays on solar and magnetic conditions. Since the ionospheric behavior is highly dependent on the region of the Earth, different region-based algorithmic modifications have been implemented in GMV's magicSBAS ionospheric algorithms to be able to estimate and forecast ionospheric delays worldwide. Different TEC prediction approaches outlined here will certainly help to learn about forecasting ionospheric ionization.

Projecting long term medical spending growth.

PubMed

Borger, Christine; Rutherford, Thomas F; Won, Gregory Y

2008-01-01

We present a dynamic general equilibrium model of the U.S. economy and the medical sector in which the adoption of new medical treatments is endogenous and the demand for medical services is conditional on the state of technology. We use this model to prepare 75-year medical spending forecasts and a projection of the Medicare actuarial balance, and we compare our results to those obtained from a method that has been used by government actuaries. Our baseline forecast predicts slower health spending growth in the long run and a lower Medicare actuarial deficit relative to the previous projection methodology.

Information Technology Resources Assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1993-04-01

The Information Technology Resources Assessment (ITRA) is being published as a companion document to the Department of Energy (DOE) FY 1994--FY 1998 Information Resources Management Long-Range Plan. This document represents a collaborative effort between the Office of Information Resources Management and the Office of Energy Research that was undertaken to achieve, in part, the Technology Strategic Objective of IRM Vision 21. An integral part of this objective, technology forecasting provides an understanding of the information technology horizon and presents a perspective and focus on technologies of particular interest to DOE program activities. Specifically, this document provides site planners with anmore » overview of the status and use of new information technology for their planning consideration.« less

New tool for the Black Sea environmental safety: BlackSea Track Web

NASA Astrophysics Data System (ADS)

Kubryakov, A. I.; Korotayev, G. K.; Thoorens, F.-X.; Liungman, O.; Ambjorn, C.

2012-04-01

Huge increases in the volume of oil being transported across the Black Sea have greatly increased the risk of oil pollution. Remote sensing data show that the majority of oil spills occur along major shipping routes, suggesting that shipping, rather than land-based oil installations have been the principal cause of concern. However, a single large spill from ships, platforms or land-based oil installations could severely impact biota and the economies of all coastal countries and could produce significant damage of the Black Sea ecosystem and fishing. Also, due to the semi-enclosed character of the basin, oil spill will definitely pollute coast of the basin suffering great losses to the recreation industry and potentially to the human health. Fighting oil pollution in the Black Sea is a great challenge. The challenge is likely to become even greater in the future as maritime traffic is expected to increase over the next few years, making offences and accidents more likely. The risks of shipwrecks and catastrophic oil spill necessitate the use of the modern technologies to effectively protect the marine environment. In turn, such technologies require high-quality products of operational oceanography. Recently such products are the products of the MyOcean project. The development of the Black Sea operational oceanography made it possible to transfer of cost-efficient technologies to the region to create a new tool against oil pollution and for life-saving in case of a shipwreck. The Black Sea Track Web (BSTW) system of accidental oil spill evolution forecast in the Black Sea has been created in the framework of MONINFO project. The system is based on the Seatrack Web (STW) model developing by the consortium of the Baltic Sea countries. It is adapted to the configuration of the Black Sea observing system and is implemented to the regional contingency plans. The BSTW system consists of three parts: - forcing in the form of forecasted stratification, sea currents and wind fields, which is provided by the Black Sea MFC located at MHI in Sevastopol. The Black Sea MFC is the MyOcean regional marine forecasting center. It runs operationally and forms weather and ocean forecasts; - the oil drift model jointly developed by SMHI and the Royal Danish Administration of Navigation and Hydrography and which takes into account and adequately describes almost all physical processes affecting the oil spill; - the graphical user interface developed by SMHI and based on open source GIS-server technology. The developed BSTW system is available via the Internet, fully operational 24 hours a day and user friendly. It allows immediate access to the latest forecasts that drives the system. And in addition, it provides other floating objects and back tracking.

Energy management of a university campus utilizing short-term load forecasting with an artificial neural network

NASA Astrophysics Data System (ADS)

Palchak, David

Electrical load forecasting is a tool that has been utilized by distribution designers and operators as a means for resource planning and generation dispatch. The techniques employed in these predictions are proving useful in the growing market of consumer, or end-user, participation in electrical energy consumption. These predictions are based on exogenous variables, such as weather, and time variables, such as day of week and time of day as well as prior energy consumption patterns. The participation of the end-user is a cornerstone of the Smart Grid initiative presented in the Energy Independence and Security Act of 2007, and is being made possible by the emergence of enabling technologies such as advanced metering infrastructure. The optimal application of the data provided by an advanced metering infrastructure is the primary motivation for the work done in this thesis. The methodology for using this data in an energy management scheme that utilizes a short-term load forecast is presented. The objective of this research is to quantify opportunities for a range of energy management and operation cost savings of a university campus through the use of a forecasted daily electrical load profile. The proposed algorithm for short-term load forecasting is optimized for Colorado State University's main campus, and utilizes an artificial neural network that accepts weather and time variables as inputs. The performance of the predicted daily electrical load is evaluated using a number of error measurements that seek to quantify the best application of the forecast. The energy management presented utilizes historical electrical load data from the local service provider to optimize the time of day that electrical loads are being managed. Finally, the utilization of forecasts in the presented energy management scenario is evaluated based on cost and energy savings.

Integrating Satellite Measurements from Polar-orbiting instruments into Smoke Disperson Forecasts

NASA Astrophysics Data System (ADS)

Smith, N.; Pierce, R. B.; Barnet, C.; Gambacorta, A.; Davies, J. E.; Strabala, K.

2015-12-01

The IDEA-I (Infusion of Satellite Data into Environmental Applications-International) is a real-time system that currently generates trajectory-based forecasts of aerosol dispersion and stratospheric intrusions. Here we demonstrate new capabilities that use satellite measurements from the Joint Polar Satellite System (JPSS) Suomi-NPP (S-NPP) instruments (operational since 2012) in the generation of trajectory-based predictions of smoke dispersion from North American wildfires. Two such data products are used, namely the Visible Infrared Imaging Radiometer Suite (VIIRS) Aerosol Optical Depth (AOD) and the combined Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) NOAA-Unique CrIS-ATMS Processing System (NUCAPS) carbon monoxide (CO) retrievals. The latter is a new data product made possible by the release of full spectral-resolution CrIS measurements since December 2014. Once NUCAPS CO becomes operationally available it will be used in real-time applications such as IDEA-I along with VIIRS AOD and meteorological forecast fields to support National Weather Service (NWS) Incident Meteorologist (IMET) and air quality management decision making. By combining different measurements, the information content of the IDEA-I transport and dispersion forecast is improved within the complex terrain features that dominate the Western US and Alaska. The primary user community of smoke forecasts is the Western regions of the National Weather Service (NWS) and US Environmental Protection Agency (EPA) due to the significant impacts of wildfires in these regions. With this we demonstrate the quality of the smoke dispersion forecasts that can be achieved by integrating polar-orbiting satellite measurements with forecast models to enable on-site decision support services for fire incident management teams and other real-time air quality agencies.

Smart Irrigation From Soil Moisture Forecast Using Satellite And Hydro -Meteorological Modelling

NASA Astrophysics Data System (ADS)

Corbari, Chiara; Mancini, Marco; Ravazzani, Giovanni; Ceppi, Alessandro; Salerno, Raffaele; Sobrino, Josè

2017-04-01

Increased water demand and climate change impacts have recently enhanced the need to improve water resources management, even in those areas which traditionally have an abundant supply of water. The highest consumption of water is devoted to irrigation for agricultural production, and so it is in this area that efforts have to be focused to study possible interventions. The SIM project funded by EU in the framework of the WaterWorks2014 - Water Joint Programming Initiative aims at developing an operational tool for real-time forecast of crops irrigation water requirements to support parsimonious water management and to optimize irrigation scheduling providing real-time and forecasted soil moisture behavior at high spatial and temporal resolutions with forecast horizons from few up to thirty days. This study discusses advances in coupling satellite driven soil water balance model and meteorological forecast as support for precision irrigation use comparing different case studies in Italy, in the Netherlands, in China and Spain, characterized by different climatic conditions, water availability, crop types and irrigation techniques and water distribution rules. Herein, the applications in two operative farms in vegetables production in the South of Italy where semi-arid climatic conditions holds, two maize fields in Northern Italy in a more water reach environment with flood irrigation will be presented. This system combines state of the art mathematical models and new technologies for environmental monitoring, merging ground observed data with Earth observations. Discussion on the methodology approach is presented, comparing for a reanalysis periods the forecast system outputs with observed soil moisture and crop water needs proving the reliability of the forecasting system and its benefits. The real-time visualization of the implemented system is also presented through web-dashboards.

Use of JPSS ATMS, CrIS, and VIIRS data to Improve Tropical Cyclone Track and Intensity Forecasting

NASA Astrophysics Data System (ADS)

Chirokova, G.; Demaria, M.; DeMaria, R.; Knaff, J. A.; Dostalek, J.; Musgrave, K. D.; Beven, J. L.

2015-12-01

JPSS data provide unique information that could be critical for the forecasting of tropical cyclone (TC) track and intensity and is currently underutilized. Preliminary results from several TC applications using data from the Advanced Technology Microwave Sounder (ATMS), the Cross-Track Infrared Sounder (CrIS), and the Visible Infrared Imaging Radiometer Suite (VIIRS), carried by the Suomi National Polar-Orbiting Partnership satellite (SNPP), will be discussed. The first group of applications, which includes applications for moisture flux and for eye-detection, aims to improve rapid intensification (RI) forecasts, which is one of the highest priorities within NOAA. The applications could be used by forecasters directly and will also provide additional input to the Rapid Intensification Index (RII), the statistical-dynamical tool for forecasting RI events that is operational at the National Hurricane Center. The moisture flux application uses bias-corrected ATMS-MIRS (Microwave Integrated Retrieval System) and NUCAPS (NOAA Unique CrIS ATMS Processing System), retrievals that provide very accurate temperature and humidity soundings in the TC environment to detect dry air intrusions. The objective automated eye-detection application uses geostationary and VIIRS data in combination with machine learning and computer vision techniques for determining the onset of eye formation which is very important for TC intensity forecast but is usually determined by subjective methods. First version of the algorithm showed very promising results with a 75% success rate. The second group of applications develops tools to better utilize VIIRS data, including day-night band (DNB) imagery, for tropical cyclone forecasting. Disclaimer: The views, opinions, and findings contained in this article are those of the authors and should not be construed as an official National Oceanic and Atmospheric Administration (NOAA) or U.S. Government position, policy, or decision.

Forecast of geomagnetic storms using CME parameters and the WSA-ENLIL model

NASA Astrophysics Data System (ADS)

Moon, Y.; Lee, J.; Jang, S.; Na, H.; Lee, J.

2013-12-01

Intense geomagnetic storms are caused by coronal mass ejections (CMEs) from the Sun and their forecast is quite important in protecting space- and ground-based technological systems. The onset and strength of geomagnetic storms depend on the kinematic and magnetic properties of CMEs. Current forecast techniques mostly use solar wind in-situ measurements that provide only a short lead time. On the other hand, techniques using CME observations near the Sun have the potential to provide 1-3 days of lead time before the storm occurs. Therefore, one of the challenging issues is to forecast interplanetary magnetic field (IMF) southward components and hence geomagnetic storm strength with a lead-time on the order of 1-3 days. We are going to answer the following three questions: (1) when does a CME arrive at the Earth? (2) what is the probability that a CME can induce a geomagnetic storm? and (3) how strong is the storm? To address the first question, we forecast the arrival time and other physical parameters of CMEs at the Earth using the WSA-ENLIL model with three CME cone types. The second question is answered by examining the geoeffective and non-geoeffective CMEs depending on CME observations (speed, source location, earthward direction, magnetic field orientation, and cone-model output). The third question is addressed by examining the relationship between CME parameters and geomagnetic indices (or IMF southward component). The forecast method will be developed with a three-stage approach, which will make a prediction within four hours after the solar coronagraph data become available. We expect that this study will enable us to forecast the onset and strength of a geomagnetic storm a few days in advance using only CME parameters and the physics-based models.

Improving the Transition of Earth Satellite Observations from Research to Operations

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Lapenta, William M.; Jedlovec, Gary J.

2004-01-01

There are significant gaps between the observations, models, and decision support tools that make use of new data. These challenges include: 1) Decreasing the time to incorporate new satellite data into operational forecast assimilation systems, 2) Blending in-situ and satellite observing systems to produce the most accurate and comprehensive data products and assessments, 3) Accelerating the transition from research to applications through national test beds, field campaigns, and pilot demonstrations, and 4) Developing the partnerships and organizational structures to effectively transition new technology into operations. At the Short-term Prediction Research and Transition (SPORT) Center in Huntsville, Alabama, a NASA-NOAA-University collaboration has been developed to accelerate the infusion of NASA Earth science observations, data assimilation and modeling research into NWS forecast operations and decision-making. The SPoRT Center research focus is to improve forecasts through new observation capability and the regional prediction objectives of the US Weather Research Program dealing with 0-1 day forecast issues such as convective initiation and 24-hr quantitative precipitation forecasting. The near real-time availability of high-resolution experimental products of the atmosphere, land, and ocean from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Advanced Infrared Spectroradiometer (AIRS), and lightning mapping systems provide an opportunity for science and algorithm risk reduction, and for application assessment prior to planned observations from the next generation of operational low Earth orbiting and geostationary Earth orbiting satellites. This paper describes the process for the transition of experimental products into forecast operations, current products undergoing assessment by forecasters, and plans for the future. The SPoRT Web page is at (http://www.ghcc.msfc.nasa.gov/sport).

Forecast for the Future: Telecommunications.

ERIC Educational Resources Information Center

Sekaquaptewa, Sam; Yawakie, Madonna; Scheer, Roger; Yawakie, Mel

1999-01-01

Four telecommunications experts comment on changes in the industry and how these changes may result in career opportunities for American Indians. American Indian reservations have limited access to telecommunications and information technology and would benefit from the advocacy of Native professionals. (CDS)

Analysis of scanner data for crop inventories

NASA Technical Reports Server (NTRS)

Horvath, R. (Principal Investigator); Cicone, R.; Crist, E.; Kauth, R. J.; Pont, W.

1980-01-01

Classification and technology development for area estimation of corn, soybeans, wheat, barley, and sunflowers are outlined. Supporting research for corn and soybean foreign commodity production forecasting is highlighted. Graphs profiling the greenness and brightness of the crops are presented.

Evaluating Hydrological Response to Forecasted Land-Use Change

EPA Science Inventory

It is currently possible to measure landscape change over large areas and determine trends in environmental condition using advanced spacebourne technologies accompanied by geospatial analyses of the remotely sensed data. There are numerous earth-observing satellite platforms fo...

Framework for multi-resolution analyses of advanced traffic management strategies.

DOT National Transportation Integrated Search

2016-11-01

Demand forecasting models and simulation models have been developed, calibrated, and used in isolation of each other. However, the advancement of transportation system technologies and strategies, the increase in the availability of data, and the unc...

The use of dispersion modeling to determine the feasibility of vegetative environmental buffers (VEBS) at controlling odor dispersion

NASA Astrophysics Data System (ADS)

Weber, Eric E.

Concentrated animal feeding operations (CAFOs) have been experiencing increased resistance from surrounding residents making construction of new facilities or expansion of existing ones increasingly limited (Jacobson et al., 2002). Such concerns often include the impact of nuisance odor on peoples’ lives and on the environment (Huang and Miller, 2006). Vegetative environmental buffers (VEBs) have been suggested as a possible odor control technology. They have been found to impact odor plume dispersion and have shown the possibility of being an effective tool for odor abatement when used alone or in combination with other technologies (Lin et al., 2006). The main objective of this study was to use Gaussian-type dispersion modeling to determine the feasibility of use and the effectiveness of a VEB at controlling the spread of odor from a swine feeding operation. First, wind tunnel NH3 dispersion trends were compared to model generated dispersion trends to determine the accuracy of the model at handling VEB dispersion. Next, facility-scale (northern Missouri specific) model simulations with and without a VEB were run to determine its viability as an option for dispersion reduction. Finally, dispersion forecasts that integrated numerical weather forecasts were developed and compared to collected concentration data to determine forecast accuracy. The results of this study found that dispersion models can be used to simulate dispersion around a VEB. AERMOD-generated dispersion trends were found to follow similar patterns of decreasing downwind concentration to those of both wind tunnel simulations and previous research. This shows that a VEB can be incorporated into AERMOD and that the model can be used to determine its effectiveness as an odor control option. The results of this study also showed that a VEB has an effect on odor dispersion by reducing downwind concentrations. This was confirmed by both wind tunnel and AERMOD simulations of dispersion displaying decreased downwind concentrations from a control scenario. This shows that VEBs have the potential to act as an odor control option for CAFOs. This study also found that a forecast method that integrated numerical weather prediction into dispersion models could be developed to forecast areas of high concentration. Model-forecasted dispersion trends had a high spatial correlation with collected concentrations for days when the facility was emitting. This shows that dispersion models can accurately predict high concentration areas using forecasted weather data. The information provided by this study may ultimately prove useful for this particular facility and others and may help to lower tensions with surrounding residents.

Design and implementation of ticket price forecasting system

NASA Astrophysics Data System (ADS)

Li, Yuling; Li, Zhichao

2018-05-01

With the advent of the aviation travel industry, a large number of data mining technologies have been developed to increase profits for airlines in the past two decades. The implementation of the digital optimization strategy leads to price discrimination, for example, similar seats on the same flight are purchased at different prices, depending on the time of purchase, the supplier, and so on. Price fluctuations make the prediction of ticket prices have application value. In this paper, a combination of ARMA algorithm and random forest algorithm is proposed to predict the price of air ticket. The experimental results show that the model is more reliable by comparing the forecasting results with the actual results of each price model. The model is helpful for passengers to buy tickets and to save money. Based on the proposed model, using Python language and SQL Server database, we design and implement the ticket price forecasting system.

Analysing trends and forecasting malaria epidemics in Madagascar using a sentinel surveillance network: a web-based application.

PubMed

Girond, Florian; Randrianasolo, Laurence; Randriamampionona, Lea; Rakotomanana, Fanjasoa; Randrianarivelojosia, Milijaona; Ratsitorahina, Maherisoa; Brou, Télesphore Yao; Herbreteau, Vincent; Mangeas, Morgan; Zigiumugabe, Sixte; Hedje, Judith; Rogier, Christophe; Piola, Patrice

2017-02-13

The use of a malaria early warning system (MEWS) to trigger prompt public health interventions is a key step in adding value to the epidemiological data routinely collected by sentinel surveillance systems. This study describes a system using various epidemic thresholds and a forecasting component with the support of new technologies to improve the performance of a sentinel MEWS. Malaria-related data from 21 sentinel sites collected by Short Message Service are automatically analysed to detect malaria trends and malaria outbreak alerts with automated feedback reports. Roll Back Malaria partners can, through a user-friendly web-based tool, visualize potential outbreaks and generate a forecasting model. The system already demonstrated its ability to detect malaria outbreaks in Madagascar in 2014. This approach aims to maximize the usefulness of a sentinel surveillance system to predict and detect epidemics in limited-resource environments.

An abridged history of federal involvement in space weather forecasting

NASA Astrophysics Data System (ADS)

Caldwell, Becaja; McCarron, Eoin; Jonas, Seth

2017-10-01

Public awareness of space weather and its adverse effects on critical infrastructure systems, services, and technologies (e.g., the electric grid, telecommunications, and satellites) has grown through recent media coverage and scientific research. However, federal interest and involvement in space weather dates back to the decades between World War I and World War II when the National Bureau of Standards led efforts to observe, forecast, and provide warnings of space weather events that could interfere with high-frequency radio transmissions. The efforts to observe and predict space weather continued through the 1960s during the rise of the Cold War and into the present with U.S. government efforts to prepare the nation for space weather events. This paper provides a brief overview of the history of federal involvement in space weather forecasting from World War II, through the Apollo Program, and into the present.

Spatio-temporal pattern clustering for skill assessment of the Korea Operational Oceanographic System

NASA Astrophysics Data System (ADS)

Kim, J.; Park, K.

2016-12-01

In order to evaluate the performance of operational forecast models in the Korea operational oceanographic system (KOOS) which has been developed by Korea Institute of Ocean Science and Technology (KIOST), a skill assessment (SA) tool has developed and provided multiple skill metrics including not only correlation and error skills by comparing predictions and observation but also pattern clustering with numerical models, satellite, and observation. The KOOS has produced 72 hours forecast information on atmospheric and hydrodynamic forecast variables of wind, pressure, current, tide, wave, temperature, and salinity at every 12 hours per day produced by operating numerical models such as WRF, ROMS, MOM5, WW-III, and SWAN and the SA has conducted to evaluate the forecasts. We have been operationally operated several kinds of numerical models such as WRF, ROMS, MOM5, MOHID, WW-III. Quantitative assessment of operational ocean forecast model is very important to provide accurate ocean forecast information not only to general public but also to support ocean-related problems. In this work, we propose a method of pattern clustering using machine learning method and GIS-based spatial analytics to evaluate spatial distribution of numerical models and spatial observation data such as satellite and HF radar. For the clustering, we use 10 or 15 years-long reanalysis data which was computed by the KOOS, ECMWF, and HYCOM to make best matching clusters which are classified physical meaning with time variation and then we compare it with forecast data. Moreover, for evaluating current, we develop extraction method of dominant flow and apply it to hydrodynamic models and HF radar's sea surface current data. By applying pattern clustering method, it allows more accurate and effective assessment of ocean forecast models' performance by comparing not only specific observation positions which are determined by observation stations but also spatio-temporal distribution of whole model areas. We believe that our proposed method will be very useful to examine and evaluate large amount of numerical modeling data as well as satellite data.

Water and Power Systems Co-optimization under a High Performance Computing Framework

NASA Astrophysics Data System (ADS)

Xuan, Y.; Arumugam, S.; DeCarolis, J.; Mahinthakumar, K.

2016-12-01

Water and energy systems optimizations are traditionally being treated as two separate processes, despite their intrinsic interconnections (e.g., water is used for hydropower generation, and thermoelectric cooling requires a large amount of water withdrawal). Given the challenges of urbanization, technology uncertainty and resource constraints, and the imminent threat of climate change, a cyberinfrastructure is needed to facilitate and expedite research into the complex management of these two systems. To address these issues, we developed a High Performance Computing (HPC) framework for stochastic co-optimization of water and energy resources to inform water allocation and electricity demand. The project aims to improve conjunctive management of water and power systems under climate change by incorporating improved ensemble forecast models of streamflow and power demand. First, by downscaling and spatio-temporally disaggregating multimodel climate forecasts from General Circulation Models (GCMs), temperature and precipitation forecasts are obtained and input into multi-reservoir and power systems models. Extended from Optimus (Optimization Methods for Universal Simulators), the framework drives the multi-reservoir model and power system model, Temoa (Tools for Energy Model Optimization and Analysis), and uses Particle Swarm Optimization (PSO) algorithm to solve high dimensional stochastic problems. The utility of climate forecasts on the cost of water and power systems operations is assessed and quantified based on different forecast scenarios (i.e., no-forecast, multimodel forecast and perfect forecast). Analysis of risk management actions and renewable energy deployments will be investigated for the Catawba River basin, an area with adequate hydroclimate predicting skill and a critical basin with 11 reservoirs that supplies water and generates power for both North and South Carolina. Further research using this scalable decision supporting framework will provide understanding and elucidate the intricate and interdependent relationship between water and energy systems and enhance the security of these two critical public infrastructures.

Innovative technology for optical and infrared astronomy

NASA Astrophysics Data System (ADS)

Cunningham, Colin R.; Evans, Christopher J.; Molster, Frank; Kendrew, Sarah; Kenworthy, Matthew A.; Snik, Frans

2012-09-01

Advances in astronomy are often enabled by adoption of new technology. In some instances this is where the technology has been invented specifically for astronomy, but more usually it is adopted from another scientific or industrial area of application. The adoption of new technology typically occurs via one of two processes. The more usual is incremental progress by a series of small improvements, but occasionally this process is disruptive, where a new technology completely replaces an older one. One of the activities of the OPTICON Key Technology Network over the past few years has been a technology forecasting exercise. Here we report on a recent event which focused on the more radical, potentially disruptive technologies for ground-based, optical and infrared astronomy.

The alternative route: hanging out the unmentionables for better decision making in health information technology.

PubMed

Kibbe, David C; McLaughlin, Curtis P

2008-01-01

Expert panels and policy analysts have often ignored potential contributions to health information technology (IT) from the Internet and Web-based applications. Perhaps they are among the "unmentionables" of health IT. Ignoring those unmentionables and relying on established industry experts has left us with a standards process that is complex and burdened by diverse goals, easy for entrenched interests to dominate, and reluctant to deal with potentially disruptive technologies. We need a health IT planning process that is more dynamic in its technological forecasting and inclusive of IT experts from outside the industry.

Requirements for an Advanced Low Earth Orbit (LEO) Sounder (ALS) for Improved Regional Weather Prediction and Monitoring of Greenhouse Gases

NASA Technical Reports Server (NTRS)

Pagano, Thomas S.; Chahine, Moustafa T.; Susskind, Joel

2008-01-01

Hyperspectral infrared atmospheric sounders (e.g., the Atmospheric Infrared Sounder (AIRS) on Aqua and the Infrared Atmospheric Sounding Interferometer (IASI) on Met Op) provide highly accurate temperature and water vapor profiles in the lower to upper troposphere. These systems are vital operational components of our National Weather Prediction system and the AIRS has demonstrated over 6 hrs of forecast improvement on the 5 day operational forecast. Despite the success in the mid troposphere to lower stratosphere, a reduction in sensitivity and accuracy has been seen in these systems in the boundary layer over land. In this paper we demonstrate the potential improvement associated with higher spatial resolution (1 km vs currently 13.5 km) on the accuracy of boundary layer products with an added consequence of higher yield of cloud free scenes. This latter feature is related to the number of samples that can be assimilated and has also shown to have a significant impact on improving forecast accuracy. We also present a set of frequencies and resolutions that will improve vertical resolution of temperature and water vapor and trace gas species throughout the atmosphere. Development of an Advanced Low Earth Orbit (LEO) Sounder (ALS) with these improvements will improve weather forecast at the regional scale and of tropical storms and hurricanes. Improvements are also expected in the accuracy of the water vapor and cloud properties products, enhancing process studies and providing a better match to the resolution of future climate models. The improvements of technology required for the ALS are consistent with the current state of technology as demonstrated in NASA Instrument Incubator Program and NOAA's Hyperspectral Environmental Suite (HES) formulation phase development programs.

The potential economic benefits of improvements in weather forecasting

NASA Technical Reports Server (NTRS)

Thompson, J. C.

1972-01-01

The study was initiated as a consequence of the increased use of weather satellites, electronic computers and other technological developments which have become a virtual necessity for solving the complex problems of the earth's atmosphere. Neither the economic emphasis, nor the monetary results of the study, are intended to imply their sole use as criteria for making decisions concerning the intrinsic value of technological improvements in meteorology.

Automated Discovery and Modeling of Sequential Patterns Preceding Events of Interest

NASA Technical Reports Server (NTRS)

Rohloff, Kurt

2010-01-01

The integration of emerging data manipulation technologies has enabled a paradigm shift in practitioners' abilities to understand and anticipate events of interest in complex systems. Example events of interest include outbreaks of socio-political violence in nation-states. Rather than relying on human-centric modeling efforts that are limited by the availability of SMEs, automated data processing technologies has enabled the development of innovative automated complex system modeling and predictive analysis technologies. We introduce one such emerging modeling technology - the sequential pattern methodology. We have applied the sequential pattern methodology to automatically identify patterns of observed behavior that precede outbreaks of socio-political violence such as riots, rebellions and coups in nation-states. The sequential pattern methodology is a groundbreaking approach to automated complex system model discovery because it generates easily interpretable patterns based on direct observations of sampled factor data for a deeper understanding of societal behaviors that is tolerant of observation noise and missing data. The discovered patterns are simple to interpret and mimic human's identifications of observed trends in temporal data. Discovered patterns also provide an automated forecasting ability: we discuss an example of using discovered patterns coupled with a rich data environment to forecast various types of socio-political violence in nation-states.

Integrating Solar Power onto the Electric Grid - Bridging the Gap between Atmospheric Science, Engineering and Economics

NASA Astrophysics Data System (ADS)

Ghonima, M. S.; Yang, H.; Zhong, X.; Ozge, B.; Sahu, D. K.; Kim, C. K.; Babacan, O.; Hanna, R.; Kurtz, B.; Mejia, F. A.; Nguyen, A.; Urquhart, B.; Chow, C. W.; Mathiesen, P.; Bosch, J.; Wang, G.

2015-12-01

One of the main obstacles to high penetrations of solar power is the variable nature of solar power generation. To mitigate variability, grid operators have to schedule additional reliability resources, at considerable expense, to ensure that load requirements are met by generation. Thus despite the cost of solar PV decreasing, the cost of integrating solar power will increase as penetration of solar resources onto the electric grid increases. There are three principal tools currently available to mitigate variability impacts: (i) flexible generation, (ii) storage, either virtual (demand response) or physical devices and (iii) solar forecasting. Storage devices are a powerful tool capable of ensuring smooth power output from renewable resources. However, the high cost of storage is prohibitive and markets are still being designed to leverage their full potential and mitigate their limitation (e.g. empty storage). Solar forecasting provides valuable information on the daily net load profile and upcoming ramps (increasing or decreasing solar power output) thereby providing the grid advance warning to schedule ancillary generation more accurately, or curtail solar power output. In order to develop solar forecasting as a tool that can be utilized by the grid operators we identified two focus areas: (i) develop solar forecast technology and improve solar forecast accuracy and (ii) develop forecasts that can be incorporated within existing grid planning and operation infrastructure. The first issue required atmospheric science and engineering research, while the second required detailed knowledge of energy markets, and power engineering. Motivated by this background we will emphasize area (i) in this talk and provide an overview of recent advancements in solar forecasting especially in two areas: (a) Numerical modeling tools for coastal stratocumulus to improve scheduling in the day-ahead California energy market. (b) Development of a sky imager to provide short term forecasts (0-20 min ahead) to improve optimization and control of equipment on distribution feeders with high penetration of solar. Leveraging such tools that have seen extensive use in the atmospheric sciences supports the development of accurate physics-based solar forecast models. Directions for future research are also provided.

Snowfall Rate Retrieval Using Passive Microwave Measurements and Its Applications in Weather Forecast and Hydrology

NASA Technical Reports Server (NTRS)

Meng, Huan; Ferraro, Ralph; Kongoli, Cezar; Yan, Banghua; Zavodsky, Bradley; Zhao, Limin; Dong, Jun; Wang, Nai-Yu

2015-01-01

(AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow-on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has also been developed. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. It employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derives the probability of snowfall. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two-stream radiative transfer model. A method adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. The SFR products are being used mainly in two communities: hydrology and weather forecast. Global blended precipitation products traditionally do not include snowfall derived from satellites because such products were not available operationally in the past. The ATMS and AMSU/MHS SFR now provide the winter precipitation information for these blended precipitation products. Weather forecasters mainly rely on radar and station observations for snowfall forecast. The SFR products can fill in gaps where no conventional snowfall data are available to forecasters. The products can also be used to confirm radar and gauge snowfall data and increase forecasters' confidence in their prediction.

The Transition of NASA EOS Datasets to WFO Operations: A Model for Future Technology Transfer

NASA Technical Reports Server (NTRS)

Darden, C.; Burks, J.; Jedlovec, G.; Haines, S.

2007-01-01

The collocation of a National Weather Service (NWS) Forecast Office with atmospheric scientists from NASA/Marshall Space Flight Center (MSFC) in Huntsville, Alabama has afforded a unique opportunity for science sharing and technology transfer. Specifically, the NWS office in Huntsville has interacted closely with research scientists within the SPORT (Short-term Prediction and Research and Transition) Center at MSFC. One significant technology transfer that has reaped dividends is the transition of unique NASA EOS polar orbiting datasets into NWS field operations. NWS forecasters primarily rely on the AWIPS (Advanced Weather Information and Processing System) decision support system for their day to day forecast and warning decision making. Unfortunately, the transition of data from operational polar orbiters or low inclination orbiting satellites into AWIPS has been relatively slow due to a variety of reasons. The ability to integrate these high resolution NASA datasets into operations has yielded several benefits. The MODIS (MODerate-resolution Imaging Spectrometer ) instrument flying on the Aqua and Terra satellites provides a broad spectrum of multispectral observations at resolutions as fine as 250m. Forecasters routinely utilize these datasets to locate fine lines, boundaries, smoke plumes, locations of fog or haze fields, and other mesoscale features. In addition, these important datasets have been transitioned to other WFOs for a variety of local uses. For instance, WFO Great Falls Montana utilizes the MODIS snow cover product for hydrologic planning purposes while several coastal offices utilize the output from the MODIS and AMSR-E instruments to supplement observations in the data sparse regions of the Gulf of Mexico and western Atlantic. In the short term, these datasets have benefited local WFOs in a variety of ways. In the longer term, the process by which these unique datasets were successfully transitioned to operations will benefit the planning and implementation of products and datasets derived from both NPP and NPOESS. This presentation will provide a brief overview of current WFO usage of satellite data, the transition of datasets between SPORT and the N W S , and lessons learned for future transition efforts.

An Operational Perspective of Total Lightning Information

NASA Technical Reports Server (NTRS)

Nadler, David J.; Darden, Christopher B.; Stano, Geoffrey; Buechler, Dennis E.

2009-01-01

The close and productive collaborations between the NWS Warning and Forecast Office, the Short Term Prediction and Research Transition Center at NASA Marshall Space Flight Center and the University of Alabama in Huntsville have provided a unique opportunity for science sharing and technology transfer. One significant technology transfer that has provided immediate benefits to NWS forecast and warning operations is the use of data from the North Alabama Lightning Mapping Array. This network consists of ten VHF receivers deployed across northern Alabama and a base station located at the National Space Science and Technology Center. Preliminary investigations done at WFO Huntsville, along with other similar total lightning networks across the country, have shown distinct correlations between the time rate-of-change of total lightning and trends in intensity/severity of the parent convective cell. Since May 2003 when WFO HUN began receiving these data - in conjunction with other more traditional remotely sensed data (radar, satellite, and surface observations) -- have improved the situational awareness of the WFO staff. The use of total lightning information, either from current ground based systems or future space borne instrumentation, may substantially contribute to the NWS mission, by enhancing severe weather warning and decision-making processes. Operational use of the data has been maximized at WFO Huntsville through a process that includes forecaster training, product implementation, and post event analysis and assessments. Since receiving these data, over 50 surveys have been completed highlighting the use of total lightning information during significant events across the Tennessee Valley. In addition, around 150 specific cases of interest have been archived for collaborative post storm analysis. From these datasets, detailed trending information from radar and total lightning can be compared to corresponding damage reports. This presentation will emphasize the effective use of total lightning information in warning decision making along with best practices for implementation of new technologies into operations.

Medclic: the Mediterranean in one click

NASA Astrophysics Data System (ADS)

Troupin, Charles; Frontera, Biel; Sebastián, Kristian; Pau Beltran, Joan; Krietemeyer, Andreas; Gómara, Sonia; Gomila, Mikel; Escudier, Romain; Juza, Mélanie; Mourre, Baptiste; Garau, Angels; Cañellas, Tomeu; Tintoré, Joaquín

2016-04-01

"Medclic: the Mediterranean in one click" is a research and dissemination project focused on the scientific, technological and societal approaches of the Balearic Islands Coastal Observing and Forecasting System ({SOCIB}{www.socib.es}) in a collaboration with "la Caixa" Foundation. SOCIB aims at research excellence and the development of technology which enables progress toward the sustainable management of coastal and marine environments, providing solutions to meet the needs of society. Medclic goes one step forward and has two main goals: at the scientific level, to advance in establishing and understanding the mesoscale variability at the regional scale and its interaction, and thus improving the characterisation of the "oceanic weather" in the Mediterranean; at the outreach level: to bring SOCIB and the new paradigm of multi-platform observation in real time closer to society, through scientific outreach. SOCIB Data Centre is the core of the new multi-platform and real time oceanography and is responsible for directing the different stages of data management, ranging from data acquisition to its distribution and visualization through web applications. The system implemented relies on open source solutions and provides data in line with international standards and conventions (INSPIRE, netCDF Climate and Forecast, ldots). In addition, the Data Centre has implemented a REST web service, called Data Discovery. This service allows data generated by SOCIB to be integrated into applications developed by the Data Centre itself or by third parties, as it is the case with Medclic. Relying on this data distribution, the new web Medclic, www.medclic.es, constitutes an interactive scientific and educational area of communication that contributes to the rapprochement of the general public with the new marine and coastal observing technologies. Thanks to the Medclic web, data coming from new observing technologies in oceanography are available in real time and in one clic for all the society. Exploring different observing systems, knowing the temperature and swell forecasts, and discovering the importance of oceanographic research will be possible in a playful and interactive way.

Research challange

DOE Office of Scientific and Technical Information (OSTI.GOV)

Staebler, G.R.

The technological forecast can be used as a research tool by describing the optimum forest from every plausible viewpoint and then charting a course to create it. We must make usable the things we already know, and define, plan, and execute a research attack on those we don't. The three main areas we must consider are full use of the land, maximization of production, and research management and administration. In all these considerations we must keep in mind that technology creates the need for more technology, and that it is biologically necessary to preserve the long look.

R&D100: CO2 Memzyme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rempe, Susan; Brinker, Jeff; Jiang, Ying-Bing

2015-11-19

By combining a water droplet loaded with CO2 enzymes in an ultrathin nanopore on a flexible substrate, researchers at Sandia National Laboratories realized the first technology that meets and exceeds DOE targets for cost-effective CO2 capture. When compared with the nearest membrane competitor, this technology delivers a three times permeation rate, twenty times higher selectivity, and ten time lower fabrication cost. The CO2 Memzyme has the potential to remove 90% of CO2 emissions and is forecasted to save the U.S. coal industry $90 billion a year compared to conventional technology.

[Optimization of processing technology for semen cuscuta by uniform and regression analysis].

PubMed

Li, Chun-yu; Luo, Hui-yu; Wang, Shu; Zhai, Ya-nan; Tian, Shu-hui; Zhang, Dan-shen

2011-02-01

To optimize the best preparation technology for the contains of total flavornoids, polysaccharides, the percentage of water and alcohol-soluble components in Semen Cuscuta herb processing. UV-spectrophotometry was applied to determine the contains of total flavornoids and polysaccharides, which were extracted from Semen Cuscuta. And the processing was optimized by the way of uniform design and contour map. The best preparation technology was satisfied with some conditions as follows: baking temperature 150 degrees C, baking time 140 seconds. The regression models are notable and reasonable, which can forecast results precisely.

R&D100: CO2 Memzyme

ScienceCinema

Rempe, Susan; Brinker, Jeff; Jiang, Ying-Bing; Vanegas, Juan

2018-06-25

By combining a water droplet loaded with CO2 enzymes in an ultrathin nanopore on a flexible substrate, researchers at Sandia National Laboratories realized the first technology that meets and exceeds DOE targets for cost-effective CO2 capture. When compared with the nearest membrane competitor, this technology delivers a three times permeation rate, twenty times higher selectivity, and ten time lower fabrication cost. The CO2 Memzyme has the potential to remove 90% of CO2 emissions and is forecasted to save the U.S. coal industry $90 billion a year compared to conventional technology.

Current and Potential Use of Technology Forecasting Tools in the Federal Government

DTIC Science & Technology

2016-03-01

that is near or at the point of late-stage trials. This could allow for earlier research investment in useful health care technologies or innovations ...pursuant to the copyright license under the clause at DFARS 252.227-7013 (a)(16) [Jun 2013]. I N S T I T U T E F O R D E F E N S E A N A L Y S E S IDA...long-term technology investments , and • Understanding economic and policy implications of the evolution and global availability of commercial

Impact Assessment and Forecasts of Information and Telecommunications Technologies Applied to Education and Training. R&D in Information and Communication Based Learning Technology. Analysis of Key Issues for the Orientation of the Work of Sector Actors in the Framework of DELTA. Volume I--Executive Summary.

ERIC Educational Resources Information Center

Commission of the European Communities, Brussels (Belgium).

This report, the first volume in a three volume set, summarizes the results of a study performed by the DELTA (Developing European Learning through Technological Advance) Unit in parallel with the projects underway in the research and development Exploratory Action. The report identifies the key issues, associated requirements and options, and…

NASA Space Technology Draft Roadmap Area 13: Ground and Launch Systems Processing

NASA Technical Reports Server (NTRS)

Clements, Greg

2011-01-01

This slide presentation reviews the technology development roadmap for the area of ground and launch systems processing. The scope of this technology area includes: (1) Assembly, integration, and processing of the launch vehicle, spacecraft, and payload hardware (2) Supply chain management (3) Transportation of hardware to the launch site (4) Transportation to and operations at the launch pad (5) Launch processing infrastructure and its ability to support future operations (6) Range, personnel, and facility safety capabilities (7) Launch and landing weather (8) Environmental impact mitigations for ground and launch operations (9) Launch control center operations and infrastructure (10) Mission integration and planning (11) Mission training for both ground and flight crew personnel (12) Mission control center operations and infrastructure (13) Telemetry and command processing and archiving (14) Recovery operations for flight crews, flight hardware, and returned samples. This technology roadmap also identifies ground, launch and mission technologies that will: (1) Dramatically transform future space operations, with significant improvement in life-cycle costs (2) Improve the quality of life on earth, while exploring in co-existence with the environment (3) Increase reliability and mission availability using low/zero maintenance materials and systems, comprehensive capabilities to ascertain and forecast system health/configuration, data integration, and the use of advanced/expert software systems (4) Enhance methods to assess safety and mission risk posture, which would allow for timely and better decision making. Several key technologies are identified, with a couple of slides devoted to one of these technologies (i.e., corrosion detection and prevention). Development of these technologies can enhance life on earth and have a major impact on how we can access space, eventually making routine commercial space access and improve building and manufacturing, and weather forecasting for example for the effect of these process improvements on our daily lives.

A Global Approach to Engineering

ERIC Educational Resources Information Center

Carlson, Scott

2007-01-01

As American manufacturing moves increasingly overseas and immense growth is forecast in modernizing countries like India and China, engineers need to understand those cultures before designing products for them, say supporters of international-engineering programs. The Accreditation Board for Engineering and Technology (ABET), which accredits…

Mesoscale weather forecasting : technological and institutional challenges July 16, 1996 summary of proceedings

DOT National Transportation Integrated Search

1996-08-31

On October 26-27, 1995, over two hundred transportation leaders and decision-makers from around the nation convened in Cambridge, Massachusetts to participate in a two day symposium on "Challenges and Opportunities for Global Transportation in the 21...

3 CFR 8986 - Proclamation 8986 of May 24, 2013. National Hurricane Preparedness Week, 2013

Code of Federal Regulations, 2014 CFR

2014-01-01

... forecasting with the latest science and technology. And in the months and years ahead, we will continue to... lives and protect communities. IN WITNESS WHEREOF, I have hereunto set my hand this twenty-fourth day of...

Forecasting system predicts presence of sea nettles in Chesapeake Bay

NASA Astrophysics Data System (ADS)

Brown, Christopher W.; Hood, Raleigh R.; Li, Zhen; Decker, Mary Beth; Gross, Thomas F.; Purcell, Jennifer E.; Wang, Harry V.

Outbreaks of noxious biota, which occur in both aquatic and terrestrial systems, can have considerable negative economic impacts. For example, an increasing frequency of harmful algal blooms worldwide has negatively affected the tourism industry in many regions. Such impacts could be mitigated if the conditions that give rise to these outbreaks were known and could be monitored. Recent advances in technology and communications allow us to continuously measure and model many environmental factors that are responsible for outbreaks of certain noxious organisms. A new prototype ecological forecasting system predicts the likelihood of occurrence of the sea nettle (Chrysaora quinquecirrha), a stinging jellyfish, in the Chesapeake Bay.

NASA Lewis Research Center Futuring Workshop

NASA Technical Reports Server (NTRS)

Boroush, Mark; Stover, John; Thomas, Charles

1987-01-01

On October 21 and 22, 1986, the Futures Group ran a two-day Futuring Workshop on the premises of NASA Lewis Research Center. The workshop had four main goals: to acquaint participants with the general history of technology forecasting; to familiarize participants with the range of forecasting methodologies; to acquaint participants with the range of applicability, strengths, and limitations of each method; and to offer participants some hands-on experience by working through both judgmental and quantitative case studies. Among the topics addressed during this workshop were: information sources; judgmental techniques; quantitative techniques; merger of judgment with quantitative measurement; data collection methods; and dealing with uncertainty.

Biospheric Monitoring and Ecological Forecasting using EOS/MODIS data, ecosystem modeling, planning and scheduling technologies

NASA Astrophysics Data System (ADS)

Nemani, R. R.; Votava, P.; Golden, K.; Hashimoto, H.; Jolly, M.; White, M.; Running, S.; Coughlan, J.

2003-12-01

The latest generation of NASA Earth Observing System satellites has brought a new dimension to continuous monitoring of the living part of the Earth System, the Biosphere. EOS data can now provide weekly global measures of vegetation productivity and ocean chlorophyll, and many related biophysical factors such as land cover changes or snowmelt rates. However, information with the highest economic value would be forecasting impending conditions of the biosphere that would allow advanced decision-making to mitigate dangers, or exploit positive trends. We have developed a software system called the Terrestrial Observation and Prediction System (TOPS) to facilitate rapid analysis of ecosystem states/functions by integrating EOS data with ecosystem models, surface weather observations and weather/climate forecasts. Land products from MODIS (Moderate Resolution Imaging Spectroradiometer) including land cover, albedo, snow, surface temperature, leaf area index are ingested into TOPS for parameterization of models and for verifying model outputs such as snow cover and vegetation phenology. TOPS is programmed to gather data from observing networks such as USDA soil moisture, AMERIFLUX, SNOWTEL to further enhance model predictions. Key technologies enabling TOPS implementation include the ability to understand and process heterogeneous-distributed data sets, automated planning and execution of ecosystem models, causation analysis for understanding model outputs. Current TOPS implementations at local (vineyard) to global scales (global net primary production) can be found at http://www.ntsg.umt.edu/tops.

Operational Space Weather Activities in the US

NASA Astrophysics Data System (ADS)

Berger, Thomas; Singer, Howard; Onsager, Terrance; Viereck, Rodney; Murtagh, William; Rutledge, Robert

2016-07-01

We review the current activities in the civil operational space weather forecasting enterprise of the United States. The NOAA/Space Weather Prediction Center is the nation's official source of space weather watches, warnings, and alerts, working with partners in the Air Force as well as international operational forecast services to provide predictions, data, and products on a large variety of space weather phenomena and impacts. In October 2015, the White House Office of Science and Technology Policy released the National Space Weather Strategy (NSWS) and associated Space Weather Action Plan (SWAP) that define how the nation will better forecast, mitigate, and respond to an extreme space weather event. The SWAP defines actions involving multiple federal agencies and mandates coordination and collaboration with academia, the private sector, and international bodies to, among other things, develop and sustain an operational space weather observing system; develop and deploy new models of space weather impacts to critical infrastructure systems; define new mechanisms for the transition of research models to operations and to ensure that the research community is supported for, and has access to, operational model upgrade paths; and to enhance fundamental understanding of space weather through support of research models and observations. The SWAP will guide significant aspects of space weather operational and research activities for the next decade, with opportunities to revisit the strategy in the coming years through the auspices of the National Science and Technology Council.

Life cycle assessment of forecasting scenarios for urban water management: A first implementation of the WaLA model on Paris suburban area.

PubMed

Loubet, Philippe; Roux, Philippe; Guérin-Schneider, Laetitia; Bellon-Maurel, Véronique

2016-03-01

A framework and an associated modeling tool to perform life cycle assessment (LCA) of urban water system, namely the WaLA model, has been recently developed. In this paper, the WaLA model is applied to a real case study: the urban water system of the Paris suburban area, in France. It aims to verify the capacity of the model to provide environmental insights to stakeholder's issues related to future trends influencing the system (e.g., evolution of water demand, increasing water scarcity) or policy responses (e.g., choices of water resources and technologies). This is achieved by evaluating a baseline scenario for 2012 and several forecasting scenarios for 2022 and 2050. The scenarios are designed through the modeling tool WaLA, which is implemented in Simulink/Matlab: it combines components representing the different technologies, users and resources of the UWS. The life cycle inventories of the technologies and users components include water quantity and quality changes, specific operation (electricity, chemicals) and infrastructures data (construction materials). The methods selected for the LCIA are midpoint ILCD, midpoint water deprivation impacts at the sub-river basin scale, and endpoint Impact 2002+. The results of the baseline scenario show that wastewater treatment plants have the highest impacts compared to drinking water production and distribution, as traditionally encountered in LCA of UWS. The results of the forecasting scenarios show important changes in water deprivation impacts due to water management choices or effects of climate change. They also enable to identify tradeoffs with other impact categories and to compare several scenarios. It suggests the capacity of the model to deliver information for decision making about future policies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Selected Technical Spin Offs from the Space Program

NASA Technical Reports Server (NTRS)

Gilmore, H. L.

1970-01-01

The report describes some of the problems which the National Aeronautics and Space Administration has encountered in getting people to understand how the general public has profited from the technical discoveries of the space program. Next, it describes NASA's Technology Utilization Program and comments on it. It then describes some of the many spin-offs from the space program. These include examples from management technology, communications, aeronautics, medicine, fabrics highway safety, and weather forecasting.

Technology Assessment: 1983 Forecast of Future Test Technology Requirements.

DTIC Science & Technology

1983-06-01

effectively utilizes existing vehicle space , power and support equipment while maintaining critical interfaces with on-board computers and fire control...Scan Converter EAR Electronically Agile Radar E-O Electro-Optics FET Field Effect Transistor FLIR Forward Looking Infrared GaAs Gallium Arsenide HEL...They might be a part of a large ATE system due to such things as the environmental effects on noise and signal/power loss. A summary of meaningful

Logical Design of a Decision Support System to Forecast Technology, Prices and Costs for the National Communications System.

DTIC Science & Technology

1984-09-01

IN SOFTWARE DESIGN ......... .................... 39 P. PROCESS DESCRIPTIONS 43.............3 1. Model Euilding .............. 43 2. M1odel Management ... manager to model a wide variety of technology, price and cost situations without the associated overhead imposed by multiple application-specific systems...The Manager of the National Communications System (NCS) has been tasked by the National Security Telecommunications Policy of 3 August 1983 with

Calls Forecast for the Moscow Ambulance Service. The Impact of Weather Forecast

NASA Astrophysics Data System (ADS)

Gordin, Vladimir; Bykov, Philipp

2015-04-01

We use the known statistics of the calls for the current and previous days to predict them for tomorrow and for the following days. We assume that this algorithm will work operatively, will cyclically update the available information and will move the horizon of the forecast. Sure, the accuracy of such forecasts depends on their lead time, and from a choice of some group of diagnoses. For comparison we used the error of the inertial forecast (tomorrow there will be the same number of calls as today). Our technology has demonstrated accuracy that is approximately two times better compared to the inertial forecast. We obtained the following result: the number of calls depends on the actual weather in the city as well as on its rate of change. We were interested in the accuracy of the forecast for 12-hour sum of the calls in real situations. We evaluate the impact of the meteorological errors [1] on the forecast errors of the number of Ambulance calls. The weather and the Ambulance calls number both have seasonal tendencies. Therefore, if we have medical information from one city only, we should separate the impacts of such predictors as "annual variations in the number of calls" and "weather". We need to consider the seasonal tendencies (associated, e. g. with the seasonal migration of the population) and the impact of the air temperature simultaneously, rather than sequentially. We forecasted separately the number of calls with diagnoses of cardiovascular group, where it was demonstrated the advantage of the forecasting method, when we use the maximum daily air temperature as a predictor. We have a chance to evaluate statistically the influence of meteorological factors on the dynamics of medical problems. In some cases it may be useful for understanding of the physiology of disease and possible treatment options. We can assimilate some personal archives of medical parameters for the individuals with concrete diseases and the relative meteorological archive. As a result we hope to evaluate how weather can influence the intensity of the disease. Thus, the knowledge of the weather forecast for several days will help us to predict a state of health. The person will be able to take some proactive actions to avoid the anticipated worsening of his health. Literature 1. A. N. Bagrov, F. L. Bykov, V. A. Gordin. Complex Forecast of Surface Meteorological Parameters. Meteorology and Hydrology, 2014, N 5, 5-16 (Russian), 283-291 (English). 2. Bykov, Ph.L., Gordin, V.A., Objective Analysis of the Structure of Three-Dimensional Atmospheric Fronts. Izvestia of Russian Academy of Sciences. Ser. The Physics of Atmosphere and Ocean, 48 (2) (2012), 172-188 (Russian), 152-168 (English), http://dx.doi.org/10.1134/S0001433812020053 3. V.A.Gordin. Mathematical Problems and Methods in Hydrodynamical Weather Forecasting. Amsterdam etc.: Gordon & Breach Publ. House, 2000. 4. V.A.Gordin. Mathematics, Computer, Weather Forecasting, and Other Mathematical Physics' Scenarios. Moscow, Fizmatlit, 2010, 2012 (Russian).

A Real-time 3D Visualization of Global MHD Simulation for Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Murata, K.; Matsuoka, D.; Kubo, T.; Shimazu, H.; Tanaka, T.; Fujita, S.; Watari, S.; Miyachi, H.; Yamamoto, K.; Kimura, E.; Ishikura, S.

2006-12-01

Recently, many satellites for communication networks and scientific observation are launched in the vicinity of the Earth (geo-space). The electromagnetic (EM) environments around the spacecraft are always influenced by the solar wind blowing from the Sun and induced electromagnetic fields. They occasionally cause various troubles or damages, such as electrification and interference, to the spacecraft. It is important to forecast the geo-space EM environment as well as the ground weather forecasting. Owing to the recent remarkable progresses of super-computer technologies, numerical simulations have become powerful research methods in the solar-terrestrial physics. For the necessity of space weather forecasting, NICT (National Institute of Information and Communications Technology) has developed a real-time global MHD simulation system of solar wind-magnetosphere-ionosphere couplings, which has been performed on a super-computer SX-6. The real-time solar wind parameters from the ACE spacecraft at every one minute are adopted as boundary conditions for the simulation. Simulation results (2-D plots) are updated every 1 minute on a NICT website. However, 3D visualization of simulation results is indispensable to forecast space weather more accurately. In the present study, we develop a real-time 3D webcite for the global MHD simulations. The 3-D visualization results of simulation results are updated every 20 minutes in the following three formats: (1)Streamlines of magnetic field lines, (2)Isosurface of temperature in the magnetosphere and (3)Isoline of conductivity and orthogonal plane of potential in the ionosphere. For the present study, we developed a 3-D viewer application working on Internet Explorer browser (ActiveX) is implemented, which was developed on the AVS/Express. Numerical data are saved in the HDF5 format data files every 1 minute. Users can easily search, retrieve and plot past simulation results (3D visualization data and numerical data) by using the STARS (Solar-terrestrial data Analysis and Reference System). The STARS is a data analysis system for satellite and ground-based observation data for solar-terrestrial physics.

STEM Vocational Socialization and Career Development in Middle Schools

ERIC Educational Resources Information Center

Kendall, Katherine A.

2017-01-01

Economic forecasts predict an unprecedented shortage of STEM workers in the United States. This study examined the vocational anticipatory socialization factors and classroom stratagems influencing middle school students' science, technology, engineering and mathematics (STEM) career development. Student attitudes towards STEM content areas and…

Small Business Programs: Benefits, Barriers, Bridges and Critical Success Factors

DTIC Science & Technology

2009-05-01

Decreased product development time cycles • Product, process and technology innovation • Joint marketing and advertising • Access to new markets or...Increased Joint Marketing and Advertising Yuva (2005) Increased Penetration into New Markets Yuva (2005); Terrill (2007) Improved Forecasting and Response

What Can Computer Technology Offer Special Education Administrators?

ERIC Educational Resources Information Center

Case, Elizabeth J.; And Others

The paper provides an overview of fundamental uses of the microcomputer by special education administrators in a large-city school district. Microcomputer applications are suggested for the following applications: school-level administrative functions (e.g., tracking equipment repair, budget forecasting, and class scheduling); district-wide…

Examining the Role of Metadata in Testing IED Detection Systems

DTIC Science & Technology

2009-09-01

energy management, crop assessment, weather forecasting, disaster alerts, and endangered species assessment [ Biagioni and Bridges 2002; Main- waring et...accessed June 10, 2008). Biagioni , E. and K. Bridges. 2002. The application of remote sensor technology to assist the recovery of rare endangered species

75 FR 51751 - Proposed Information Collection; Comment Request; User Engagement Survey for Water Resources...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-23

... techniques or other forms of information technology. Comments submitted in response to this notice will be... DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration Proposed Information Collection; Comment Request; User Engagement Survey for Water Resources Forecasts and Climate Information...

Molecular electronics: The technology of sixth generation computers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jarvis, M.T.; Miller, R.K.

1987-01-01

In February 1986, Japan began the 6th Generation project. At the 1987 Economic Summit in Venice, Prime Minister Yashuhiro Makasone opened the project to world collaboration. A project director suggests that the 6th Generation ''may just be a turning point for human society.'' The major rationale for building molecular electronic devices is to achieve advances in computational densities and speeds. Proposed chromophore chains for molecular-scale chips, for example, could be spaced closer than today's silicone elements by a factor of almost 100. This book describes the research and proposed designs for molecular electronic devices and computers. It examines specific potentialmore » applications and the relationship to molecular electronics to silicon technology and presents the first published survey of experts on research issues, applications, and forecast of future developments and also includes market forecast. An interesting suggestion of the survey is that the chemical industry may become a significant factor in the computer industry as the sixth generation unfolds.« less

Utilization of GIS/GPS-Based Information Technology in Commercial Crop Decision Making in California, Washington, Oregon, Idaho, and Arizona

PubMed Central

Thomas, C. S.; Skinner, P. W.; Fox, A. D.; Greer, C. A.; Gubler, W. D.

2002-01-01

Ground-based weather, plant-stage measurements, and remote imagery were geo-referenced in geographic information system (GIS) software using an integrated approach to determine insect and disease risk and crop cultural requirements. Weather forecasts and disease weather forecasts for agricultural areas were constructed with elevation, weather, and satellite data. Models for 6 insect pests and 12 diseases of various crops were calculated and presented daily in georeferenced maps for agricultural areas in northern California and Washington. Grape harvest dates and yields also were predicted with high accuracy. The data generated from the GIS global positioning system (GPS) analyses were used to make management decisions over a large number of acres in California, Washington, Oregon, Idaho, and Arizona. Information was distributed daily over the Internet as regional weather, insect, and disease risk maps as industry-sponsored or subscription-based products. Use of GIS/GPS technology for semi-automated data analysis is discussed. PMID:19265934

e-Business Innovation: The Next Decade

NASA Astrophysics Data System (ADS)

Marca, David A.

Innovation is invention or application of technologies or theories that radically alters business and the economy. For many years, innovation and the economy have been locked in 80-year cycles, which might imply that innovation is an economic driver, and vice versa. Based on this, some forecast that innovation and the economy might decrease sharply due to several forces: a) decreasing economic growth, b) increasing demand for custom services, c) more entrepreneurial work environments, and d) urban and environmental degradation. Should such forecasts hold true, business may need to alter its offerings, operations and organization to survive. Such a scenario may also require applied e-Business innovation by combining existing internet, wireless, broadband, and video technologies. One possible result: flexible front offices integrated with efficient back offices. Such an e-Business could comprise: a) a customer-based and transaction-based organization, b) functions for adaptive offerings that anticipate need, c) highly responsive, real-time, operations having no inventory, and d) value-based front-end, and automated back-end, decision making.

Paradigm change in ocean studies: multi-platform observing and forecasting integrated approach in response to science and society needs

NASA Astrophysics Data System (ADS)

Tintoré, Joaquín

2017-04-01

The last 20 years of ocean research have allowed a description of the state of the large-scale ocean circulation. However, it is also well known that there is no such thing as an ocean state and that the ocean varies a wide range of spatial and temporal scales. More recently, in the last 10 years, new monitoring and modelling technologies have emerged allowing quasi real time observation and forecasting of the ocean at regional and local scales. Theses new technologies are key components of recent observing & forecasting systems being progressively implemented in many regional seas and coastal areas of the world oceans. As a result, new capabilities to characterise the ocean state and more important, its variability at small spatial and temporal scales, exists today in many cases in quasi-real time. Examples of relevance for society can be cited, among others our capabilities to detect and understand long-term climatic changes and also our capabilities to better constrain our forecasting capabilities of the coastal ocean circulation at temporal scales from sub-seasonal to inter-annual and spatial from regional to meso and submesoscale. The Mediterranean Sea is a well-known laboratory ocean where meso and submesoscale features can be ideally observed and studied as shown by the key contributions from projects such as Perseus, CMEMS, Jericonext, among others. The challenge for the next 10 years is the integration of theses technologies and multiplatform observing and forecasting systems to (a) monitor the variability at small scales mesoscale/weeks) in order (b) to resolve the sub-basin/seasonal and inter-annual variability and by this (c) establish the decadal variability, understand the associated biases and correct them. In other words, the new observing systems now allow a major change in our focus of ocean observation, now from small to large scales. Recent studies from SOCIB -www.socib.es- have shown the importance of this new small to large-scale multi-platform approach in ocean observation. Three examples from the integration capabilities of SOCIB facilities will be presented and discussed. First the quasi-continuous high frequency glider monitoring of the Ibiza Channel since 2011, an important biodiversity hot spot and a 'choke' point in the Western Mediterranean circulation, has allowed us to reveal a high frequency variability in the North-South exchanges, with very significant changes (0.8 - 0.9 Sv) occurring over periods of days to week of the same order as the previously known seasonal cycle. HF radar data and model results have also contributed more recently to better describe and understand the variability at small scales. Second, the Alborex/Perseus project multi-platform experiment (e.g., RV catamaran, 2 gliders, 25 drifters, 3 Argo type profilers & satellite data) that focused on submesoscale processes and ecosystem response and carried out in the Alborán Sea in May 2014. Glider results showed significant chlorophyll subduction in areas adjacent to the steep density front with patterns related to vertical motion. Initial dynamical interpretations will be presented. Third and final, I will discuss the key relevance of the data centre to guarantee data interoperability, quality control, availability and distribution for this new approach to ocean observation and forecasting to be really efficient in responding to key scientific state of the art priorities, enhancing technology development and responding to society needs.

A study on the utilization of advanced composites in commercial aircraft wing structure

NASA Technical Reports Server (NTRS)

Watts, D. J.

1978-01-01

A study was conducted to define the technology and data needed to support the introduction of advanced composite materials in the wing structure of future production aircraft. The study accomplished the following: (1) definition of acceptance factors, (2) identification of technology issues, (3) evaluation of six candidate wing structures, (4) evaluation of five program options, (5) definition of a composite wing technology development plan, (6) identification of full-scale tests, (7) estimation of program costs for the total development plan, (8) forecast of future utilization of composites in commercial transport aircraft and (9) identification of critical technologies for timely program planning.

Research in space commercialization, technology transfer, and communications

NASA Technical Reports Server (NTRS)

1982-01-01

Research and internship programs in technology transfer, space commercialization, and information and communications policy are described. The intern's activities are reviewed. On-campus research involved work on the costs of conventional telephone technology in rural areas, an investigation of the lag between the start of a research and development project and the development of new technology, using NASA patent and patent waiver data, studies of the financial impact and economic prospects of a space operation center, a study of the accuracy of expert forecasts of uncertain quantities and a report on frequency coordination in the fixed and fixed satellite services at 4 and 6 GHz.

Development of Hydrometeorological Monitoring and Forecasting as AN Essential Component of the Early Flood Warning System:

NASA Astrophysics Data System (ADS)

Manukalo, V.

2012-12-01

Defining issue The river inundations are the most common and destructive natural hazards in Ukraine. Among non-structural flood management and protection measures a creation of the Early Flood Warning System is extremely important to be able to timely recognize dangerous situations in the flood-prone areas. Hydrometeorological information and forecasts are a core importance in this system. The primary factors affecting reliability and a lead - time of forecasts include: accuracy, speed and reliability with which real - time data are collected. The existing individual conception of monitoring and forecasting resulted in a need in reconsideration of the concept of integrated monitoring and forecasting approach - from "sensors to database and forecasters". Result presentation The Project: "Development of Flood Monitoring and Forecasting in the Ukrainian part of the Dniester River Basin" is presented. The project is developed by the Ukrainian Hydrometeorological Service in a conjunction with the Water Management Agency and the Energy Company "Ukrhydroenergo". The implementation of the Project is funded by the Ukrainian Government and the World Bank. The author is nominated as the responsible person for coordination of activity of organizations involved in the Project. The term of the Project implementation: 2012 - 2014. The principal objectives of the Project are: a) designing integrated automatic hydrometeorological measurement network (including using remote sensing technologies); b) hydrometeorological GIS database construction and coupling with electronic maps for flood risk assessment; c) interface-construction classic numerical database -GIS and with satellite images, and radar data collection; d) providing the real-time data dissemination from observation points to forecasting centers; e) developing hydrometeoroogical forecasting methods; f) providing a flood hazards risk assessment for different temporal and spatial scales; g) providing a dissemination of current information, forecasts and warnings to consumers automatically. Besides scientific and technical issues the implementation of these objectives requires solution of a number of organizational issues. Thus, as a result of the increased complexity of types of hydrometeorological data and in order to develop forecasting methods, a reconsideration of meteorological and hydrological measurement networks should be carried out. The "optimal density of measuring networks" is proposed taking into account principal terms: a) minimizing an uncertainty in characterizing the spacial distribution of hydrometeorological parameters; b) minimizing the Total Life Cycle Cost of creation and maintenance of measurement networks. Much attention will be given to training Ukrainian disaster management authorities from the Ministry of Emergencies and the Water Management Agency to identify the flood hazard risk level and to indicate the best protection measures on the basis of continuous monitoring and forecasts of evolution of meteorological and hydrological conditions in the river basin.

How to Improve Fault Tolerance in Disaster Predictions: A Case Study about Flash Floods Using IoT, ML and Real Data.

PubMed

Furquim, Gustavo; Filho, Geraldo P R; Jalali, Roozbeh; Pessin, Gustavo; Pazzi, Richard W; Ueyama, Jó

2018-03-19

The rise in the number and intensity of natural disasters is a serious problem that affects the whole world. The consequences of these disasters are significantly worse when they occur in urban districts because of the casualties and extent of the damage to goods and property that is caused. Until now feasible methods of dealing with this have included the use of wireless sensor networks (WSNs) for data collection and machine-learning (ML) techniques for forecasting natural disasters. However, there have recently been some promising new innovations in technology which have supplemented the task of monitoring the environment and carrying out the forecasting. One of these schemes involves adopting IP-based (Internet Protocol) sensor networks, by using emerging patterns for IoT. In light of this, in this study, an attempt has been made to set out and describe the results achieved by SENDI (System for dEtecting and forecasting Natural Disasters based on IoT). SENDI is a fault-tolerant system based on IoT, ML and WSN for the detection and forecasting of natural disasters and the issuing of alerts. The system was modeled by means of ns-3 and data collected by a real-world WSN installed in the town of São Carlos - Brazil, which carries out the data collection from rivers in the region. The fault-tolerance is embedded in the system by anticipating the risk of communication breakdowns and the destruction of the nodes during disasters. It operates by adding intelligence to the nodes to carry out the data distribution and forecasting, even in extreme situations. A case study is also included for flash flood forecasting and this makes use of the ns-3 SENDI model and data collected by WSN.

Development of Ensemble Model Based Water Demand Forecasting Model

NASA Astrophysics Data System (ADS)

Kwon, Hyun-Han; So, Byung-Jin; Kim, Seong-Hyeon; Kim, Byung-Seop

2014-05-01

In recent years, Smart Water Grid (SWG) concept has globally emerged over the last decade and also gained significant recognition in South Korea. Especially, there has been growing interest in water demand forecast and optimal pump operation and this has led to various studies regarding energy saving and improvement of water supply reliability. Existing water demand forecasting models are categorized into two groups in view of modeling and predicting their behavior in time series. One is to consider embedded patterns such as seasonality, periodicity and trends, and the other one is an autoregressive model that is using short memory Markovian processes (Emmanuel et al., 2012). The main disadvantage of the abovementioned model is that there is a limit to predictability of water demands of about sub-daily scale because the system is nonlinear. In this regard, this study aims to develop a nonlinear ensemble model for hourly water demand forecasting which allow us to estimate uncertainties across different model classes. The proposed model is consist of two parts. One is a multi-model scheme that is based on combination of independent prediction model. The other one is a cross validation scheme named Bagging approach introduced by Brieman (1996) to derive weighting factors corresponding to individual models. Individual forecasting models that used in this study are linear regression analysis model, polynomial regression, multivariate adaptive regression splines(MARS), SVM(support vector machine). The concepts are demonstrated through application to observed from water plant at several locations in the South Korea. Keywords: water demand, non-linear model, the ensemble forecasting model, uncertainty. Acknowledgements This subject is supported by Korea Ministry of Environment as "Projects for Developing Eco-Innovation Technologies (GT-11-G-02-001-6)

Forecast of Frost Days Based on Monthly Temperatures

NASA Astrophysics Data System (ADS)

Castellanos, M. T.; Tarquis, A. M.; Morató, M. C.; Saa-Requejo, A.

2009-04-01

Although frost can cause considerable crop damage and mitigation practices against forecasted frost exist, frost forecasting technologies have not changed for many years. The paper reports a new method to forecast the monthly number of frost days (FD) for several meteorological stations at Community of Madrid (Spain) based on successive application of two models. The first one is a stochastic model, autoregressive integrated moving average (ARIMA), that forecasts monthly minimum absolute temperature (tmin) and monthly average of minimum temperature (tminav) following Box-Jenkins methodology. The second model relates these monthly temperatures to minimum daily temperature distribution during one month. Three ARIMA models were identified for the time series analyzed with a stational period correspondent to one year. They present the same stational behavior (moving average differenced model) and different non-stational part: autoregressive model (Model 1), moving average differenced model (Model 2) and autoregressive and moving average model (Model 3). At the same time, the results point out that minimum daily temperature (tdmin), for the meteorological stations studied, followed a normal distribution each month with a very similar standard deviation through years. This standard deviation obtained for each station and each month could be used as a risk index for cold months. The application of Model 1 to predict minimum monthly temperatures showed the best FD forecast. This procedure provides a tool for crop managers and crop insurance companies to asses the risk of frost frequency and intensity, so that they can take steps to mitigate against frost damage and estimated the damage that frost would cost. This research was supported by Comunidad de Madrid Research Project 076/92. The cooperation of the Spanish National Meteorological Institute and the Spanish Ministerio de Agricultura, Pesca y Alimentation (MAPA) is gratefully acknowledged.

A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale

NASA Astrophysics Data System (ADS)

Zhang, Shaojie; Zhao, Luqiang; Delgado-Tellez, Ricardo; Bao, Hongjun

2018-03-01

Conventional outputs of physics-based landslide forecasting models are presented as deterministic warnings by calculating the safety factor (Fs) of potentially dangerous slopes. However, these models are highly dependent on variables such as cohesion force and internal friction angle which are affected by a high degree of uncertainty especially at a regional scale, resulting in unacceptable uncertainties of Fs. Under such circumstances, the outputs of physical models are more suitable if presented in the form of landslide probability values. In order to develop such models, a method to link the uncertainty of soil parameter values with landslide probability is devised. This paper proposes the use of Monte Carlo methods to quantitatively express uncertainty by assigning random values to physical variables inside a defined interval. The inequality Fs < 1 is tested for each pixel in n simulations which are integrated in a unique parameter. This parameter links the landslide probability to the uncertainties of soil mechanical parameters and is used to create a physics-based probabilistic forecasting model for rainfall-induced shallow landslides. The prediction ability of this model was tested in a case study, in which simulated forecasting of landslide disasters associated with heavy rainfalls on 9 July 2013 in the Wenchuan earthquake region of Sichuan province, China, was performed. The proposed model successfully forecasted landslides in 159 of the 176 disaster points registered by the geo-environmental monitoring station of Sichuan province. Such testing results indicate that the new model can be operated in a highly efficient way and show more reliable results, attributable to its high prediction accuracy. Accordingly, the new model can be potentially packaged into a forecasting system for shallow landslides providing technological support for the mitigation of these disasters at regional scale.

How to Improve Fault Tolerance in Disaster Predictions: A Case Study about Flash Floods Using IoT, ML and Real Data

PubMed Central

Furquim, Gustavo; Filho, Geraldo P. R.; Pessin, Gustavo; Pazzi, Richard W.

2018-01-01

The rise in the number and intensity of natural disasters is a serious problem that affects the whole world. The consequences of these disasters are significantly worse when they occur in urban districts because of the casualties and extent of the damage to goods and property that is caused. Until now feasible methods of dealing with this have included the use of wireless sensor networks (WSNs) for data collection and machine-learning (ML) techniques for forecasting natural disasters. However, there have recently been some promising new innovations in technology which have supplemented the task of monitoring the environment and carrying out the forecasting. One of these schemes involves adopting IP-based (Internet Protocol) sensor networks, by using emerging patterns for IoT. In light of this, in this study, an attempt has been made to set out and describe the results achieved by SENDI (System for dEtecting and forecasting Natural Disasters based on IoT). SENDI is a fault-tolerant system based on IoT, ML and WSN for the detection and forecasting of natural disasters and the issuing of alerts. The system was modeled by means of ns-3 and data collected by a real-world WSN installed in the town of São Carlos - Brazil, which carries out the data collection from rivers in the region. The fault-tolerance is embedded in the system by anticipating the risk of communication breakdowns and the destruction of the nodes during disasters. It operates by adding intelligence to the nodes to carry out the data distribution and forecasting, even in extreme situations. A case study is also included for flash flood forecasting and this makes use of the ns-3 SENDI model and data collected by WSN. PMID:29562657

Waste Information Management System with 2012-13 Waste Streams - 13095

DOE Office of Scientific and Technical Information (OSTI.GOV)

Upadhyay, H.; Quintero, W.; Lagos, L.

2013-07-01

The Waste Information Management System (WIMS) 2012-13 was updated to support the Department of Energy (DOE) accelerated cleanup program. The schedule compression required close coordination and a comprehensive review and prioritization of the barriers that impeded treatment and disposition of the waste streams at each site. Many issues related to waste treatment and disposal were potential critical path issues under the accelerated schedule. In order to facilitate accelerated cleanup initiatives, waste managers at DOE field sites and at DOE Headquarters in Washington, D.C., needed timely waste forecast and transportation information regarding the volumes and types of radioactive waste that wouldmore » be generated by DOE sites over the next 40 years. Each local DOE site historically collected, organized, and displayed waste forecast information in separate and unique systems. In order for interested parties to understand and view the complete DOE complex-wide picture, the radioactive waste and shipment information of each DOE site needed to be entered into a common application. The WIMS application was therefore created to serve as a common application to improve stakeholder comprehension and improve DOE radioactive waste treatment and disposal planning and scheduling. WIMS allows identification of total forecasted waste volumes, material classes, disposition sites, choke points, technological or regulatory barriers to treatment and disposal, along with forecasted waste transportation information by rail, truck and inter-modal shipments. The Applied Research Center (ARC) at Florida International University (FIU) in Miami, Florida, developed and deployed the web-based forecast and transportation system and is responsible for updating the radioactive waste forecast and transportation data on a regular basis to ensure the long-term viability and value of this system. (authors)« less

Towards the intrahour forecasting of direct normal irradiance using sky-imaging data.

PubMed

Nou, Julien; Chauvin, Rémi; Eynard, Julien; Thil, Stéphane; Grieu, Stéphane

2018-04-01

Increasing power plant efficiency through improved operation is key in the development of Concentrating Solar Power (CSP) technologies. To this end, one of the most challenging topics remains accurately forecasting the solar resource at a short-term horizon. Indeed, in CSP plants, production is directly impacted by both the availability and variability of the solar resource and, more specifically, by Direct Normal Irradiance (DNI). The present paper deals with a new approach to the intrahour forecasting (the forecast horizon [Formula: see text] is up to [Formula: see text] ahead) of DNI, taking advantage of the fact that this quantity can be split into two terms, i.e. clear-sky DNI and the clear sky index. Clear-sky DNI is forecasted from DNI measurements, using an empirical model (Ineichen and Perez, 2002) combined with a persistence of atmospheric turbidity. Moreover, in the framework of the CSPIMP (Concentrating Solar Power plant efficiency IMProvement) research project, PROMES-CNRS has developed a sky imager able to provide High Dynamic Range (HDR) images. So, regarding the clear-sky index, it is forecasted from sky-imaging data, using an Adaptive Network-based Fuzzy Inference System (ANFIS). A hybrid algorithm that takes inspiration from the classification algorithm proposed by Ghonima et al. (2012) when clear-sky anisotropy is known and from the hybrid thresholding algorithm proposed by Li et al. (2011) in the opposite case has been developed to the detection of clouds. Performance is evaluated via a comparative study in which persistence models - either a persistence of DNI or a persistence of the clear-sky index - are included. Preliminary results highlight that the proposed approach has the potential to outperform these models (both persistence models achieve similar performance) in terms of forecasting accuracy: over the test data used, RMSE (the Root Mean Square Error) is reduced of about [Formula: see text], with [Formula: see text], and [Formula: see text], with [Formula: see text].

Optimization modeling of U.S. renewable electricity deployment using local input variables

NASA Astrophysics Data System (ADS)

Bernstein, Adam

For the past five years, state Renewable Portfolio Standard (RPS) laws have been a primary driver of renewable electricity (RE) deployments in the United States. However, four key trends currently developing: (i) lower natural gas prices, (ii) slower growth in electricity demand, (iii) challenges of system balancing intermittent RE within the U.S. transmission regions, and (iv) fewer economical sites for RE development, may limit the efficacy of RPS laws over the remainder of the current RPS statutes' lifetime. An outsized proportion of U.S. RE build occurs in a small number of favorable locations, increasing the effects of these variables on marginal RE capacity additions. A state-by-state analysis is necessary to study the U.S. electric sector and to generate technology specific generation forecasts. We used LP optimization modeling similar to the National Renewable Energy Laboratory (NREL) Renewable Energy Development System (ReEDS) to forecast RE deployment across the 8 U.S. states with the largest electricity load, and found state-level RE projections to Year 2031 significantly lower than thoseimplied in the Energy Information Administration (EIA) 2013 Annual Energy Outlook forecast. Additionally, the majority of states do not achieve their RPS targets in our forecast. Combined with the tendency of prior research and RE forecasts to focus on larger national and global scale models, we posit that further bottom-up state and local analysis is needed for more accurate policy assessment, forecasting, and ongoing revision of variables as parameter values evolve through time. Current optimization software eliminates much of the need for algorithm coding and programming, allowing for rapid model construction and updating across many customized state and local RE parameters. Further, our results can be tested against the empirical outcomes that will be observed over the coming years, and the forecast deviation from the actuals can be attributed to discrete parameter variances.

JPRS Report, Science & Technology. Japan: Economic Planning Agency Technology Forecast to the Year 2010.

DTIC Science & Technology

1991-11-17

are several concrete examples of how these affect application. (1) For the development and spread of solar photoelectric power generation, under the...technician in charge of each generator. In order to promote the installation of solar cells at various households and businesses, the relevant laws must be...products from microorganisms ’ Solar photoelectric power Communications satellites Skyscrapers Alone in 1st Tied for 1st 10 Years Ago Present !i

Impact Assessment and Forecasts of Information and Telecommunications Technologies Applied to Education and Training: Volume II--Main Report and Issues Analyses. Analysis for the Orientation of the Work of Sector Actors in the Framework of DELTA.

ERIC Educational Resources Information Center

Commission of the European Communities, Brussels (Belgium).

This report, the second volume in a three volume set, summarizes the results of a study performed by the DELTA (Developing European Learning through Technological Advance) unit in parallel with the projects underway in the research and development Exploratory Action. The report identifies the key issues, associated requirements and options, and…

Prioritization Methodology for Chemical Replacement

NASA Technical Reports Server (NTRS)

Cruit, W.; Schutzenhofer, S.; Goldberg, B.; Everhart, K.

1993-01-01

This project serves to define an appropriate methodology for effective prioritization of efforts required to develop replacement technologies mandated by imposed and forecast legislation. The methodology used is a semiquantitative approach derived from quality function deployment techniques (QFD Matrix). This methodology aims to weigh the full environmental, cost, safety, reliability, and programmatic implications of replacement technology development to allow appropriate identification of viable candidates and programmatic alternatives. The results are being implemented as a guideline for consideration for current NASA propulsion systems.

Technology Scenario for the Year 2005. Volume II. Detailed Scenes for Scenarios.

DTIC Science & Technology

1981-10-01

administrative law judge action. c. Data on case routed to federal district court. 6. Input from Weather Service and EDNI sensors give indications of ai shift...1Of T*4A- FINAL REPORT October, 1981 Document is available to the public through the National Technical Information Service , Springfield, Virginia...volume study forecasts advances in science and technology and ’in deand fo CostGuard services , and expanding opportunities for the Coast Guard. Volme

Ocean Predictability and Uncertainty Forecasts Using Local Ensemble Transfer Kalman Filter (LETKF)

NASA Astrophysics Data System (ADS)

Wei, M.; Hogan, P. J.; Rowley, C. D.; Smedstad, O. M.; Wallcraft, A. J.; Penny, S. G.

2017-12-01

Ocean predictability and uncertainty are studied with an ensemble system that has been developed based on the US Navy's operational HYCOM using the Local Ensemble Transfer Kalman Filter (LETKF) technology. One of the advantages of this method is that the best possible initial analysis states for the HYCOM forecasts are provided by the LETKF which assimilates operational observations using ensemble method. The background covariance during this assimilation process is implicitly supplied with the ensemble avoiding the difficult task of developing tangent linear and adjoint models out of HYCOM with the complicated hybrid isopycnal vertical coordinate for 4D-VAR. The flow-dependent background covariance from the ensemble will be an indispensable part in the next generation hybrid 4D-Var/ensemble data assimilation system. The predictability and uncertainty for the ocean forecasts are studied initially for the Gulf of Mexico. The results are compared with another ensemble system using Ensemble Transfer (ET) method which has been used in the Navy's operational center. The advantages and disadvantages are discussed.

Advanced solar irradiances applied to satellite and ionospheric operational systems

NASA Astrophysics Data System (ADS)

Tobiska, W. Kent; Schunk, Robert; Eccles, Vince; Bouwer, Dave

Satellite and ionospheric operational systems require solar irradiances in a variety of time scales and spectral formats. We describe the development of a system using operational grade solar irradiances that are applied to empirical thermospheric density models and physics-based ionospheric models used by operational systems that require a space weather characterization. The SOLAR2000 (S2K) and SOLARFLARE (SFLR) models developed by Space Environment Technologies (SET) provide solar irradiances from the soft X-rays (XUV) through the Far Ultraviolet (FUV) spectrum. The irradiances are provided as integrated indices for the JB2006 empirical atmosphere density models and as line/band spectral irradiances for the physics-based Ionosphere Forecast Model (IFM) developed by the Space Environment Corporation (SEC). We describe the integration of these irradiances in historical, current epoch, and forecast modes through the Communication Alert and Prediction System (CAPS). CAPS provides real-time and forecast HF radio availability for global and regional users and global total electron content (TEC) conditions.

Applications of ISES for meteorology

NASA Technical Reports Server (NTRS)

Try, Paul D.

1990-01-01

The results are summarized from an initial assessment of the potential real-time meteorological requirements for the data from Eos systems. Eos research scientists associated with facility instruments, investigator instruments, and interdisciplinary groups with data related to meteorological support were contacted, along with those from the normal operational user and technique development groups. Two types of activities indicated the greatest need for real-time Eos data: technology transfer groups (e.g., NOAA's Forecasting System Laboratory and the DOD development laboratories), and field testing groups with airborne operations. A special concern was expressed by several non-U.S. participants who desire a direct downlink to be sure of rapid receipt of the data for their area of interest. Several potential experiments or demonstrations are recommended for ISES which include support for hurricane/typhoon forecasting, space shuttle reentry, severe weather forecasting (using microphysical cloud classification techniques), field testing, and quick reaction of instrumented aircraft to measure such events as polar stratospheric clouds and volcanic eruptions.

Scaling forecast models for wind turbulence and wind turbine power intermittency

NASA Astrophysics Data System (ADS)

Duran Medina, Olmo; Schmitt, Francois G.; Calif, Rudy

2017-04-01

The intermittency of the wind turbine power remains an important issue for the massive development of this renewable energy. The energy peaks injected in the electric grid produce difficulties in the energy distribution management. Hence, a correct forecast of the wind power in the short and middle term is needed due to the high unpredictability of the intermittency phenomenon. We consider a statistical approach through the analysis and characterization of stochastic fluctuations. The theoretical framework is the multifractal modelisation of wind velocity fluctuations. Here, we consider three wind turbine data where two possess a direct drive technology. Those turbines are producing energy in real exploitation conditions and allow to test our forecast models of power production at a different time horizons. Two forecast models were developed based on two physical principles observed in the wind and the power time series: the scaling properties on the one hand and the intermittency in the wind power increments on the other. The first tool is related to the intermittency through a multifractal lognormal fit of the power fluctuations. The second tool is based on an analogy of the power scaling properties with a fractional brownian motion. Indeed, an inner long-term memory is found in both time series. Both models show encouraging results since a correct tendency of the signal is respected over different time scales. Those tools are first steps to a search of efficient forecasting approaches for grid adaptation facing the wind energy fluctuations.

SSMA Science Reviewers' Forecasts for the Future of Science Education.

ERIC Educational Resources Information Center

Jinks, Jerry; Hoffer, Terry

1989-01-01

Described is a study which was conducted as an exploratory assessment of science reviewers' perceptions for the future of science education. Arrives at interpretations for identified categories of computers and high technology, science curriculum, teacher education, training, certification, standards, teaching methods, and materials. (RT)

Clarus multi-state regional demonstrations, evaluation of use case #5 : enhanced road weather content for traveler advisories.

DOT National Transportation Integrated Search

2011-05-11

This evaluation report presents an assessment of the benefits of a new road condition forecast tool that offers road weather information to travelers. The tool has been developed by Meridian Environmental Technology, Inc. and has been demonstrated in...

Defining the taxonomic domain of applicability for mammalian-based high-throughput screening assays

EPA Science Inventory

Cell-based high throughput screening (HTS) technologies are becoming mainstream in chemical safety evaluations. The US Environmental Protection Agency (EPA) Toxicity Forecaster (ToxCastTM) and the multi-agency Tox21 Programs have been at the forefront in advancing this science, m...

Establishing Priorities for Postsecondary Energy-Related Technology Programs

ERIC Educational Resources Information Center

Brooking, Walter J.

1977-01-01

Data from a Shell Oil Company forecast of national energy requirements through 1990 and from a national invitational conference on energy-related postsecondary programs are presented under the following headings: Coal mining beneficiation and processing, petroleum extraction and refining, nuclear power production, solar energy, and energy…

NREL: Renewable Resource Data Center - Solar Resource Publications

Science.gov Websites

Publications The following links provide useful information about solar resource tools and data resources, solar data, or solar technology". Resource Assessment and Forecasting Group Publications By | 1985 | 1984 | 1983 | 1982 | 1981 | 1980 Miscellaneous Printable Version RReDC Home Biomass Resource

(Some) Computer Futures: Mainframes.

ERIC Educational Resources Information Center

Joseph, Earl C.

Possible futures for the world of mainframe computers can be forecast through studies identifying forces of change and their impact on current trends. Some new prospects for the future have been generated by advances in information technology; for example, recent United States successes in applied artificial intelligence (AI) have created new…

APPLICATION OF THE REGIONAL VULNERABILITY ASSESSMENT (REVA) INTEGRATION TOOL AND UNDERLYING METHODS FOR MULTI-SCALE DECISION MAKING

EPA Science Inventory

In support of the National Science and Technology Council's cross-Agency priority of Integrated Science for Ecological Challenges (ISEC) EPA is conducting research to improve capabilities in the area of regional vulnerability assessment and ecological forecasting. EPA's research...

Net-zero Building Cluster Simulations and On-line Energy Forecasting for Adaptive and Real-Time Control and Decisions

NASA Astrophysics Data System (ADS)

Li, Xiwang

Buildings consume about 41.1% of primary energy and 74% of the electricity in the U.S. Moreover, it is estimated by the National Energy Technology Laboratory that more than 1/4 of the 713 GW of U.S. electricity demand in 2010 could be dispatchable if only buildings could respond to that dispatch through advanced building energy control and operation strategies and smart grid infrastructure. In this study, it is envisioned that neighboring buildings will have the tendency to form a cluster, an open cyber-physical system to exploit the economic opportunities provided by a smart grid, distributed power generation, and storage devices. Through optimized demand management, these building clusters will then reduce overall primary energy consumption and peak time electricity consumption, and be more resilient to power disruptions. Therefore, this project seeks to develop a Net-zero building cluster simulation testbed and high fidelity energy forecasting models for adaptive and real-time control and decision making strategy development that can be used in a Net-zero building cluster. The following research activities are summarized in this thesis: 1) Development of a building cluster emulator for building cluster control and operation strategy assessment. 2) Development of a novel building energy forecasting methodology using active system identification and data fusion techniques. In this methodology, a systematic approach for building energy system characteristic evaluation, system excitation and model adaptation is included. The developed methodology is compared with other literature-reported building energy forecasting methods; 3) Development of the high fidelity on-line building cluster energy forecasting models, which includes energy forecasting models for buildings, PV panels, batteries and ice tank thermal storage systems 4) Small scale real building validation study to verify the performance of the developed building energy forecasting methodology. The outcomes of this thesis can be used for building cluster energy forecasting model development and model based control and operation optimization. The thesis concludes with a summary of the key outcomes of this research, as well as a list of recommendations for future work.

Short Term Weather Forecasting and Long Term Climate Predictions in Mesoamerica

NASA Astrophysics Data System (ADS)

Hardin, D. M.; Daniel, I.; Mecikalski, J.; Graves, S.

2008-05-01

The SERVIR project utilizes several predictive models to support regional monitoring and decision support in Mesoamerica. Short term forecasts ranging from a few hours to several days produce more than 30 data products that are used daily by decision makers, as well as news organizations in the region. The forecast products can be visualized in both two and three dimensional viewers such as Google Maps and Google Earth. Other viewers developed specifically for the Mesoamerican region by the University of Alabama in Huntsville and the Institute for the Application of Geospatial Technologies in Auburn New York can also be employed. In collaboration with the NASA Short Term Prediction Research and Transition (SpoRT) Center SERVIR utilizes the Weather Research and Forecast (WRF) model to produce short-term (24 hr) regional weather forecasts twice a day. Temperature, precipitation, wind, and other variables are forecast in 10km and 30km grids over the Mesoamerica region. Using the PSU/NCAR Mesoscale Model, known as MM5, SERVIR produces 48 hour- forecasts of soil temperature, two meter surface temperature, three hour accumulated precipitation, winds at different heights, and other variables. These are forecast hourly in 9km grids. Working in collaboration with the Atmospheric Science Department of the University of Alabama in Huntsville produces a suite of short-term (0-6 hour) weather prediction products are generated. These "convective initiation" products predict the onset of thunderstorm rainfall and lightning within a 1-hour timeframe. Models are also employed for long term predictions. The SERVIR project, under USAID funding, has developed comprehensive regional climate change scenarios of Mesoamerica for future years: 2010, 2015, 2025, 2050, and 2099. These scenarios were created using the Pennsylvania State University/National Center for Atmospheric Research (MM5) model and processed on the Oak Ridge National Laboratory Cheetah supercomputer. The goal of these Mesoamerican climate change scenarios is to better understand the regional climate, the major controls, and how it might be expected to change in the future. This presentation will present a summary of the model results and show the application of these data in preparation for and response to recent tropical storms.

Nowcasting in the FROST-2014 Sochi Olympic project

NASA Astrophysics Data System (ADS)

Bica, Benedikt; Wang, Yong; Joe, Paul; Isaac, George; Kiktev, Dmitry; Bocharnikov, Nikolai

2013-04-01

FROST (Forecast and Research: the Olympic Sochi Testbed) 2014 is a WMO WWRP international project aimed at development, implementation, and demonstration of capabilities of short-range numerical weather prediction and nowcasting technologies for mountainous terrain in winter season. Sharp weather contrasts and high spatial and temporal variability are typical for the region of the Sochi-2014 Olympics. Steep mountainous terrain and an intricate mixture of maritime sub-tropical and Alpine environments make weather forecasting in this region extremely challenging. Goals of the FROST-2014 project: • To develop a comprehensive information resource of Alpine winter weather observations; • To improve and exploit: o Nowcasting systems of high impact weather phenomena (precipitation type and intensity, snow levels, visibility, wind speed, direction and gusts) in complex terrain; o High-resolution deterministic and ensemble mesoscale forecasts in winter complex terrain environment; • To improve the understanding of physics of high impact weather phenomena in the region; • To deliver forecasts (Nowcasts) to Olympic weather forecasters and decision makers and assess benefits of forecast improvement. 46 Automatic Meteorological Stations (AMS) were installed in the Olympic region by Roshydromet, by owners of sport venues and by the Megafon corporation, provider of mobile communication services. The time resolution of AMS observations does not exceed 10 minutes. For a subset of the stations it is even equal to 1 min. Data flow from the new dual polarization Doppler weather radar WRM200 in Sochi was organized at the end of 2012. Temperature/humidity and wind profilers and two Micro Rain Radars (MRR) will supplement the network. Nowcasting potential of NWP models participating in the project (COSMO, GEM, WRF, AROME, HARMONIE) is to be assessed for direct and post-processed (e.g. Kalman filter, 1-D model, MOS) model forecasts. Besides the meso-scale models, the specialized nowcasting systems are expected to be used in the project - ABOM, CARDS, INCA, INTW, STEPS, MeteoExpert. FROST-2014 is intended as an 'end-to-end' project. Its products will be used by local forecasters for meteorological support of the Olympics and preceding test sport events. The project is open for new interested participants. Additional information is available at http://frost2014.meteoinfo.ru.

The impact of underwater glider observations in the forecast of Hurricane Gonzalo (2014)

NASA Astrophysics Data System (ADS)

Goni, G. J.; Domingues, R. M.; Kim, H. S.; Domingues, R. M.; Halliwell, G. R., Jr.; Bringas, F.; Morell, J. M.; Pomales, L.; Baltes, R.

2017-12-01

The tropical Atlantic basin is one of seven global regions where tropical cyclones (TC) are commonly observed to originate and intensify from June to November. On average, approximately 12 TCs travel through the region every year, frequently affecting coastal, and highly populated areas. In an average year, 2 to 3 of them are categorized as intense hurricanes. Given the appropriate atmospheric conditions, TC intensification has been linked to ocean conditions, such as increased ocean heat content and enhanced salinity stratification near the surface. While errors in hurricane track forecasts have been reduced during the last years, errors in intensity forecasts remain mostly unchanged. Several studies have indicated that the use of in situ observations has the potential to improve the representation of the ocean to correctly initialize coupled hurricane intensity forecast models. However, a sustained in situ ocean observing system in the tropical North Atlantic Ocean and Caribbean Sea dedicated to measuring subsurface thermal and salinity fields in support of TC intensity studies and forecasts has yet to be implemented. Autonomous technologies offer new and cost-effective opportunities to accomplish this objective. We highlight here a partnership effort that utilize underwater gliders to better understand air-sea processes during high wind events, and are particularly geared towards improving hurricane intensity forecasts. Results are presented for Hurricane Gonzalo (2014), where glider observations obtained in the tropical Atlantic: Helped to provide an accurate description of the upper ocean conditions, that included the presence of a low salinity barrier layer; Allowed a detailed analysis of the upper ocean response to hurricane force winds of Gonzalo; Improved the initialization of the ocean in a coupled ocean-atmosphere numerical model; and together with observations from other ocean observing platforms, substantially reduced the error in intensity forecast using the HYCOM-HWRF model. Data collected by this project are transmitted in real-time to the Global Telecommunication System, distributed through the institutional web pages, by the IOOS Glider Data Assembly Center, and by NCEI, and assimilated in real-time numerical weather forecast models.

Regional Precipitation Forecast with Atmospheric InfraRed Sounder (AIRS) Profile Assimilation

NASA Technical Reports Server (NTRS)

Chou, S.-H.; Zavodsky, B. T.; Jedloved, G. J.

2010-01-01

Advanced technology in hyperspectral sensors such as the Atmospheric InfraRed Sounder (AIRS; Aumann et al. 2003) on NASA's polar orbiting Aqua satellite retrieve higher vertical resolution thermodynamic profiles than their predecessors due to increased spectral resolution. Although these capabilities do not replace the robust vertical resolution provided by radiosondes, they can serve as a complement to radiosondes in both space and time. These retrieved soundings can have a significant impact on weather forecasts if properly assimilated into prediction models. Several recent studies have evaluated the performance of specific operational weather forecast models when AIRS data are included in the assimilation process. LeMarshall et al. (2006) concluded that AIRS radiances significantly improved 500 hPa anomaly correlations in medium-range forecasts of the Global Forecast System (GFS) model. McCarty et al. (2009) demonstrated similar forecast improvement in 0-48 hour forecasts in an offline version of the operational North American Mesoscale (NAM) model when AIRS radiances were assimilated at the regional scale. Reale et al. (2008) showed improvements to Northern Hemisphere 500 hPa height anomaly correlations in NASA's Goddard Earth Observing System Model, Version 5 (GEOS-5) global system with the inclusion of partly cloudy AIRS temperature profiles. Singh et al. (2008) assimilated AIRS temperature and moisture profiles into a regional modeling system for a study of a heavy rainfall event during the summer monsoon season in Mumbai, India. This paper describes an approach to assimilate AIRS temperature and moisture profiles into a regional configuration of the Advanced Research Weather Research and Forecasting (WRF-ARW) model using its three-dimensional variational (3DVAR) assimilation system (WRF-Var; Barker et al. 2004). Section 2 describes the AIRS instrument and how the quality indicators are used to intelligently select the highest-quality data for assimilation. Section 3 presents an overall precipitation improvement with AIRS assimilation during a 37-day case study period, and Section 4 focuses on a single case study to further investigate the meteorological impact of AIRS profiles on synoptic scale models. Finally, Section 5 provides a summary of the paper.

Ethical issues in forecasting of natural hazards

NASA Astrophysics Data System (ADS)

Tinti, Stefano

2014-05-01

Natural hazards have by definition a large impact on the society and, therefore, since the beginning of science one of the major aspiration of mankind has been the prediction of natural calamities in the attempt to avoid or to mitigate their effects. In modern societies where science and technology have gained a foundational role, forecasts and predictions have become part of the every-day life and may also influence state policies and economic development. And in parallel with the growing importance of forecasting, even ethical problems for forecasters and for forecasters communities have started to appear. In this work two of the many geo-ethical issues are considered mostly: 1) how to cope with uncertainties that are inherently associated with any forecast statement; 2) how to handle predictions in scientific journals and scientific conferences The former issue is mainly related to the impact of predictions on the general public and on managers and operators in the civil protection field. Forecasters operate in specific contexts that 1) may change from country to country, depending on the local adopted best practices, but also, which is more constraining, on the local legal regulations and laws; 2) may change from discipline to discipline according to the development of the specific knowhow and the range of the forecast (from minutes to centuries) The second issue has to do with the communication of the scientific results on predictions and on prediction methods to the audience mainly composed of scientists, and involves one of the basic elements of science. In principle, scientists should use scientific communication means (papers in scientific journals, conferences, …) to illustrate results that are sound and certain, or the methods by means of which they conduct their research. But scientists involved in predictions have inherently to do with uncertainties, and, since there is no common agreement on how to deal with them, there is the risk that scientific results may be confused with opinions and opinions with scientific results, which creates confusion in the scientific community, in the science divulgators and in turn in the general public.

Using Bayes Model Averaging for Wind Power Forecasts

NASA Astrophysics Data System (ADS)

Preede Revheim, Pål; Beyer, Hans Georg

2014-05-01

For operational purposes predictions of the forecasts of the lumped output of groups of wind farms spread over larger geographic areas will often be of interest. A naive approach is to make forecasts for each individual site and sum them up to get the group forecast. It is however well documented that a better choice is to use a model that also takes advantage of spatial smoothing effects. It might however be the case that some sites tends to more accurately reflect the total output of the region, either in general or for certain wind directions. It will then be of interest giving these a greater influence over the group forecast. Bayesian model averaging (BMA) is a statistical post-processing method for producing probabilistic forecasts from ensembles. Raftery et al. [1] show how BMA can be used for statistical post processing of forecast ensembles, producing PDFs of future weather quantities. The BMA predictive PDF of a future weather quantity is a weighted average of the ensemble members' PDFs, where the weights can be interpreted as posterior probabilities and reflect the ensemble members' contribution to overall forecasting skill over a training period. In Revheim and Beyer [2] the BMA procedure used in Sloughter, Gneiting and Raftery [3] were found to produce fairly accurate PDFs for the future mean wind speed of a group of sites from the single sites wind speeds. However, when the procedure was attempted applied to wind power it resulted in either problems with the estimation of the parameters (mainly caused by longer consecutive periods of no power production) or severe underestimation (mainly caused by problems with reflecting the power curve). In this paper the problems that arose when applying BMA to wind power forecasting is met through two strategies. First, the BMA procedure is run with a combination of single site wind speeds and single site wind power production as input. This solves the problem with longer consecutive periods where the input data does not contain information, but it has the disadvantage of nearly doubling the number of model parameters to be estimated. Second, the BMA procedure is run with group mean wind power as the response variable instead of group mean wind speed. This also solves the problem with longer consecutive periods without information in the input data, but it leaves the power curve to also be estimated from the data. [1] Raftery, A. E., et al. (2005). Using Bayesian Model Averaging to Calibrate Forecast Ensembles. Monthly Weather Review, 133, 1155-1174. [2]Revheim, P. P. and H. G. Beyer (2013). Using Bayesian Model Averaging for wind farm group forecasts. EWEA Wind Power Forecasting Technology Workshop,Rotterdam, 4-5 December 2013. [3]Sloughter, J. M., T. Gneiting and A. E. Raftery (2010). Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging. Journal of the American Statistical Association, Vol. 105, No. 489, 25-35

Transition to Operations Plans for GPM Datasets

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Jedlovec, Gary; Case, Jonathan; Leroy, Anita; Molthan, Andrew; Bell, Jordan; Fuell, Kevin; Stano, Geoffrey

2013-01-01

Founded in 2002 at the National Space Science Technology Center at Marshall Space Flight Center in Huntsville, AL. Focused on transitioning unique NASA and NOAA observations and research capabilities to the operational weather community to improve short-term weather forecasts on a regional and local scale. NASA directed funding; NOAA funding from Proving Grounds (PG). Demonstrate capabilities experimental products to weather applications and societal benefit to prepare forecasters for the use of data from next generation of operational satellites. Objective of this poster is to highlight SPoRT's research to operations (R2O) paradigm and provide examples of work done by the team with legacy instruments relevant to GPM in order to promote collaborations with groups developing GPM products.

AgRISTARS: Foreign commodity production forecasting. Minutes of the annual formal project manager's review, including preliminary technical review reports of FY80 experiments. [wheat/barley and corn/soybean experiments

NASA Technical Reports Server (NTRS)

1980-01-01

The U.S./Canada wheat/barley exploratory experiment is discussed with emphasis on labeling, machine processing using P1A, and the crop calendar. Classification and the simulated aggregation test used in the U.S. corn/soybean exploratory experiment are also considered. Topics covered regarding the foreign commodity production forecasting project include: (1) the acquisition, handling, and processing of both U.S. and foreign agricultural data, as well as meteorological data. The accuracy assessment methodology, multicrop sampling and aggregation technology development, frame development, the yield project interface, and classification for area estimation are also examined.

Proceedings of a Workshop on Navy Long-Range Deep Ocean Technology: An Assessment of Current Development, Forecasts, and Research Thrusts Held at Washington, DC on September 23-24, 1982,

DTIC Science & Technology

1983-01-01

the Navy. These technologies ini- tially were reviewed in five groups; the technologies were assessed later during the workshop in four sets, two of...sulfur dioxide (LiSO2 ). The latter two systems present safety hazards after discharge.1- 7 Also these systems are already being developed exten- sively...Control The K02 life support system will supply oxygen and, at the same time, remove CO2. One chemical performs the two essential functions of the

Efficiency improvements in US Office equipment: Expected policy impacts and uncertainties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koomey, J.G.; Cramer, M.; Piette, M.A.

This report describes a detailed end-use forecast of office equipment energy use for the US commercial sector. We explore the likely impacts of the US Environmental Protection Agency`s ENERGY STAR office equipment program and the potential impacts of advanced technologies. The ENERGY STAR program encourages manufacturers to voluntarily incorporate power saving features into personal computers, monitors, printers, copiers, and fax machines in exchange for allowing manufacturers to use the EPA ENERGY STAR logo in their advertising campaigns. The Advanced technology case assumes that the most energy efficient current technologies are implemented regardless of cost.

Fiscal year 1981 US corn and soybeans pilot preliminary experiment plan, phase 1

NASA Technical Reports Server (NTRS)

Livingston, G. P.; Nedelman, K. S.; Norwood, D. F.; Smith, J. H. (Principal Investigator)

1981-01-01

A draft of the preliminary experiment plan for the foreign commodity production forecasting project fiscal year 1981 is presented. This draft plan includes: definition of the phase 1 and 2 U.S. pilot objectives; the proposed experiment design to evaluate crop calendar, area estimation, and area aggregation components for corn and soybean technologies using 1978/1979 crop-year data; a description of individual sensitivity evaluations of the baseline corn and soybean segment classification procedure; and technology and data assessment in support of the corn and soybean estimation technology for use in the U.S. central corn belt.

The development and utilization of solar photovoltaic cells: An assessment of the potential for a new energy technology

NASA Technical Reports Server (NTRS)

Cyr, K. J.

1981-01-01

The Government set the goal of accelerating the adaptation of photovoltaics by reducing system costs to a competitive level and overcoming the technical, institutional, legal, environmental, and social barriers impeding the diffusion of photovoltaic technology. The technology of silicon solar arrays was examined and the status of development efforts are reviewed. The political, legal, economic, social, and environmental issues are discussed, and several methods for selecting development projects are described. A number of market forecasting techniques, including time trend, judgemental, and econometric methods, were reviewed, and the results of these models are presented.

A Public-Private-Acadmic Partnership to Advance Solar Power Forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haupt, Sue Ellen

The National Center for Atmospheric Research (NCAR) is pleased to have led a partnership to advance the state-of-the-science of solar power forecasting by designing, developing, building, deploying, testing, and assessing the SunCast™ Solar Power Forecasting System. The project has included cutting edge research, testing in several geographically- and climatologically-diverse high penetration solar utilities and Independent System Operators (ISOs), and wide dissemination of the research results to raise the bar on solar power forecasting technology. The partners include three other national laboratories, six universities, and industry partners. This public-private-academic team has worked in concert to perform use-inspired research to advance solarmore » power forecasting through cutting-edge research to advance both the necessary forecasting technologies and the metrics for evaluating them. The project has culminated in a year-long, full-scale demonstration of provide irradiance and power forecasts to utilities and ISOs to use in their operations. The project focused on providing elements of a value chain, beginning with the weather that causes a deviation from clear sky irradiance and progresses through monitoring and observations, modeling, forecasting, dissemination and communication of the forecasts, interpretation of the forecast, and through decision-making, which produces outcomes that have an economic value. The system has been evaluated using metrics developed specifically for this project, which has provided rich information on model and system performance. Research was accomplished on the very short range (0-6 hours) Nowcasting system as well as on the longer term (6-72 hour) forecasting system. The shortest range forecasts are based on observations in the field. The shortest range system, built by Brookhaven National Laboratory (BNL) and based on Total Sky Imagers (TSIs) is TSICast, which operates on the shortest time scale with a latency of only a few minutes and forecasts that currently go out to about 15 min. This project has facilitated research in improving the hardware and software so that the new high definition cameras deployed at multiple nearby locations allow discernment of the clouds at varying levels and advection according to the winds observed at those levels. Improvements over “smart persistence” are about 29% for even these very short forecasts. StatCast is based on pyranometer data measured at the site as well as concurrent meteorological observations and forecasts. StatCast is based on regime-dependent artificial intelligence forecasting techniques and has been shown to improve on “smart persistence” forecasts by 15-50%. A second category of short-range forecasting systems employ satellite imagery and use that information to discern clouds and their motion, allowing them to project the clouds, and the resulting blockage of irradiance, in time. CIRACast (the system produced by the Cooperative Institute for Atmospheric Research [CIRA] at Colorado State University) was already one of the more advanced cloud motion systems, which is the reason that team was brought to this project. During the project timeframe, the CIRA team was able to advance cloud shadowing, parallax removal, and implementation of better advecting winds at different altitudes. CIRACast shows generally a 25-40% improvement over Smart Persistence between sunrise and approximately 1600 UTC (Coordinated Universal Time) . A second satellite-based system, MADCast (Multi-sensor Advective Diffusive foreCast system), assimilates data from multiple satellite imagers and profilers to assimilate a fully three-dimensional picture of the cloud into the dynamic core of WRF. During 2015, MADCast (provided at least 70% improvement over Smart Persistence, with most of that skill being derived during partly cloudy conditions. That allows advection of the clouds via the Weather Research and Forecasting (WRF) model dynamics directly. After WRF-Solar™ showed initial success, it was also deployed in nowcasting mode with coarser runs out to 6 hours made hourly. It provided improvements on the order of 50-60% over Smart Persistence for forecasts up to 1600 UTC. The advantages of WRF-Solar-Nowcasting and MADCast were then blended to develop the new MAD-WRF model that incorporates the most important features of each of those models, both assimilating satellite cloud fields and using WRF-So far physics to develop and dissipate clouds. MAE improvements for MAD-WRF for forecasts from 3-6 hours are improved over WRF-Solar-Now by 20%. While all the Nowcasting system components by themselves provide improvement over Smart Persistence, the largest benefit is derived when they are smartly blended together by the Nowcasting Integrator to produce an integrated forecast. The development of WRF-Solar™ under this project has provided the first numerical weather prediction (NWP) model specifically designed to meet the needs of irradiance forecasting. The first augmentation improved the solar tracking algorithm to account for deviations associated with the eccentricity of the Earth’s orbit and the obliquity of the Earth. Second, WRF-Solar™ added the direct normal irradiance (DNI) and diffuse (DIF) components from the radiation parameterization to the model output. Third, efficient parameterizations were implemented to either interpolate the irradiance in between calls to the expensive radiative transfer parameterization, or to use a fast radiative transfer code that avoids computing three-dimensional heating rates but provides the surface irradiance. Fourth, a new parameterization was developed to improve the representation of absorption and scattering of radiation by aerosols (aerosol direct effect). A fifth advance is that the aerosols now interact with the cloud microphysics, altering the cloud evolution and radiative properties, an effect that has been traditionally only implemented in atmospheric computationally costly chemistry models. A sixth development accounts for the feedbacks that sub-grid scale clouds produce in shortwave irradiance as implemented in a shallow cumulus parameterization Finally, WRF-Solar™ also allows assimilation of infrared irradiances from satellites to determine the three dimensional cloud field, allowing for an improved initialization of the cloud field that increases the performance of short-range forecasts. We find that WRF-Solar™ can improve clear sky irradiance prediction by 15-80% over a standard version of WRF, depending on location and cloud conditions. In a formal comparison to the NAM baseline, WRF-Solar™ showed improvements in the Day-Ahead forecast of 22-42%. The SunCast™ system requires substantial software engineering to blend all of the new model components as well as existing publically available NWP model runs. To do this we use an expert system for the Nowcasting blender and the Dynamic Integrated foreCast (DICast®) system for the NWP models. These two systems are then blended, we use an empirical power conversion method to convert the irradiance predictions to power, then apply an analog ensemble (AnEn) approach to further tune the forecast as well as to estimate its uncertainty. The AnEn module decreased RMSE (root mean squared error) by 17% over the blended SunCast™ power forecasts and provided skill in the probabilistic forecast with a Brier Skill Score of 0.55. In addition, we have also developed a Gridded Atmospheric Forecast System (GRAFS) in parallel, leveraging cost share funds. An economic evaluation based on Production Cost Modeling in the Public Service Company of Colorado showed that the observed 50% improvement in forecast accuracy will save their customers $819,200 with the projected MW deployment for 2024. Using econometrics, NCAR has scaled this savings to a national level and shown that an annual expected savings for this 50% forecast error reduction ranges from $11M in 2015 to $43M expected in 2040 with increased solar deployment. This amounts to a $455M discounted savings over the 26 year period of analysis.« less

Welding and Fabricating Technology Program Needs Assessment.

ERIC Educational Resources Information Center

Oakland Community Coll., Farmington, MI. Office of Institutional Planning and Analysis.

In 1992, Oakland Community College (OCC) conducted a needs assessment study to assist in reviewing and evaluating proposed changes to the college's existing Welding and Fabricating Program. A literature review was undertaken, examining industry forecasts, related programs at other institutions of higher education, and data supplied by the U.S.…

An Integrated Modeling Framework Forecasting Ecosystem Services: Application to the Albemarle Pamlico Basins, NC and VA (USA)

EPA Science Inventory

We demonstrate an Integrated Modeling Framework that predicts the state of freshwater ecosystem services within the Albemarle-Pamlico Basins. The Framework consists of three facilitating technologies: Data for Environmental Modeling (D4EM) that automates the collection and standa...

Intertwined Cultural and Relational Environments of Organizations

ERIC Educational Resources Information Center

Granados, Francisco J.

2005-01-01

I examine fundamental elements of the cultural and relational environments of the organizations that produce electoral forecasts in the Spanish parliamentary elections. The analysis reveals how these elements shape the interests and decisions in a collectivity of organizations that share a common technology. I investigate the reasons for the…

The Twilight of Television.

ERIC Educational Resources Information Center

Morrisett, Lloyd N.

1994-01-01

Describes the evolution of television technology and the changes in its use brought about by cable television and the videocassette recorder. The increasing use of multimedia, made possible by the marriage of television and computer, are discussed. A reemergence of the importance of written language in this new medium is forecast. (KRN)

Guest Editorial

DOE PAGES

Deline, Christopher A; van Sark, Wilfried; Georghiou, George E.

2017-08-16

This Special Issue entitled 'Performance Assessment and Condition Monitoring of Photovoltaic Systems for Improved Energy Yield', contains ten papers that discuss various aspects in performance assessment, thus bringing the reader up to date with the present state-of-the-art technologies. In particular, the following topics are addressed: system performance monitoring; operational analysis and design; solar forecasting.

Workshop on Office Automation and Telecommunication: Applying the Technology.

ERIC Educational Resources Information Center

Mitchell, Bill

This document contains 12 outlines that forecast the office of the future. The outlines cover the following topics: (1) office automation definition and objectives; (2) functional categories of office automation software packages for mini and mainframe computers; (3) office automation-related software for microcomputers; (4) office automation…

New NOAA spacecraft readies for launch next month

Science.gov Websites

: NASA) DSCOVR spacecraft at NASA's Goddard Spaceflight Center, Greenbelt, Maryland. (Credit: NASA) " . In addition to space weather technology, DSCOVR will carry two NASA Earth-observing instruments that timely space weather forecasting by NOAA and provide important Earth-observing data to NASA." The

Planning Responses to Demographic Change. AIR 1986 Annual Forum Paper.

ERIC Educational Resources Information Center

Taylor, Bryan J. R.; Taylor, Elizabeth A.

A method for forecasting the number of college graduates in the United Kingdom is described, and suggestions are offered about ways that society should react to influence declining enrollments and potential reductions in technologically skilled graduates. Consideration is given to the implications of recruiting noncollege-bound individuals to…

Essays on Technology and Forecasting in Macroeconomics

ERIC Educational Resources Information Center

Samuels, Jon Devin

2012-01-01

The three chapters in this dissertation use disaggregated models and data to provide new insights on well-established questions in macroeconomics. In the first chapter, to analyze how productivity impacts the business cycle, I model aggregate production with a production possibility frontier that accommodates sector-and factor-biased productivity.…

Controlling vector-borne disease and adapting to climate change with novel research on disease forecasting to target new vector control materials and technologies

USDA-ARS?s Scientific Manuscript database

Population growth, frontier agricultural expansion, and urbanization transform the landscape and the surrounding ecosystem, affecting climate and interactions between animals and humans, and significantly influencing the transmission dynamics and geographic distribution of malaria, dengue and other ...

The Economics of Industrial Preparedness Planning and Raw Materials Stockpiling

DTIC Science & Technology

1982-05-01

concepts are sketched on page 6. Chapter II 1. Marshall, Alfred, Principles of Economics , Guillebaud ed., pages 330, 465, 366, 372, 374, and 377. 2... Principles of Economics , Guillebaud Edition, Vol. 1. New York: The MacMillan Co, 1961. Martino, Joseph P., Technological Forecasting For Decision- making

EXAMINING PAST LANDSCAPE CHANGE AND FORECASTING HYDROLOGICAL AND BIOLOGICAL RESPONSE TO LAND USE CHANGE

EPA Science Inventory

It is currently possible to measure landscape change over large areas and

determine trends in environmental condition using advanced space-based technologies

accompanied by geospatial data. There are numerous earth-observing satellite platforms

for mapping an...

EVALUATING HYDROLOGICAL RESPONSE TO FORECASTED LAND-USE CHANGE: SCENARIO TESTING WITH THE AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT TOOL

EPA Science Inventory

It is currently possible to measure landscape change over large areas and determine trends in environmental condition using advanced space-based technologies accompanied by geospatial analyses of the remotely sensed data. There are numerous earth-observing satellite platforms fo...

On the forecasting the unfavorable periods in the technosphere by the space weather factors

NASA Astrophysics Data System (ADS)

Lyakhov, N. N.

2002-12-01

There is the considerable progress in development of geomagnetic disturbances forecast technique, in the necessary time, by solar activity phenomena last years. The possible relationship between violations of the traffic safety terms (VTS) in East Siberian Railway during 1986-1999 and the space weather factors was investigated. The overall number of cases under consideration is equal to 11575. By methods of correlation and spectral analysis it was shown, that statistics of VTS has not a random and it's character is probably caused by space weather factors. The principal difference between rhythmic of VTS by purely technical reasons (MECH) (failures in mechanical systems) and, that of VTS caused by wrong operations of a personnel (MAN), is noted. Increase of sudden storm commencements number results in increase of probability of mistakable actions of an operator. Probability of violations in mechanical systems increases with increase of number of quiet geomagnetic conditions. This, in its turn, dictate different approach to the ordered rows of MECH and MAN data when forecasting the unfavourable periods as the priods of increased risk in working out a wrong decision by technological process participants. The advances in forecasting of geomagnetic environment technique made possible to start construction of systems of the operative informing about unfavourable factors of space weather for the interested organizations.

Community-based early warning systems for flood risk mitigation in Nepal

NASA Astrophysics Data System (ADS)

Smith, Paul J.; Brown, Sarah; Dugar, Sumit

2017-03-01

This paper focuses on the use of community-based early warning systems for flood resilience in Nepal. The first part of the work outlines the evolution and current status of these community-based systems, highlighting the limited lead times currently available for early warning. The second part of the paper focuses on the development of a robust operational flood forecasting methodology for use by the Nepal Department of Hydrology and Meteorology (DHM) to enhance early warning lead times. The methodology uses data-based physically interpretable time series models and data assimilation to generate probabilistic forecasts, which are presented in a simple visual tool. The approach is designed to work in situations of limited data availability with an emphasis on sustainability and appropriate technology. The successful application of the forecast methodology to the flood-prone Karnali River basin in western Nepal is outlined, increasing lead times from 2-3 to 7-8 h. The challenges faced in communicating probabilistic forecasts to the last mile of the existing community-based early warning systems across Nepal is discussed. The paper concludes with an assessment of the applicability of this approach in basins and countries beyond Karnali and Nepal and an overview of key lessons learnt from this initiative.

Forecast Vienna Mapping Functions 1 for real-time analysis of space geodetic observations

NASA Astrophysics Data System (ADS)

Boehm, J.; Kouba, J.; Schuh, H.

2009-05-01

The Vienna Mapping Functions 1 (VMF1) as provided by the Institute of Geodesy and Geophysics (IGG) at the Vienna University of Technology are the most accurate mapping functions for the troposphere delays that are available globally and for the entire history of space geodetic observations. So far, the VMF1 coefficients have been released with a time delay of almost two days; however, many scientific applications require their availability in near real-time, e.g. the Ultra Rapid solutions of the International GNSS Service (IGS) or the analysis of the Intensive sessions of the International VLBI Service (IVS). Here we present coefficients of the VMF1 as well as the hydrostatic and wet zenith delays that have been determined from forecasting data of the European Centre for Medium-Range Weather Forecasts (ECMWF) and provided on global grids. The comparison with parameters derived from ECMWF analysis data shows that the agreement is at the 1 mm level in terms of station height, and that the differences are larger for the wet mapping functions than for the hydrostatic mapping functions and the hydrostatic zenith delays. These new products (VMF1-FC and hydrostatic zenith delays from forecast data) can be used in real-time analysis of geodetic data without significant loss of accuracy.

Waste information management system: a web-based system for DOE waste forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geisler, T.J.; Shoffner, P.A.; Upadhyay, U.

2007-07-01

The implementation of the Department of Energy (DOE) mandated accelerated cleanup program has created significant potential technical impediments that must be overcome. The schedule compression will require close coordination and a comprehensive review and prioritization of the barriers that may impede treatment and disposition of the waste streams at each site. Many issues related to site waste treatment and disposal have now become potential critical path issues under the accelerated schedules. In order to facilitate accelerated cleanup initiatives, waste managers at DOE field sites and at DOE headquarters in Washington, D.C., need timely waste forecast information regarding the volumes andmore » types of waste that will be generated by DOE sites over the next 25 years. Each local DOE site has historically collected, organized, and displayed site waste forecast information in separate and unique systems. However, waste information from all sites needs a common application to allow interested parties to understand and view the complete complex-wide picture. A common application would allow identification of total waste volumes, material classes, disposition sites, choke points, and technological or regulatory barriers to treatment and disposal. The Applied Research Center (ARC) at Florida International University (FIU) in Miami, Florida, has completed the development of this web-based forecast system. (authors)« less

Role of the Internet in Anticipating and Mitigating Earthquake Catastrophes, and the Emergence of Personal Risk Management (Invited)

NASA Astrophysics Data System (ADS)

Rundle, J. B.; Holliday, J. R.; Donnellan, A.; Graves, W.; Tiampo, K. F.; Klein, W.

2009-12-01

Risks from natural and financial catastrophes are currently managed by a combination of large public and private institutions. Public institutions usually are comprised of government agencies that conduct studies, formulate policies and guidelines, enforce regulations, and make “official” forecasts. Private institutions include insurance and reinsurance companies, and financial service companies that underwrite catastrophe (“cat”) bonds, and make private forecasts. Although decisions about allocating resources and developing solutions are made by large institutions, the costs of dealing with catastrophes generally fall for the most part on businesses and the general public. Information on potential risks is generally available to the public for some hazards but not others. For example, in the case of weather, private forecast services are provided by www.weather.com and www.wunderground.com. For earthquakes in California (only), the official forecast is the WGCEP-USGS forecast, but provided in a format that is difficult for the public to use. Other privately made forecasts are currently available, for example by the JPL QuakeSim and Russian groups, but these efforts are limited. As more of the world’s population moves increasingly into major seismic zones, new strategies are needed to allow individuals to manage their personal risk from large and damaging earthquakes. Examples include individual mitigation measures such as retrofitting, as well as microinsurance in both developing and developed countries, as well as other financial strategies. We argue that the “long tail” of the internet offers an ideal, and greatly underutilized mechanism to reach out to consumers and to provide them with the information and tools they need to confront and manage seismic hazard and risk on an individual, personalized basis. Information of this type includes not only global hazard forecasts, which are now possible, but also global risk estimation. Additionally, social networking tools are available that will allow self-organizing, disaster-resilient communities to arise as emergent structures from the underlying nonlinear social dynamics. In this talk, we argue that the current style of risk management is not making adequate use of modern internet technology, and that significantly more can be done. We suggest several avenues to proceed, in particular making use of the internet for earthquake forecast and information delivery, as well as tracking forecast validation and verification on a real-time basis. We also show examples of forecasts delivered over the internet, and describe how these are made.

Measuring real-time streamflow using emerging technologies: Radar, hydroacoustics, and the probability concept

NASA Astrophysics Data System (ADS)

Fulton, John; Ostrowski, Joseph

2008-07-01

SummaryForecasting streamflow during extreme hydrologic events such as floods can be problematic. This is particularly true when flow is unsteady, and river forecasts rely on models that require uniform-flow rating curves to route water from one forecast point to another. As a result, alternative methods for measuring streamflow are needed to properly route flood waves and account for inertial and pressure forces in natural channels dominated by nonuniform-flow conditions such as mild water surface slopes, backwater, tributary inflows, and reservoir operations. The objective of the demonstration was to use emerging technologies to measure instantaneous streamflow in open channels at two existing US Geological Survey streamflow-gaging stations in Pennsylvania. Surface-water and instream-point velocities were measured using hand-held radar and hydroacoustics. Streamflow was computed using the probability concept, which requires velocity data from a single vertical containing the maximum instream velocity. The percent difference in streamflow at the Susquehanna River at Bloomsburg, PA ranged from 0% to 8% with an average difference of 4% and standard deviation of 8.81 m 3/s. The percent difference in streamflow at Chartiers Creek at Carnegie, PA ranged from 0% to 11% with an average difference of 5% and standard deviation of 0.28 m 3/s. New generation equipment is being tested and developed to advance the use of radar-derived surface-water velocity and instantaneous streamflow to facilitate the collection and transmission of real-time streamflow that can be used to parameterize hydraulic routing models.

Measuring real-time streamflow using emerging technologies: Radar, hydroacoustics, and the probability concept

USGS Publications Warehouse

Fulton, J.; Ostrowski, J.

2008-01-01

Forecasting streamflow during extreme hydrologic events such as floods can be problematic. This is particularly true when flow is unsteady, and river forecasts rely on models that require uniform-flow rating curves to route water from one forecast point to another. As a result, alternative methods for measuring streamflow are needed to properly route flood waves and account for inertial and pressure forces in natural channels dominated by nonuniform-flow conditions such as mild water surface slopes, backwater, tributary inflows, and reservoir operations. The objective of the demonstration was to use emerging technologies to measure instantaneous streamflow in open channels at two existing US Geological Survey streamflow-gaging stations in Pennsylvania. Surface-water and instream-point velocities were measured using hand-held radar and hydroacoustics. Streamflow was computed using the probability concept, which requires velocity data from a single vertical containing the maximum instream velocity. The percent difference in streamflow at the Susquehanna River at Bloomsburg, PA ranged from 0% to 8% with an average difference of 4% and standard deviation of 8.81 m3/s. The percent difference in streamflow at Chartiers Creek at Carnegie, PA ranged from 0% to 11% with an average difference of 5% and standard deviation of 0.28 m3/s. New generation equipment is being tested and developed to advance the use of radar-derived surface-water velocity and instantaneous streamflow to facilitate the collection and transmission of real-time streamflow that can be used to parameterize hydraulic routing models.

GPS Technologies as a Tool to Detect the Pre-Earthquake Signals Associated with Strong Earthquakes

NASA Astrophysics Data System (ADS)

Pulinets, S. A.; Krankowski, A.; Hernandez-Pajares, M.; Liu, J. Y. G.; Hattori, K.; Davidenko, D.; Ouzounov, D.

2015-12-01

The existence of ionospheric anomalies before earthquakes is now widely accepted. These phenomena started to be considered by GPS community to mitigate the GPS signal degradation over the territories of the earthquake preparation. The question is still open if they could be useful for seismology and for short-term earthquake forecast. More than decade of intensive studies proved that ionospheric anomalies registered before earthquakes are initiated by processes in the boundary layer of atmosphere over earthquake preparation zone and are induced in the ionosphere by electromagnetic coupling through the Global Electric Circuit. Multiparameter approach based on the Lithosphere-Atmosphere-Ionosphere Coupling model demonstrated that earthquake forecast is possible only if we consider the final stage of earthquake preparation in the multidimensional space where every dimension is one from many precursors in ensemble, and they are synergistically connected. We demonstrate approaches developed in different countries (Russia, Taiwan, Japan, Spain, and Poland) within the framework of the ISSI and ESA projects) to identify the ionospheric precursors. They are also useful to determine the all three parameters necessary for the earthquake forecast: impending earthquake epicenter position, expectation time and magnitude. These parameters are calculated using different technologies of GPS signal processing: time series, correlation, spectral analysis, ionospheric tomography, wave propagation, etc. Obtained results from different teams demonstrate the high level of statistical significance and physical justification what gives us reason to suggest these methodologies for practical validation.

Modeling timelines for translational science in cancer; the impact of technological maturation

PubMed Central

McNamee, Laura M.; Ledley, Fred D.

2017-01-01

This work examines translational science in cancer based on theories of innovation that posit a relationship between the maturation of technologies and their capacity to generate successful products. We examined the growth of technologies associated with 138 anticancer drugs using an analytical model that identifies the point of initiation of exponential growth and the point at which growth slows as the technology becomes established. Approval of targeted and biological products corresponded with technological maturation, with first approval averaging 14 years after the established point and 44 years after initiation of associated technologies. The lag in cancer drug approvals after the increases in cancer funding and dramatic scientific advances of the 1970s thus reflects predictable timelines of technology maturation. Analytical models of technological maturation may be used for technological forecasting to guide more efficient translation of scientific discoveries into cures. PMID:28346525

Prioritization methodology for chemical replacement

NASA Technical Reports Server (NTRS)

Goldberg, Ben; Cruit, Wendy; Schutzenhofer, Scott

1995-01-01

This methodology serves to define a system for effective prioritization of efforts required to develop replacement technologies mandated by imposed and forecast legislation. The methodology used is a semi quantitative approach derived from quality function deployment techniques (QFD Matrix). QFD is a conceptual map that provides a method of transforming customer wants and needs into quantitative engineering terms. This methodology aims to weight the full environmental, cost, safety, reliability, and programmatic implications of replacement technology development to allow appropriate identification of viable candidates and programmatic alternatives.

Knowledge/Data Mining, Assessment and Forecasting of Ground Military Vehicle Technologies

DTIC Science & Technology

2010-06-11

Equipment • Commercial Technology  Evaluations • University Partnerships • International Cooperative R&D • Manufacturing  / Industrial Base... manufacturing of industry successfully solved the blade pitting problem – Excellent adhesion properties of thin films  Conclusion • Current...10. Pre‐action • Partially cured prepreg • Assembly line  manufacture  for automobiles inspired by the watch  making industry. • Sterilized medical

Impact Assessment and Forecasts of Information and Telecommunications Technologies Applied to Education and Training: Volume III--Annex & Glossary. Analysis of Key Issues for the Orientation of the Work of Sector Actors in the Framework of DELTA.

ERIC Educational Resources Information Center

Commission of the European Communities, Brussels (Belgium).

This annex to the main report, the third volume in a three volume set, is based on a study performed by the DELTA (Developing European Learning through Technological Advance) unit in parallel with the projects underway in the research and development Exploratory Action. It provides an assessment of the world situation in flexible and distance…

Dielectric and Insulating Technology 2004 : Review & Forecast

NASA Astrophysics Data System (ADS)

Okamoto, Tatsuki

This article reports the state-of-art of DEIS activites. DEIS activiteis are basically based on the activites of 8-10 investigation committees’ under DEIS committee. Recent DEIS activites are categlized into three functions in this article and remarkable activity or trend of each category is mentioned. Those are activities on insulation diagnosis (AI application and asset management), activities on new insulation technology for power tansmission (high Tc super conducting cable insulation and all solid sinulated substation), and activities on new insulating materials (Nanocomposite).

Proceedings of the American Power Conference. Volume 58-I

DOE Office of Scientific and Technical Information (OSTI.GOV)

McBride, A.E.

1996-10-01

This is volume 58-I of the proceedings of the American Power Conference, 1996, Technology for Competition and Globalization. The topics of the papers include power plant DC issues; cost of environmental compliance; advanced coal systems -- environmental performance; technology for competition in dispersed generation; superconductivity technologies for electric utility applications; power generation trends and challenges in China; aging in nuclear power plants; innovative and competitive repowering options; structural examinations, modifications and repairs; electric load forecasting; distribution planning; EMF effects; fuzzy logic and neural networks for power plant applications; electrokinetic decontamination of soils; integrated gasification combined cycle; advances in fusion; coolingmore » towers; relays; plant controls; flue gas desulfurization; waste product utilization; and improved technologies.« less

Towards Developing a Regional Drought Information System for Lower Mekong

NASA Astrophysics Data System (ADS)

Dutta, R.; Jayasinghe, S.; Basnayake, S. B.; Apirumanekul, C.; Pudashine, J.; Granger, S. L.; Andreadis, K.; Das, N. N.

2016-12-01

With the climate and weather patterns changing over the years, the Lower Mekong Basin have been experiencing frequent and prolonged droughts resulting in severe damage to the agricultural sector affecting food security and livelihoods of the farming community. However, the Regional Drought Information System (RDIS) for Lower Mekong countries would help prepare vulnerable communities from frequent and severe droughts through monitoring, assessing and forecasting of drought conditions and allowing decision makers to take effective decisions in terms of providing early warning, incentives to farmers, and adjustments to cropping calendars and so on. The RDIS is an integrated system that is being designed for drought monitoring, analysis and forecasting based on the need to meet the growing demand of an effective monitoring system for drought by the lower Mekong countries. The RDIS is being built on four major components that includes earth observation component, meteorological data component, database storage and Regional Hydrologic Extreme Assessment System (RHEAS) framework while the outputs from the system will be made open access to the public through a web-based user interface. The system will run on the RHEAS framework that allows both nowcasting and forecasting using hydrological and crop simulation models such as the Variable Infiltration Capacity (VIC) model and the Decision Support System for Agro-Technology Transfer (DSSAT) model respectively. The RHEAS allows for a tightly constrained observation based drought and crop yield information system that can provide customized outputs on drought that includes root zone soil moisture, Standard Precipitation Index (SPI), Standard Runoff Index (SRI), Palmer Drought Severity Index (PDSI) and Crop Yield and can integrate remote sensing products, along with evapotranspiration and soil moisture data. The anticipated outcomes from the RDIS is to improve the operational, technological and institutional capabilities of lower Mekong countries to prepare for and respond towards drought situations and providing policy makers with current and forecast drought indices for decision making on adjusting cropping calendars as well as planning short and long term mitigation measures.

Forecasting Propagation and Evolution of CMEs in an Operational Setting: What Has Been Learned

NASA Technical Reports Server (NTRS)

Zheng, Yihua; Macneice, Peter; Odstrcil, Dusan; Mays, M. L.; Rastaetter, Lutz; Pulkkinen, Antti; Taktakishvili, Aleksandre; Hesse, Michael; Kuznetsova, M. Masha; Lee, Hyesook;

Forecasting Optimal Solar Energy Supply in Jiangsu Province (China): A Systematic Approach Using Hybrid of Weather and Energy Forecast Models

PubMed Central

Zhao, Xiuli; Yiranbon, Ethel

2014-01-01

The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, “least-cost,” and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor. PMID:24511292

Forecasting propagation and evolution of CMEs in an operational setting: What has been learned

NASA Astrophysics Data System (ADS)

Zheng, Yihua; Macneice, Peter; Odstrcil, Dusan; Mays, M. L.; Rastaetter, Lutz; Pulkkinen, Antti; Taktakishvili, Aleksandre; Hesse, Michael; Masha Kuznetsova, M.; Lee, Hyesook; Chulaki, Anna

2013-10-01

of the major types of solar eruption, coronal mass ejections (CMEs) not only impact space weather, but also can have significant societal consequences. CMEs cause intense geomagnetic storms and drive fast mode shocks that accelerate charged particles, potentially resulting in enhanced radiation levels both in ions and electrons. Human and technological assets in space can be endangered as a result. CMEs are also the major contributor to generating large amplitude Geomagnetically Induced Currents (GICs), which are a source of concern for power grid safety. Due to their space weather significance, forecasting the evolution and impacts of CMEs has become a much desired capability for space weather operations worldwide. Based on our operational experience at Space Weather Research Center at NASA Goddard Space Flight Center (http://swrc.gsfc.nasa.gov), we present here some of the insights gained about accurately predicting CME impacts, particularly in relation to space weather operations. These include: 1. The need to maximize information to get an accurate handle of three-dimensional (3-D) CME kinetic parameters and therefore improve CME forecast; 2. The potential use of CME simulation results for qualitative prediction of regions of space where solar energetic particles (SEPs) may be found; 3. The need to include all CMEs occurring within a 24 h period for a better representation of the CME interactions; 4. Various other important parameters in forecasting CME evolution in interplanetary space, with special emphasis on the CME propagation direction. It is noted that a future direction for our CME forecasting is to employ the ensemble modeling approach.

Monitoring and forecasting of great radiation hazards for spacecraft and aircrafts by online cosmic ray data

NASA Astrophysics Data System (ADS)

Dorman, L. I.

2005-11-01

We show that an exact forecast of great radiation hazard in space, in the magnetosphere, in the atmosphere and on the ground can be made by using high-energy particles (few GeV/nucleon and higher) whose transportation from the Sun is characterized by a much bigger diffusion coefficient than for small and middle energy particles. Therefore, high energy particles come from the Sun much earlier (8-20 min after acceleration and escaping into solar wind) than the main part of smaller energy particles (more than 30-60 min later), causing radiation hazard for electronics and personal health, as well as spacecraft and aircrafts. We describe here principles of an automatic set of programs that begin with "FEP-Search", used to determine the beginning of a large FEP event. After a positive signal from "FEP-Search", the following programs start working: "FEP-Research/Spectrum", and then "FEP-Research/Time of Ejection", "FEP-Research /Source" and "FEP-Research/Diffusion", which online determine properties of FEP generation and propagation. On the basis of the obtained information, the next set of programs immediately start to work: "FEP-Forecasting/Spacecrafts", "FEP-Forecasting/Aircrafts", "FEP-Forecasting/Ground", which determine the expected differential and integral fluxes and total fluency for spacecraft on different orbits, aircrafts on different airlines, and on the ground, depending on altitude and cutoff rigidity. If the level of radiation hazard is expected to be dangerous for high level technology or/and personal health, the following programs will be used "FEP-Alert/Spacecrafts", "FEP-Alert/ Aircrafts", "FEP-Alert/Ground".

Forecasting optimal solar energy supply in Jiangsu Province (China): a systematic approach using hybrid of weather and energy forecast models.

PubMed

Zhao, Xiuli; Asante Antwi, Henry; Yiranbon, Ethel

2014-01-01

The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, "least-cost," and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.

Operational Numerical Weather Prediction at the Met Office and potential ways forward for operational space weather prediction systems

NASA Astrophysics Data System (ADS)

Jackson, David

NICT (National Institute of Information and Communications Technology) has been in charge of space weather forecast service in Japan for more than 20 years. The main target region of the space weather is the geo-space in the vicinity of the Earth where human activities are dominant. In the geo-space, serious damages of satellites, international space stations and astronauts take place caused by energetic particles or electromagnetic disturbances: the origin of the causes is dynamically changing of solar activities. Positioning systems via GPS satellites are also im-portant recently. Since the most significant effect of positioning error comes from disturbances of the ionosphere, it is crucial to estimate time-dependent modulation of the electron density profiles in the ionosphere. NICT is one of the 13 members of the ISES (International Space Environment Service), which is an international assembly of space weather forecast centers under the UNESCO. With help of geo-space environment data exchanging among the member nations, NICT operates daily space weather forecast service every day to provide informa-tion on forecasts of solar flare, geomagnetic disturbances, solar proton event, and radio-wave propagation conditions in the ionosphere. The space weather forecast at NICT is conducted based on the three methodologies: observations, simulations and informatics (OSI model). For real-time or quasi real-time reporting of space weather, we conduct our original observations: Hiraiso solar observatory to monitor the solar activity (solar flare, coronal mass ejection, and so on), domestic ionosonde network, magnetometer HF radar observations in far-east Siberia, and south-east Asia low-latitude ionosonde network (SEALION). Real-time observation data to monitor solar and solar-wind activities are obtained through antennae at NICT from ACE and STEREO satellites. We have a middle-class super-computer (NEC SX-8R) to maintain real-time computer simulations for solar and solar-wind, magnetosphere and ionosphere. The three simulations are directly or indirectly connected each other based on real-time observa-tion data to reproduce a virtual geo-space region on the super-computer. Informatics is a new methodology to make precise forecast of space weather. Based on new information and communication technologies (ICT), it provides more information in both quality and quantity. At NICT, we have been developing a cloud-computing system named "space weather cloud" based on a high-speed network system (JGN2+). Huge-scale distributed storage (1PB), clus-ter computers, visualization systems and other resources are expected to derive new findings and services of space weather forecasting. The final goal of NICT space weather service is to predict near-future space weather conditions and disturbances which will be causes of satellite malfunctions, tele-communication problems, and error of GPS navigations. In the present talk, we introduce our recent activities on the space weather services and discuss how we are going to develop the services from the view points of space science and practical uses.

Activities of NICT space weather project

NASA Astrophysics Data System (ADS)

Murata, Ken T.; Nagatsuma, Tsutomu; Watari, Shinichi; Shinagawa, Hiroyuki; Ishii, Mamoru

NICT (National Institute of Information and Communications Technology) has been in charge of space weather forecast service in Japan for more than 20 years. The main target region of the space weather is the geo-space in the vicinity of the Earth where human activities are dominant. In the geo-space, serious damages of satellites, international space stations and astronauts take place caused by energetic particles or electromagnetic disturbances: the origin of the causes is dynamically changing of solar activities. Positioning systems via GPS satellites are also im-portant recently. Since the most significant effect of positioning error comes from disturbances of the ionosphere, it is crucial to estimate time-dependent modulation of the electron density profiles in the ionosphere. NICT is one of the 13 members of the ISES (International Space Environment Service), which is an international assembly of space weather forecast centers under the UNESCO. With help of geo-space environment data exchanging among the member nations, NICT operates daily space weather forecast service every day to provide informa-tion on forecasts of solar flare, geomagnetic disturbances, solar proton event, and radio-wave propagation conditions in the ionosphere. The space weather forecast at NICT is conducted based on the three methodologies: observations, simulations and informatics (OSI model). For real-time or quasi real-time reporting of space weather, we conduct our original observations: Hiraiso solar observatory to monitor the solar activity (solar flare, coronal mass ejection, and so on), domestic ionosonde network, magnetometer HF radar observations in far-east Siberia, and south-east Asia low-latitude ionosonde network (SEALION). Real-time observation data to monitor solar and solar-wind activities are obtained through antennae at NICT from ACE and STEREO satellites. We have a middle-class super-computer (NEC SX-8R) to maintain real-time computer simulations for solar and solar-wind, magnetosphere and ionosphere. The three simulations are directly or indirectly connected each other based on real-time observa-tion data to reproduce a virtual geo-space region on the super-computer. Informatics is a new methodology to make precise forecast of space weather. Based on new information and communication technologies (ICT), it provides more information in both quality and quantity. At NICT, we have been developing a cloud-computing system named "space weather cloud" based on a high-speed network system (JGN2+). Huge-scale distributed storage (1PB), clus-ter computers, visualization systems and other resources are expected to derive new findings and services of space weather forecasting. The final goal of NICT space weather service is to predict near-future space weather conditions and disturbances which will be causes of satellite malfunctions, tele-communication problems, and error of GPS navigations. In the present talk, we introduce our recent activities on the space weather services and discuss how we are going to develop the services from the view points of space science and practical uses.

Student Activities in Meteorology: SAM. Version 2.

ERIC Educational Resources Information Center

Meier, Beverly L.; Passarelli, Elisa

The task of providing hands-on as well as minds-on activities for students in science is one of concern to many scientists and educators. In an effort to inspire student interest in science and technology, scientists from the Forecast Systems Laboratory, a laboratory within the National Oceanic and Atmospheric Administration's (NOAA) Environmental…

A Primer on Applying Monte Carlo Simulation, Real Options Analysis, Knowledge Value Added, Forecasting, and Portfolio Optimization

DTIC Science & Technology

2010-02-08

popular pastime. Even in Biblical accounts, Roman soldiers cast lots for Christ’s robes. In earlier times, chance was something that occurred in nature...with the advent of blazing fast computing technology, our modern world of uncertainty can be explained with much more elegance through

Rural land mobile radio market assessment and satellite and terrestrial system concepts

NASA Technical Reports Server (NTRS)

Stevenson, S. M.; Provencher, C. E.

1984-01-01

Market potential exists; the nature of the market in terms of service needs, usage characteristics, service requirements, and forecasting the demand to the year 2000; alternative system cncepts that show promise in addressing the identified needs, in a cost effective manner; and advanced technology requirements associated with these concepts are considered.

Social Effects of Prospective Population Changes in the United States.

ERIC Educational Resources Information Center

Kirk, Dudley

Unlike many population forecasts, the thesis of this paper is that present and prospective effects of population growth in the United States have been exaggerated in comparison with other aspects of population change. The effects of national population growth have been confused with those of growing affluence, changing technology, and…

SURVEY OF INFORMATION ON VOCATIONAL AND TECHNICAL EDUCATION IN THE STATE OF ILLINOIS. FINAL REPORT.

ERIC Educational Resources Information Center

Corplan Associates, Chicago, IL. Technology Center.

THE BASIC OBJECTIVE OF THE SURVEY WAS TO GATHER INFORMATION HELPFUL IN PLANNING AND DEVELOPING VOCATIONAL AND TECHNICAL EDUCATION PRIMARILY WITHIN THE PUBLIC SCHOOL SYSTEM. OCCUPATIONAL NEEDS WERE IDENTIFIED FROM FORECASTS OF CHANGES IN CURRENT OCCUPATIONS, AN ANALYSIS OF THE IMPLICATIONS OF SCIENTIFIC AND TECHNOLOGICAL DEVELOPMENTS, AND…

Technical Processing Librarians in the 1980's: Current Trends and Future Forecasts.

ERIC Educational Resources Information Center

Kennedy, Gail

1980-01-01

This review of recent and anticipated advances in library automation technology and methodology includes a review of the effects of OCLC, MARC formatting, AACR2, and increasing costs, as well as predictions of the impact on library technical processing of networking, expansion of automation, minicomputers, specialized reference services, and…

Building Technology Forecast and Evaluation (BTFE). Volume 2. Evaluation of Two Structural Systems

DTIC Science & Technology

1990-11-01

insulative foam ( expanded polystyrene ) strips between each truss. The assembly is held together with 14-gauge wires welded to the trusses on 2-in. centers...structural load bearing qualities expanded polystyrene . No taping and mudding. Ar. ~J~ .wplrtpd( at each irllnfrnPllo Tile I hin- set or float over

Tutorial Video Series: Using Stakeholder Outreach to Increase Usage of ToxCast Data (SETAC EU)

EPA Science Inventory

The limited amount of toxicity data on thousands of chemicals found in consumer products has led to the development of research endeavors such as the U.S. EPA’s Toxicity Forecaster (ToxCast). ToxCast uses high-throughput screening technology to evaluate thousands of chemicals for...

Film Scenes in Interdisciplinary Education: Teaching the Internet of Things

ERIC Educational Resources Information Center

Hwang, Young-mee; Kim, Kwang-sun; Im, Tami

2017-01-01

The Internet of Things (IoT) is gaining importance in education owing to its rapid development. This study addresses the importance of interdisciplinary education between technology and the humanities. The use of films as a teaching resource is suitable for interdisciplinary education because films represent creative forecasts and predictions on…

Industrial Technology Modernization Program. Project 44. Modernize Facility Equipment and Processes. Volume 2. Revision 2. Phase 2

DTIC Science & Technology

1988-05-01

not be implemented. A change in foreign exchange rates (which increase the equipment cost) and a reduction in marketing forecast resulted in an...project will not be implemented due to unfavorable changes in foreign exchange rates (which increase the equipment costs) and a reduction in market

Forecasting Sectors, Occupational Activities and Qualifications in the Federal Republic of Germany. A Survey on Research Activities and Recent Findings.

ERIC Educational Resources Information Center

Tessaring, Manfred

In view of German reunification, the 1992-94 recession, and ongoing demographic, technological, organizational, and social changes, alternative projections of labor market and employment structures provide policy makers with needed information. The Institut fur Arbeitsmarkt- und Berufsforschung (IAB) structural labor projection (1989) forecasted…

Automated information-analytical system for thunderstorm monitoring and early warning alarms using modern physical sensors and information technologies with elements of artificial intelligence

NASA Astrophysics Data System (ADS)

Boldyreff, Anton S.; Bespalov, Dmitry A.; Adzhiev, Anatoly Kh.

2017-05-01

Methods of artificial intelligence are a good solution for weather phenomena forecasting. They allow to process a large amount of diverse data. Recirculation Neural Networks is implemented in the paper for the system of thunderstorm events prediction. Large amounts of experimental data from lightning sensors and electric field mills networks are received and analyzed. The average recognition accuracy of sensor signals is calculated. It is shown that Recirculation Neural Networks is a promising solution in the forecasting of thunderstorms and weather phenomena, characterized by the high efficiency of the recognition elements of the sensor signals, allows to compress images and highlight their characteristic features for subsequent recognition.

Study on Capturing Functional Requirements of the New Product Based on Evolution

NASA Astrophysics Data System (ADS)

Liu, Fang; Song, Liya; Bai, Zhonghang; Zhang, Peng

In order to exist in an increasingly competitive global marketplace, it is important for corporations to forecast the evolutionary direction of new products rapidly and effectively. Most products in the world are developed based on the design of existing products. In the product design, capturing functional requirements is a key step. Function is continuously evolving, which is driven by the evolution of needs and technologies. So the functional requirements of new product can be forecasted based on the functions of existing product. Eight laws of function evolution are put forward in this paper. The process model of capturing the functional requirements of new product based on function evolution is proposed. An example illustrates the design process.

Real time hydro-metereological hazards monitoring system for the Ravenna municipality

NASA Astrophysics Data System (ADS)

Bertoni, W.; Cattarossi, A.; Gonella, M.

2003-04-01

The Ravenna municipality (Italy, Emilia Romagna region), through a cooperative agreement with ENI S.p.A’s., AGIP division, is carrying out a research study for the development of a real time monitoring system of hydro-meteorological conditions. The system aims to support the city Crisis Response Unit to provide more efficient support all over the municipal territory that is the largest in Italy with more than 700 km2. The support unit, a GIS computer based application, directly links to a broad range of sources, gathering real time information from a Local Area Model (meteorological data), a Wave Model (sea hydrodynamic circulation), monitoring stations, located partially on the Adriatic sea (AGIP offshore platform, SIMN) and partially over the Ravenna inland (SPDS, SIN). In the first phase, now completed and undergoing testing, this vast and diversified collection of data feeds a number of statistical models with up to 72 hours of forecast capabilities. The GIS application displays actual and forecast sea conditions offshore of Ravenna littorals in addition to actual and forecast flood conditions along the Ravenna Province inland. Model generated data are used for the forecast, which is then calibrated using the measured data. When the predefined warning limits are exceeded, end users are alerted via prerecorded phone messages, SMS, or visually through the direct or remote interaction with the GIS system (remotely accessible via portable computers). In the second stage, the statistical approach will be substituted by a more deterministic approach. A coupled hydrologic-hydraulic model will be used to forecast water stages along rivers and runoff volume along major watersheds. Moreover, already functioning capabilities allows direct control of remote monitoring points (stream and rain gages, etc.) The entire Real Time Monitoring System was developed on a GIS platform. The GEOdatabase, a relational database based on MSDE technology, is the core of the application which revolves around the conceptualization of a Hydro Data Model, a standardized way to store hydraulic based data such as watershed delineation, hydrologic network, monitoring points and time series data. Recent advancement in GIS software technologies and ready to use hydro-meteorological data offer an unprecedented opportunity to customize the GIS application and provide a powerful application to prevent and defeat flood hazards.

Advanced space program studies. Overall executive summary

NASA Technical Reports Server (NTRS)

Wolfe, M. G.

1977-01-01

NASA and DoD requirements and planning data were used in multidiscipline advanced planning investigations of space operations and associated elements (including man), identification of potential low cost approaches, vehicle design, cost synthesis techniques, technology forecasting and opportunities for DoD technology transfer, and the development near-, mid-, and far-term space initiatives and development plans with emphasis on domestic and military commonality. An overview of objectives and results are presented for the following studies: advanced space planning and conceptual analysis, shuttle users, technology assessment and new opportunities, standardization and program practice, integrated STS operations planning, solid spinning upper stage, and integrated planning support functions.

Induced pluripotent stem cells meet genome editing

PubMed Central

Hockemeyer, Dirk; Jaenisch, Rudolf

2016-01-01

It is extremely rare for a single experiment to be so impactful and timely that it shapes and forecasts the experiments of the next decade. Here, we review how two such experiments --the generation of human induced pluripotent stem cells (iPSCs) and the development of CRISPR/Cas9 technology-- have fundamentally reshaped our approach to biomedical research, stem cell biology and human genetics. We will also highlight the previous knowledge that iPSC and CRISPR/Cas9 technologies were built on as this groundwork demonstrated the need for solutions and the benefits that these technologies provided, and have set the stage for their success. PMID:27152442

Induced Pluripotent Stem Cells Meet Genome Editing.

PubMed

Hockemeyer, Dirk; Jaenisch, Rudolf

2016-05-05

It is extremely rare for a single experiment to be so impactful and timely that it shapes and forecasts the experiments of the next decade. Here, we review how two such experiments-the generation of human induced pluripotent stem cells (iPSCs) and the development of CRISPR/Cas9 technology-have fundamentally reshaped our approach to biomedical research, stem cell biology, and human genetics. We will also highlight the previous knowledge that iPSC and CRISPR/Cas9 technologies were built on as this groundwork demonstrated the need for solutions and the benefits that these technologies provided and set the stage for their success. Copyright © 2016 Elsevier Inc. All rights reserved.

Giant step for communication satellite technology

NASA Technical Reports Server (NTRS)

Lovell, R. R.

1984-01-01

NASA's communications program, which is concerned with advanced communications technology, reflects the need for operational communications satellite capacity beyond the capabilities of current technology and the unwillingness of private industry in the U.S. to undertake making the required long-range, high-risk technology advances. It is pointed out that current satellites will not satisfy the forecasted demand for additional capacity in the 1990s and beyond. Current technology exists primarily up to 18 GHz. Designing a communications satellite at each of the three major uplink/downlink frequency bands (C, Ku, and Ka, 6/4 GHz, 14/11 GHz, and 30/20 GHz, respectively) presents different program management and technical problems. Increasing frequency or power can be done only by intensive sustained research. This is the rationale for NASA to pursue the Advanced Communications Technology Satellite (ACTS) program.

Giant step for communication satellite technology

NASA Astrophysics Data System (ADS)

Lovell, R. R.

1984-03-01

NASA's communications program, which is concerned with advanced communications technology, reflects the need for operational communications satellite capacity beyond the capabilities of current technology and the unwillingness of private industry in the U.S. to undertake making the required long-range, high-risk technology advances. It is pointed out that current satellites will not satisfy the forecasted demand for additional capacity in the 1990s and beyond. Current technology exists primarily up to 18 GHz. Designing a communications satellite at each of the three major uplink/downlink frequency bands (C, Ku, and Ka, 6/4 GHz, 14/11 GHz, and 30/20 GHz, respectively) presents different program management and technical problems. Increasing frequency or power can be done only by intensive sustained research. This is the rationale for NASA to pursue the Advanced Communications Technology Satellite (ACTS) program.

On the future of carbonaceous aerosol emissions

NASA Astrophysics Data System (ADS)

Streets, D. G.; Bond, T. C.; Lee, T.; Jang, C.

2004-12-01

This paper presents the first model-based forecasts of future emissions of the primary carbonaceous aerosols, black carbon (BC) and organic carbon (OC). The forecasts build on a recent 1996 inventory of emissions that contains detailed fuel, technology, sector, and world-region specifications. The forecasts are driven by four IPCC scenarios, A1B, A2, B1, and B2, out to 2030 and 2050, incorporating not only changing patterns of fuel use but also technology development. Emissions from both energy generation and open biomass burning are included. We project that global BC emissions will decline from 8.0 Tg in 1996 to 5.3-7.3 Tg by 2030 and to 4.3-6.1 Tg by 2050, across the range of scenarios. We project that OC emissions will decline from 34 Tg in 1996 to 24-30 Tg by 2030 and to 21-28 Tg by 2050. The introduction of advanced technology with lower emission rates, as well as a shift away from the use of traditional solid fuels in the residential sector, more than offsets the increased combustion of fossil fuels worldwide. Environmental pressures and a diminishing demand for new agricultural land lead to a slow decline in the amount of open biomass burning. Although emissions of BC and OC are generally expected to decline around the world, some regions, particularly South America, northern Africa, the Middle East, South Asia, Southeast Asia, and Oceania, show increasing emissions in several scenarios. Particularly difficult to control are BC emissions from the transport sector, which increase under most scenarios. We expect that the BC/OC emission ratio for energy sources will rise from 0.5 to as much as 0.8, signifying a shift toward net warming of the climate system due to carbonaceous aerosols. When biomass burning is included, however, the BC/OC emission ratios are for the most part invariant across scenarios at about 0.2.

Illustrating anticipatory life cycle assessment for emerging photovoltaic technologies.

PubMed

Wender, Ben A; Foley, Rider W; Prado-Lopez, Valentina; Ravikumar, Dwarakanath; Eisenberg, Daniel A; Hottle, Troy A; Sadowski, Jathan; Flanagan, William P; Fisher, Angela; Laurin, Lise; Bates, Matthew E; Linkov, Igor; Seager, Thomas P; Fraser, Matthew P; Guston, David H

2014-09-16

Current research policy and strategy documents recommend applying life cycle assessment (LCA) early in research and development (R&D) to guide emerging technologies toward decreased environmental burden. However, existing LCA practices are ill-suited to support these recommendations. Barriers related to data availability, rapid technology change, and isolation of environmental from technical research inhibit application of LCA to developing technologies. Overcoming these challenges requires methodological advances that help identify environmental opportunities prior to large R&D investments. Such an anticipatory approach to LCA requires synthesis of social, environmental, and technical knowledge beyond the capabilities of current practices. This paper introduces a novel framework for anticipatory LCA that incorporates technology forecasting, risk research, social engagement, and comparative impact assessment, then applies this framework to photovoltaic (PV) technologies. These examples illustrate the potential for anticipatory LCA to prioritize research questions and help guide environmentally responsible innovation of emerging technologies.

Improving the Forecast Accuracy of an Ocean Observation and Prediction System by Adaptive Control of the Sensor Network

NASA Astrophysics Data System (ADS)

Talukder, A.; Panangadan, A. V.; Blumberg, A. F.; Herrington, T.; Georgas, N.

2008-12-01

The New York Harbor Observation and Prediction System (NYHOPS) is a real-time, estuarine and coastal ocean observing and modeling system for the New York Harbor and surrounding waters. Real-time measurements from in-situ mobile and stationary sensors in the NYHOPS networks are assimilated into marine forecasts in order to reduce the discrepancy with ground truth. The forecasts are obtained from the ECOMSED hydrodynamic model, a shallow water derivative of the Princeton Ocean Model. Currently, all sensors in the NYHOPS system are operated in a fixed mode with uniform sampling rates. This technology infusion effort demonstrates the use of Model Predictive Control (MPC) to autonomously adapt the operation of both mobile and stationary sensors in response to changing events that are -automatically detected from the ECOMSED forecasts. The controller focuses sensing resources on those regions that are expected to be impacted by the detected events. The MPC approach involves formulating the problem of calculating the optimal sensor parameters as a constrained multi-objective optimization problem. We have developed an objective function that takes into account the spatiotemporal relationship of the in-situ sensor locations and the locations of events detected by the model. Experiments in simulation were carried out using data collected during a freshwater flooding event. The location of the resulting freshwater plume was calculated from the corresponding model forecasts and was used by the MPC controller to derive control parameters for the sensing assets. The operational parameters that are controlled include the sampling rates of stationary sensors, paths of unmanned underwater vehicles (UUVs), and data transfer routes between sensors and the central modeling computer. The simulation experiments show that MPC-based sensor control reduces the RMS error in the forecast by a factor of 380% as compared to uniform sampling. The paths of multiple UUVs were simultaneously calculated such that measurements from on-board sensors would lead to maximal reduction in the forecast error after data assimilation. The MPC controller also reduces the consumption of system resources such as energy expended in sampling and wireless communication. The MPC-based control approach can be generalized to accept data from remote sensing satellites. This will enable in-situ sensors to be regulated using forecasts generated by assimilating local high resolution in-situ measurements with wide-area observations from remote sensing satellites.

Lossy compression for Animated Web Visualisation

NASA Astrophysics Data System (ADS)

Prudden, R.; Tomlinson, J.; Robinson, N.; Arribas, A.

2017-12-01

This talk will discuss an technique for lossy data compression specialised for web animation. We set ourselves the challenge of visualising a full forecast weather field as an animated 3D web page visualisation. This data is richly spatiotemporal, however it is routinely communicated to the public as a 2D map, and scientists are largely limited to visualising data via static 2D maps or 1D scatter plots. We wanted to present Met Office weather forecasts in a way that represents all the generated data. Our approach was to repurpose the technology used to stream high definition videos. This enabled us to achieve high rates of compression, while being compatible with both web browsers and GPU processing. Since lossy compression necessarily involves discarding information, evaluating the results is an important and difficult problem. This is essentially a problem of forecast verification. The difficulty lies in deciding what it means for two weather fields to be "similar", as simple definitions such as mean squared error often lead to undesirable results. In the second part of the talk, I will briefly discuss some ideas for alternative measures of similarity.

Vertical Profiling of Air Pollution at RAPCD

NASA Technical Reports Server (NTRS)

Newchurch, Michael J.; Fuller, Kirk A.; Bowdle, David A.; Johnson, Steven; Knupp, Kevin; Gillani, Noor; Biazar, Arastoo; Mcnider, Richard T.; Burris, John

2004-01-01

The interaction between local and regional pollution levels occurs at the interface of the Planetary Boundary Layer and the Free Troposphere. Measuring the vertical distribution of ozone, aerosols, and winds with high temporal and vertical resolution is essential to diagnose the nature of this interchange and ultimately for accurately forecasting ozone and aerosol pollution levels. The Regional Atmospheric Profiling Center for Discovery, RAPCD, was built and instrumented to address this critical issue. The ozone W DIAL lidar, Nd:YAG aerosol lidar, and 2.1 micron Doppler wind lidar, along with balloon- borne ECC ozonesondes form the core of the W C D instrumentation for addressing this problem. Instrumentation in the associated Mobile Integrated Profiling (MIPS) laboratory includes 91 5Mhz profiler, sodar, and ceilometer. The collocated Applied particle Optics and Radiometry (ApOR) laboratory hosts an FTIR along with MOUDI and optical particle counters. With MODELS-3 analysis by colleagues in the National Space Science and Technology Center on the UAH campus and the co- located National Weather Service Forecasting Office in Huntsville, AL we are developing a unique facility for advancing the state of the science of pollution forecasting.

Operational Earthquake Forecasting and Earthquake Early Warning: The Challenges of Introducing Scientific Innovations for Public Safety

NASA Astrophysics Data System (ADS)

Goltz, J. D.

2016-12-01

Although variants of both earthquake early warning and short-term operational earthquake forecasting systems have been implemented or are now being implemented in some regions and nations, they have been slow to gain acceptance within the disciplines that produced them as well as among those for whom they were intended to assist. To accelerate the development and implementation of these technologies will require the cooperation and collaboration of multiple disciplines, some inside and others outside of academia. Seismologists, social scientists, emergency managers, elected officials and key opinion leaders from the media and public must be the participants in this process. Representatives of these groups come from both inside and outside of academia and represent very different organizational cultures, backgrounds and expectations for these systems, sometimes leading to serious disagreements and impediments to further development and implementation. This presentation will focus on examples of the emergence of earthquake early warning and operational earthquake forecasting systems in California, Japan and other regions and document the challenges confronted in the ongoing effort to improve seismic safety.

Development and Evaluation of a Gridded CrIS/ATMS Visualization for Operational Forecasting

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Smith, N.; Dostalek, J.; Stevens, E.; Nelson, K.; Weisz, E.; Berndt, E.; Line, W.; Barnet, C.; Gambacorta, A.; Reale, A.; Hoese, D.

2016-12-01

Upper-air observations from radiosondes are limited in spatial coverage and are primarily launched only at synoptic times, potentially missing evolving air masses. For forecast challenges which require diagnosis of the three-dimensional extent of the atmosphere, these observations may not be enough for forecasters. Currently, forecasters rely on model output alongside the sparse network of radiosondes for characterizing the three-dimensional atmosphere. However, satellite information can help fill in the spatial and temporal gaps in radiosonde observations. In particular, temperature and moisture retrievals from the NOAA-Unique Combined Atmospheric Processing System (NUCAPS), which combines infrared soundings from the Cross-track Infrared Sounder (CrIS) with the Advanced Technology Microwave Sounder (ATMS) to retrieve profiles of temperature and moisture. NUCAPS retrievals are available in a wide swath of observations with approximately 45-km spatial resolution at nadir and a local Equator crossing time of 1:30 A.M./P.M. enabling three-dimensional observations at asynoptic times. For forecasters to make the best use of these observations, these satellite-based soundings must be displayed in the National Weather Service's decision support system, the Advanced Weather Interactive Processing System (AWIPS). NUCAPS profiles are currently available in AWIPS as point observations that can be displayed on Skew-T diagrams. This presentation discusses the development of a new visualization capability for NUCAPS within AWIPS that will allow the data to be viewed in gridded horizontal maps or as vertical cross sections, giving forecasters additional tools for diagnosing atmospheric features. Forecaster feedback and examples of operational applications from two testbed activities will be highlighted. First is a product evaluation at the Hazardous Weather Testbed for severe weather—such as high winds, large hail, tornadoes—where the vertical distribution of temperature and moisture ahead of frontal boundaries was assessed. Second, is a product evaluation with the Alaska Center Weather Service Unit for cold air aloft—where the detection of the three-dimension extent of exterior aircraft temperatures lower than -65°C (temperatures at which jet fuel may begin to freeze)—was assessed.

Developing Dual Polarization Applications For 45th Weather Squadron's (45 WS) New Weather Radar: A Cooperative Project With The National Space Science and Technology Center (NSSTC)

NASA Technical Reports Server (NTRS)

Roeder, W.P.; Peterson, W.A.; Carey, L.D.; Deierling, W.; McNamara, T.M.

2009-01-01

A new weather radar is being acquired for use in support of America s space program at Cape Canaveral Air Force Station, NASA Kennedy Space Center, and Patrick AFB on the east coast of central Florida. This new radar includes dual polarization capability, which has not been available to 45 WS previously. The 45 WS has teamed with NSSTC with funding from NASA Marshall Spaceflight Flight Center to improve their use of this new dual polarization capability when it is implemented operationally. The project goals include developing a temperature profile adaptive scan strategy, developing training materials, and developing forecast techniques and tools using dual polarization products. The temperature profile adaptive scan strategy will provide the scan angles that provide the optimal compromise between volume scan rate, vertical resolution, phenomena detection, data quality, and reduced cone-of-silence for the 45 WS mission. The mission requirements include outstanding detection of low level boundaries for thunderstorm prediction, excellent vertical resolution in the atmosphere electrification layer between 0 C and -20 C for lightning forecasting and Lightning Launch Commit Criteria evaluation, good detection of anvil clouds for Lightning Launch Commit Criteria evaluation, reduced cone-of-silence, fast volume scans, and many samples per pulse for good data quality. The training materials will emphasize the appropriate applications most important to the 45 WS mission. These include forecasting the onset and cessation of lightning, forecasting convective winds, and hopefully the inference of electrical fields in clouds. The training materials will focus on annotated radar imagery based on products available to the 45 WS. Other examples will include time sequenced radar products without annotation to simulate radar operations. This will reinforce the forecast concepts and also allow testing of the forecasters. The new dual polarization techniques and tools will focus on the appropriate applications for the 45 WS mission. These include forecasting the onset of lightning, the cessation of lightning, convective winds, and hopefully the inference of electrical fields in clouds. This presentation will report on the results achieved so far in the project.

Near-real-time simulation and internet-based delivery of forecast-flood inundation maps using two-dimensional hydraulic modeling--A pilot study for the Snoqualmie River, Washington

USGS Publications Warehouse

Jones, Joseph L.; Fulford, Janice M.; Voss, Frank D.

2002-01-01

A system of numerical hydraulic modeling, geographic information system processing, and Internet map serving, supported by new data sources and application automation, was developed that generates inundation maps for forecast floods in near real time and makes them available through the Internet. Forecasts for flooding are generated by the National Weather Service (NWS) River Forecast Center (RFC); these forecasts are retrieved automatically by the system and prepared for input to a hydraulic model. The model, TrimR2D, is a new, robust, two-dimensional model capable of simulating wide varieties of discharge hydrographs and relatively long stream reaches. TrimR2D was calibrated for a 28-kilometer reach of the Snoqualmie River in Washington State, and is used to estimate flood extent, depth, arrival time, and peak time for the RFC forecast. The results of the model are processed automatically by a Geographic Information System (GIS) into maps of flood extent, depth, and arrival and peak times. These maps subsequently are processed into formats acceptable by an Internet map server (IMS). The IMS application is a user-friendly interface to access the maps over the Internet; it allows users to select what information they wish to see presented and allows the authors to define scale-dependent availability of map layers and their symbology (appearance of map features). For example, the IMS presents a background of a digital USGS 1:100,000-scale quadrangle at smaller scales, and automatically switches to an ortho-rectified aerial photograph (a digital photograph that has camera angle and tilt distortions removed) at larger scales so viewers can see ground features that help them identify their area of interest more effectively. For the user, the option exists to select either background at any scale. Similar options are provided for both the map creator and the viewer for the various flood maps. This combination of a robust model, emerging IMS software, and application interface programming should allow the technology developed in the pilot study to be applied to other river systems where NWS forecasts are provided routinely.

NASA's aircraft icing technology program

NASA Technical Reports Server (NTRS)

Reinmann, John J.

1991-01-01

NASA' Aircraft Icing Technology program is aimed at developing innovative technologies for safe and efficient flight into forecasted icing. The program addresses the needs of all aircraft classes and supports both commercial and military applications. The program is guided by three key strategic objectives: (1) numerically simulate an aircraft's response to an in-flight icing encounter, (2) provide improved experimental icing simulation facilities and testing techniques, and (3) offer innovative approaches to ice protection. Our research focuses on topics that directly support stated industry needs, and we work closely with industry to assure a rapid and smooth transfer of technology. This paper presents selected results that illustrate progress towards the three strategic objectives, and it provides a comprehensive list of references on the NASA icing program.

An application of a multi model approach for solar energy prediction in Southern Italy

NASA Astrophysics Data System (ADS)

Avolio, Elenio; Lo Feudo, Teresa; Calidonna, Claudia Roberta; Contini, Daniele; Torcasio, Rosa Claudia; Tiriolo, Luca; Montesanti, Stefania; Transerici, Claudio; Federico, Stefano

2015-04-01

The accuracy of the short and medium range forecast of solar irradiance is very important for solar energy integration into the grid. This issue is particularly important for Southern Italy where a significant availability of solar energy is associated with a poor development of the grid. In this work we analyse the performance of two deterministic models for the prediction of surface temperature and short-wavelength radiance for two sites in southern Italy. Both parameters are needed to forecast the power production from solar power plants, so the performance of the forecast for these meteorological parameters is of paramount importance. The models considered in this work are the RAMS (Regional Atmospheric Modeling System) and the WRF (Weather Research and Forecasting Model) and they were run for the summer 2013 at 4 km horizontal resolution over Italy. The forecast lasts three days. Initial and dynamic boundary conditions are given by the 12 UTC deterministic forecast of the ECMWF-IFS (European Centre for Medium Weather Range Forecast - Integrated Forecasting System) model, and were available every 6 hours. Verification is given against two surface stations located in Southern Italy, Lamezia Terme and Lecce, and are based on hourly output of models forecast. Results for the whole period for temperature show a positive bias for the RAMS model and a negative bias for the WRF model. RMSE is between 1 and 2 °C for both models. Results for the whole period for the short-wavelength radiance show a positive bias for both models (about 30 W/m2 for both models) and a RMSE of 100 W/m2. To reduce the model errors, a statistical post-processing technique, i.e the multi-model, is adopted. In this approach the two model's outputs are weighted with an adequate set of weights computed for a training period. In general, the performance is improved by the application of the technique, and the RMSE is reduced by a sizeable fraction (i.e. larger than 10% of the initial RMSE) depending on the forecasting time and parameter. The performance of the multi model is discussed as a function of the length of the training period and is compared with the performance of the MOS (Model Output Statistics) approach. ACKNOWLEDGMENTS This work is partially supported by projects PON04a2E Sinergreen-ResNovae - "Smart Energy Master for the energetic government of the territory" and PONa3_00363 "High Technology Infrastructure for Climate and Environment Monitoring" (I-AMICA) founded by Italian Ministry of University and Research (MIUR) PON 2007-2013. The ECMWF and CNMCA (Centro Nazionale di Meteorologia e Climatologia Aeronautica) are acknowledged for the use of the MARS (Meteorological Archive and Retrieval System).

Biometeorological forecasts for health surveillance and prevention of meteor-tropic effects

NASA Astrophysics Data System (ADS)

Lecha Estela, Luis B.

2018-05-01

An early method of biometeorological forecasts was developed for Cuba during the late 90s. It was based on the relationship between the daily occurrence of massive health crisis and the magnitude of the 24-h differences of partial density of oxygen in the air (PODA index). Ten years later, applying new technological facilities, a new model was developed in order to offer operational biometeorological forecast to Cuban health institutions. After a satisfactory validation process, the official bioforecast service to health institutions in Villa Clara province began on February of 2012. The effectiveness had different success levels: for the bronchial asthma crisis (94%), in the hypertensive crisis (88%), with the cerebrovascular illnesses (85%), as well as migraines (82%) and in case of cardiovascular diseases (75%) were acceptable. Since 2008, the application of the model was extended to other regions of the world, including some national applications. Furthermore, it allowed the beginning of regional monitoring of meteor-tropic effects, following the occurrence and movement of areas with higher weather contrasts, defined according to the normalized scale of PODA index. The paper describes the main regional results already available, with emphasis in the observed meteor-tropic effects increasing in all regions during recent years. It coincides with the general increase of energy imbalance in the whole climate system. Finally, the paper describes the current development of new global biometeorological forecast services.

Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing

NASA Astrophysics Data System (ADS)

Toye, Habib; Zhan, Peng; Gopalakrishnan, Ganesh; Kartadikaria, Aditya R.; Huang, Huang; Knio, Omar; Hoteit, Ibrahim

2017-07-01

We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and of the Data Research Testbed (DART) for ensemble data assimilation. DART has been configured to integrate all members of an ensemble adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble operations in DART to use an invariant ensemble, i.e., an ensemble Optimal Interpolation (EnOI) algorithm. This approach requires only single forward model integration in the forecast step and therefore saves substantial computational cost. To deal with the strong seasonal variability of the Red Sea, the EnOI ensemble is then seasonally selected from a climatology of long-term model outputs. Observations of remote sensing sea surface height (SSH) and sea surface temperature (SST) are assimilated every 3 days. Real-time atmospheric fields from the National Center for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) are used as forcing in different assimilation experiments. We investigate the behaviors of the EAKF and (seasonal-) EnOI and compare their performances for assimilating and forecasting the circulation of the Red Sea. We further assess the sensitivity of the assimilation system to various filtering parameters (ensemble size, inflation) and atmospheric forcing.

Biometeorological forecasts for health surveillance and prevention of meteor-tropic effects

NASA Astrophysics Data System (ADS)

Lecha Estela, Luis B.

2017-09-01

An early method of biometeorological forecasts was developed for Cuba during the late 90s. It was based on the relationship between the daily occurrence of massive health crisis and the magnitude of the 24-h differences of partial density of oxygen in the air (PODA index). Ten years later, applying new technological facilities, a new model was developed in order to offer operational biometeorological forecast to Cuban health institutions. After a satisfactory validation process, the official bioforecast service to health institutions in Villa Clara province began on February of 2012. The effectiveness had different success levels: for the bronchial asthma crisis (94%), in the hypertensive crisis (88%), with the cerebrovascular illnesses (85%), as well as migraines (82%) and in case of cardiovascular diseases (75%) were acceptable. Since 2008, the application of the model was extended to other regions of the world, including some national applications. Furthermore, it allowed the beginning of regional monitoring of meteor-tropic effects, following the occurrence and movement of areas with higher weather contrasts, defined according to the normalized scale of PODA index. The paper describes the main regional results already available, with emphasis in the observed meteor-tropic effects increasing in all regions during recent years. It coincides with the general increase of energy imbalance in the whole climate system. Finally, the paper describes the current development of new global biometeorological forecast services.

Multivariate time series modeling of short-term system scale irrigation demand

NASA Astrophysics Data System (ADS)

Perera, Kushan C.; Western, Andrew W.; George, Biju; Nawarathna, Bandara

2015-12-01

Travel time limits the ability of irrigation system operators to react to short-term irrigation demand fluctuations that result from variations in weather, including very hot periods and rainfall events, as well as the various other pressures and opportunities that farmers face. Short-term system-wide irrigation demand forecasts can assist in system operation. Here we developed a multivariate time series (ARMAX) model to forecast irrigation demands with respect to aggregated service points flows (IDCGi, ASP) and off take regulator flows (IDCGi, OTR) based across 5 command areas, which included area covered under four irrigation channels and the study area. These command area specific ARMAX models forecast 1-5 days ahead daily IDCGi, ASP and IDCGi, OTR using the real time flow data recorded at the service points and the uppermost regulators and observed meteorological data collected from automatic weather stations. The model efficiency and the predictive performance were quantified using the root mean squared error (RMSE), Nash-Sutcliffe model efficiency coefficient (NSE), anomaly correlation coefficient (ACC) and mean square skill score (MSSS). During the evaluation period, NSE for IDCGi, ASP and IDCGi, OTR across 5 command areas were ranged 0.98-0.78. These models were capable of generating skillful forecasts (MSSS ⩾ 0.5 and ACC ⩾ 0.6) of IDCGi, ASP and IDCGi, OTR for all 5 lead days and IDCGi, ASP and IDCGi, OTR forecasts were better than using the long term monthly mean irrigation demand. Overall these predictive performance from the ARMAX time series models were higher than almost all the previous studies we are aware. Further, IDCGi, ASP and IDCGi, OTR forecasts have improved the operators' ability to react for near future irrigation demand fluctuations as the developed ARMAX time series models were self-adaptive to reflect the short-term changes in the irrigation demand with respect to various pressures and opportunities that farmers' face, such as changing water policy, continued development of water markets, drought and changing technology.

The Role of Robots and Automation in Space

NASA Technical Reports Server (NTRS)

Heer, E.

1978-01-01

Advanced space transportation systems based on the shuttle and interim upper stage will open the way to the use of large-scale industrial and commercial systems in space. The role of robot and automation technology in the cost-effective implementation and operation of such systems in the next two decades is discussed. Planning studies initiated by NASA are described as applied to space exploration, global services, and space industrialization, and a forecast of potential missions in each category is presented. The appendix lists highlights of space robot technology from 1967 to the present.

Computer technology forecast study for general aviation

NASA Technical Reports Server (NTRS)

Seacord, C. L.; Vaughn, D.

1976-01-01

A multi-year, multi-faceted program is underway to investigate and develop potential improvements in airframes, engines, and avionics for general aviation aircraft. The objective of this study was to assemble information that will allow the government to assess the trends in computer and computer/operator interface technology that may have application to general aviation in the 1980's and beyond. The current state of the art of computer hardware is assessed, technical developments in computer hardware are predicted, and nonaviation large volume users of computer hardware are identified.

Numerical aerodynamic simulation facility preliminary study, volume 1

NASA Technical Reports Server (NTRS)

1977-01-01

A technology forecast was established for the 1980-1985 time frame and the appropriateness of various logic and memory technologies for the design of the numerical aerodynamic simulation facility was assessed. Flow models and their characteristics were analyzed and matched against candidate processor architecture. Metrics were established for the total facility, and housing and support requirements of the facility were identified. An overview of the system is presented, with emphasis on the hardware of the Navier-Stokes solver, which is the key element of the system. Software elements of the system are also discussed.

Application of Advanced Technologies to Small, Short-haul Air Transports

NASA Technical Reports Server (NTRS)

Adcock, C.; Coverston, C.; Knapton, B.

1980-01-01

A study was conducted of the application of advanced technologies to small, short-haul transport aircraft. A three abreast, 30 passenger design for flights of approximately 100 nautical miles was evaluated. Higher wing loading, active flight control, and a gust alleviation system results in improved ride quality. Substantial savings in fuel and direct operating cost are forecast. An aircraft of this configuration also has significant benefits in forms of reliability and operability which should enable it to sell a total of 450 units through 1990, of which 80% are for airline use.

Existing generating assets squeezed as new project starts slow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, R.B.; Tiffany, E.D.

Most forecasting reports concentrate on political or regulatory events to predict future industry trends. Frequently overlooked are the more empirical performance trends of the principal power generation technologies. Solomon and Associates queried its many power plant performance databases and crunched some numbers to identify those trends. Areas of investigation included reliability, utilization (net output factor and net capacity factor) and cost (operating costs). An in-depth analysis for North America and Europe is presented in this article, by region and by regeneration technology. 4 figs., 2 tabs.

Trends in Microfabrication Capabilities & Device Architectures.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bauer, Todd; Jones, Adam; Lentine, Anthony L.

The last two decades have seen an explosion in worldwide R&D, enabling fundamentally new capabilities while at the same time changing the international technology landscape. The advent of technologies for continued miniaturization and electronics feature size reduction, and for architectural innovations, will have many technical, economic, and national security implications. It is important to anticipate possible microelectronics development directions and their implications on US national interests. This report forecasts and assesses trends and directions for several potentially disruptive microfabrication capabilities and device architectures that may emerge in the next 5-10 years.

Remotely piloted aircraft in the civil environment

NASA Technical Reports Server (NTRS)

Gregory, T. J.; Nelms, W. P.; Karmarkar, J. S.

1977-01-01

Remotely piloted aircraft (RPA's) are of increasing interest to the military and others, as evidenced by a number of technology and development programs that are currently funded or planned. These programs have led to a number of test aircraft with significant capabilities, and future remotely piloted aircraft are forecast to become even more capable as the technology in a number of important subsystem areas is progressing at a rapid rate. As the size, weight and cost of RPA's is reduced, the prospect of using them for civilian applications becomes more likely.

The Hydrometeorological Testbed (HMT): Opportunities for Scenario Development in a Framework of Improving Precipitation and Streamflow Science and Prediction

NASA Astrophysics Data System (ADS)

Ralph, F. M.; Kingsmill, D.; Restrepo, P.; Nowlis, J.; White, A.

2006-12-01

The Hydrometeorology Testbed (HMT) is an effort to accelerate the infusion of new technologies, models, and scientific results from the research community into daily hydrometeorological forecast operations of the National Weather Service (NWS) and its River Forecast Centers (RFCs). HMT is a product of NOAA's CALJET and PACJET projects from 1997-2003 on the West Coast and it has been identified in the NWS Hydrology Science and Technology Implementation Plan (STIP) and NOAA's Programming, Planning, Budgeting and Execution System (PPBES) as a key new R&D approach for improving flood and streamflow forecasts. Preliminary, small scale tests of HMT facilities, led by the NOAA Earth System Research Laboratory, were conducted in California's Coast Range in 2004 (HMT-04) and were moved to the western slopes of the Sierra Nevada for the winters of 2005-2006 and 2006-2007. Unlike typical research field projects, the HMT operates as a demonstration with forecasters and researchers joining forces in the operational setting, to addressing key forecast user needs. The current HMT targets California's flood-vulnerable American River Basin with the first full-scale deployment of this highly instrumented facility. Following the California demonstration, HMT facilities will be sequentially deployed to other regions of the Nation to address additional serious hydrometeorology problems that are unique to those locations. The project will run for a few years in each regional demonstration to determine the new tools most useful for improving precipitation and runoff forecasting methods. These successful tools will remain in place and will be duplicated as the HMT moves to the next region. Through NOAA funding, HMT will provide a foundation level of effort and infrastructure each year in the test region. It is expected that this foundation will be augmented by occasional ramping-up to more intensive operations that include additional participants and specialized instrumentation. The HMT activities in the American River Basin can benefit from the development and analysis of management scenarios that evaluate the impacts HMT can provide through improved predictions of water inflow into the Folsom Reservoir. Management models that explore various water management policies and their relative performance at controlling floods, generating energy, presenting recreational opportunities, maintaining healthy downstream ecosystems, and providing water for agricultural, urban, and industrial uses, would be particularly valuable. Use of conventional inputs to estimate reservoir levels could be compared with improved estimates resulting from HMT.. The difference between the model results will illustrate the value of improved predictability of extreme weather, while also providing insight into the strengths and weaknesses of various water management policies.

Tailored high-resolution numerical weather forecasts for energy efficient predictive building control

NASA Astrophysics Data System (ADS)

Stauch, V. J.; Gwerder, M.; Gyalistras, D.; Oldewurtel, F.; Schubiger, F.; Steiner, P.

2010-09-01

The high proportion of the total primary energy consumption by buildings has increased the public interest in the optimisation of buildings' operation and is also driving the development of novel control approaches for the indoor climate. In this context, the use of weather forecasts presents an interesting and - thanks to advances in information and predictive control technologies and the continuous improvement of numerical weather prediction (NWP) models - an increasingly attractive option for improved building control. Within the research project OptiControl (www.opticontrol.ethz.ch) predictive control strategies for a wide range of buildings, heating, ventilation and air conditioning (HVAC) systems, and representative locations in Europe are being investigated with the aid of newly developed modelling and simulation tools. Grid point predictions for radiation, temperature and humidity of the high-resolution limited area NWP model COSMO-7 (see www.cosmo-model.org) and local measurements are used as disturbances and inputs into the building system. The control task considered consists in minimizing energy consumption whilst maintaining occupant comfort. In this presentation, we use the simulation-based OptiControl methodology to investigate the impact of COSMO-7 forecasts on the performance of predictive building control and the resulting energy savings. For this, we have selected building cases that were shown to benefit from a prediction horizon of up to 3 days and therefore, are particularly suitable for the use of numerical weather forecasts. We show that the controller performance is sensitive to the quality of the weather predictions, most importantly of the incident radiation on differently oriented façades. However, radiation is characterised by a high temporal and spatial variability in part caused by small scale and fast changing cloud formation and dissolution processes being only partially represented in the COSMO-7 grid point predictions. On the other hand, buildings are affected by particularly local weather conditions at the building site. To overcome this discrepancy, we make use of local measurements to statistically adapt the COSMO-7 model output to the meteorological conditions at the building. For this, we have developed a general correction algorithm that exploits systematic properties of the COSMO-7 prediction error and explicitly estimates the degree of temporal autocorrelation using online recursive estimation. The resulting corrected predictions are improved especially for the first few hours being the most crucial for the predictive controller and, ultimately for the reduction of primary energy consumption using predictive control. The use of numerical weather forecasts in predictive building automation is one example in a wide field of weather dependent advanced energy saving technologies. Our work particularly highlights the need for the development of specifically tailored weather forecast products by (statistical) postprocessing in order to meet the requirements of specific applications.

Creating the Workforce of the Future: The STEM Interest and Proficiency Challenge. BHEF Research Brief

ERIC Educational Resources Information Center

Business-Higher Education Forum (NJ1), 2011

2011-01-01

A strong economy requires a highly educated workforce, especially in science, technology, engineering, and math (STEM) fields. In the United States, STEM degree production has stagnated, despite employment projections forecasting a 17% growth in the field over the next decade. Two key criteria influence progression through the STEM education…

Cargo/Logistics Airlift System Study (CLASS), Executive Summary

NASA Technical Reports Server (NTRS)

Norman, J. M.; Henderson, R. D.; Macey, F. C.; Tuttle, R. P.

1978-01-01

The current air cargo system is analyzed along with advanced air cargo systems studies. A forecast of advanced air cargo system demand is presented with cost estimates. It is concluded that there is a need for a dedicated advance air cargo system, and with application of advanced technology, reductions of 45% in air freight rates may be achieved.

An Empirical Study of Logistics Organization, Electronic Linkage, and Performance

DTIC Science & Technology

1993-01-01

utilization of transportation resources, and improved quality management. Researchers have proposed an information technology (IT) implementation model for...management, more efficient utilization of transportation resources, and improved quality management. Researchers have proposed an information...coordination of (1) facility structure, (2) forecasting and order management, (3) transportation , (4) inventory, and (5) warehousing and packaging. The

[Paradigm shift in health: forecasting and causation as a basis for risk management].

PubMed

Denisov, E I; Prokopenko, L V; Golovaneva, G V; Stepanian, I V

2012-01-01

The problem of occupational risk management (ORM) is discussed using the evidence-based medicine approach and bio- and IT-technologies. The prognosis and causation of work-related health disorders are analyzed as components of ORM system. The Web-based handbook "Occupational risk assessment" with software and information materials as practical tool is presented.

THE SAN PEDRO RIVER: A CASE STUDY FOR EXAMINING PAST LANDSCAPE CHANGE AND FORECASTING HYDROLOGICAL AND BIOLOGICAL RESPONSE TO URBAN GROWTH AND LAND USE CHANGE

EPA Science Inventory

It is currently possible to measure landscape change over large areas and determine trends in

environmental condition using advanced space-based technologies accompanied by geospatial data.

During the past two decades, important advances in the integration of remote...

Entering the Interaction Age: Implementing a Future Vision for Campus Learning Spaces...Today

ERIC Educational Resources Information Center

Milne, Andrew J.

2007-01-01

Learning space design for higher education has become a popular topic of discussion as institutions attempt to chart a course for the future of their campuses. Several authors in EDUCAUSE publications have forecast the future for such spaces, a future infused with new and sometimes exotic-sounding technologies. Indeed, some discussions in the…

Innovation Forecasting

DTIC Science & Technology

1997-11-01

Hamel, G., Doz, Y., Prahalad , C., Collaborate With Your Competitors And Win, in Strategic Management of Technology and Innovation, 2nd ed., R...information should help management make better decisions with regard to strategic corporate planning, R&D management, product development, investment in new...different perspectives and act to influence its development toward their own interests [7]. As an example, in assessing national strategic value

Neither Feast nor Famine: Summary of the Second Twenty Year Forecast Project.

ERIC Educational Resources Information Center

Enzer, Selwyn; And Others

1977-01-01

The key question to ask in determining whether a solution will be found to the world food problem is whether people will learn to effectively manage the food/population balance. Predictions concerning the world food situation should be made on the basis of these factors: (1) possible future changes involving technological development, political…

Forecasting Twenty-First Century Information Technology Skills: A Delphi Study

ERIC Educational Resources Information Center

Young, Jackie A.

2012-01-01

As cities and regions seek to increase the stock of college educated citizens in order to compete in the twenty-first century knowledge-economy, colleges and universities are realizing increased enrollment. At the same time, much is being written about the skills needed by graduates for the new economy. These studies articulate skills in critical…

Future-Orientated Approaches to Curriculum Development: Fictive Scripting

ERIC Educational Resources Information Center

Garraway, James

2017-01-01

Though the future cannot be accurately predicted, it is possible to envisage a number of probable developments which can promote thinking about the future and so promote a more informed stance about what should or should not be done. Studies in technology and society have claimed that the use of a type of forecasting using plausible but imaginary…

Manpower Planning and Forecasting, Proceedings of the Annual Research Conference (10th, Beverly Hills, California, April 10-11, 1967).

ERIC Educational Resources Information Center

California Univ., Los Angeles. Inst. of Industrial Relations.

Five conference papers covering research studies and problems related to effective utilization of manpower in southern California are presented. "The Impact of Technological Change on Employees in the Southern California Aerospace Industry," by Paul Prasow, reports a longitudinal study of social and psychological adjustment factors…

Forecasting Educational Futures. Resolving Uncertainties and Disagreements through Compact Policy Assessment.

ERIC Educational Resources Information Center

Hudson, Barclay M.

Descriptions of models for policy analysis in future studies are presented. Separate sections of the paper focus on the need for appropriate technologies of social science in future studies, a description of "compact policy assessment" (CPA), and a comparison of two CPA methods, Compass and Delphi. Compact policy assessment refers to any low-cost,…

Predicting the impacts of new technology aircraft on international air transportation demand

NASA Technical Reports Server (NTRS)

Ausrotas, R. A.

1981-01-01

International air transportation to and from the United States was analyzed. Long term and short term effects and causes of travel are described. The applicability of econometric methods to forecast passenger travel is discussed. A nomograph is developed which shows the interaction of economic growth, airline yields, and quality of service in producing international traffic.

The Future Institutional Research Office: Brave New Workplace or Electronic Sweatshop? AIR 1989 Annual Forum Paper.

ERIC Educational Resources Information Center

Liebmann, Jeffrey D.

Information technology is changing the workplace. Forecasts range from wondrous visions of future capabilities to dark scenarios of employment loss and dehumanization. Some predict revolutionary impacts, while others conclude that the way we do business will change only gradually if much at all. The less positive visions of the future workplace…

Smart Power: New power integrated circuit technologies and their applications

NASA Astrophysics Data System (ADS)

Kuivalainen, Pekka; Pohjonen, Helena; Yli-Pietilae, Timo; Lenkkeri, Jaakko

1992-05-01

Power Integrated Circuits (PIC) is one of the most rapidly growing branches of the semiconductor technology. The PIC markets has been forecast to grow from 660 million dollars in 1990 to 1658 million dollars in 1994. It has even been forecast that at the end of the 1990's the PIC markets would correspond to the value of the whole semiconductor production in 1990. Automotive electronics will play the leading role in the development of the standard PIC's. Integrated motor drivers (36 V/4 A), smart integrated switches (60 V/30 A), solenoid drivers, integrated switch-mode power supplies and regulators are the latest standard devices of the PIC manufactures. ASIC (Application Specific Integrated Circuits) PIC solutions are needed for the same reasons as other ASIC devices: there are no proper standard devices, a company has a lot of application knowhow, which should be kept inside the company, the size of the product must be reduced, and assembly costs are wished to be reduced by decreasing the number of discrete devices. During the next few years the most probable ASIC PIC applications in Finland will be integrated solenoid and motor drivers, an integrated electronic lamp ballast circuit and various sensor interface circuits. Application of the PIC technologies to machines and actuators will strongly be increased all over the world. This means that various PIC's, either standard PIC's or full custom ASIC circuits, will appear in many products which compete with the corresponding Finnish products. Therefore the development of the PIC technologies must be followed carefully in order to immediately be able to apply the latest development in the smart power technologies and their design methods.

JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis

NASA Astrophysics Data System (ADS)

Folmer, M. J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J. M.; Nelson, J. A., Jr.; Goldberg, M.

2016-12-01

The National Oceanic and Atmospheric Administration (NOAA) Satellite Proving Ground (PG) for Marine, Precipitation, and Satellite Analysis (MPS) has been demonstrating and evaluating Suomi National Polar-orbiting Partnership (S-NPP) products along with other polar-orbiting satellite platforms in preparation for the Joint Polar Satellite System - 1 (JPSS-1) launch in March 2017. The first S-NPP imagery was made available to the MPS PG during the evolution of Hurricane Sandy in October 2012 and has since been popular in operations. Since this event the MPS PG Satellite Liaison has been working with forecasters on ways to integrate single-channel and multispectral imagery from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Advanced Very High Resolution Radiometer (AVHRR)into operations to complement numerical weather prediction and geostationary satellite savvy National Weather Service (NWS) National Centers. Additional unique products have been introduced to operations to address specific forecast challenges, including the Cooperative Institute for Research in the Atmosphere (CIRA) Layered Precipitable Water, the National Environmental Satellite, Data, and Information Service (NESDIS) Snowfall Rate product, NOAA Unique Combined Atmospheric Processing System (NUCAPS) Soundings, ozone products from the Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS), and Infrared Atmospheric Sounding Interferometer (IASI). In addition, new satellite domains have been created to provide forecasters at the NWS Ocean Prediction Center and Weather Prediction Center with better quality imagery at high latitudes. This has led to research projects that are addressing forecast challenges such as tropical to extratropical transition and explosive cyclogenesis. This presentation will provide examples of how the MPS PG has been introducing and integrating these products into operations to help solve these forecast challenges.

Forecasting the regional distribution and sufficiency of physicians in Japan with a coupled system dynamics-geographic information system model.

PubMed

Ishikawa, Tomoki; Fujiwara, Kensuke; Ohba, Hisateru; Suzuki, Teppei; Ogasawara, Katsuhiko

2017-09-12

In Japan, the shortage of physicians has been recognized as a major medical issue. In our previous study, we reported that the absolute shortage will be resolved in the long term, but maldistribution among specialties will persist. To address regional shortage, several Japanese medical schools increased existing quota and established "regional quotas." This study aims to assist policy makers in designing effective policies; we built a model for forecasting physician numbers by region to evaluate future physician supply-demand balances. For our case study, we selected Hokkaido Prefecture in Japan, a region displaying disparities in healthcare services availability between urban and rural areas. We combined a system dynamics (SD) model with geographic information system (GIS) technology to analyze the dynamic change in spatial distribution of indicators. For Hokkaido overall and for each secondary medical service area (SMSA) within the prefecture, we analyzed the total number of practicing physicians. For evaluating absolute shortage and maldistribution, we calculated sufficiency levels and Gini coefficient. Our study covered the period 2010-2030 in 5-year increments. According to our forecast, physician shortage in Hokkaido Prefecture will largely be resolved by 2020. Based on current policies, we forecast that four SMSAs in Hokkaido will continue to experience physician shortages past that date, but only one SMSA would still be understaffed in 2030. The results show the possibility that diminishing imbalances between SMSAs would not necessarily mean that regional maldistribution would be eliminated, as seen from the sufficiency levels of the various SMSAs. Urgent steps should be taken to place doctors in areas where our forecasting model predicts that physician shortages could occur in the future.

Space Weather Products and Tools Used in Auroral Monitoring and Forecasting at CCMC/SWRC

NASA Technical Reports Server (NTRS)

Zheng, Yihua; Rastaetter, Lutz

2015-01-01

Key points discussed in this chapter are (1) the importance of aurora research to scientific advances and space weather applications, (2) space weather products at CCMC that are relevant to aurora monitoring and forecasting, and (3) the need for more effort from the whole community to achieve a better and long-lead-time forecast of auroral activity. Aurora, as manifestations of solar wind-magnetosphere-ionosphere coupling that occurs in a region of space that is relatively easy to access for sounding rockets, satellites, and other types of observational platforms, serves as a natural laboratory for studying the underlying physics of the complex system. From a space weather application perspective, auroras can cause surface charging of technological assets passing through the region, result in scintillation effects affecting communication and navigation, and cause radar cluttering that hinders military and civilian applications. Indirectly, an aurora and its currents can induce geomagnetically induced currents (GIC) on the ground, which poses major concerns for the wellbeing and operation of power grids, particularly during periods of intense geomagnetic activity. In addition, accurate auroral forecasting is desired for auroral tourism. In this chapter, we first review some of the existing auroral models and discuss past validation efforts. Such efforts are crucial in transitioning a model(s) from research to operations and for further model improvement and development that also benefits scientific endeavors. Then we will focus on products and tools that are used for auroral monitoring and forecasting at the Space Weather Research Center (SWRC). As part of the CCMC (Community Coordinated Modeling Center), SWRC has been providing space weather services since 2010.

Probabilistic Weather Information Tailored to the Needs of Transmission System Operators

NASA Astrophysics Data System (ADS)

Alberts, I.; Stauch, V.; Lee, D.; Hagedorn, R.

2014-12-01

Reliable and accurate forecasts for wind and photovoltaic (PV) power production are essential for stable transmission systems. A high potential for improving the wind and PV power forecasts lies in optimizing the weather forecasts, since these energy sources are highly weather dependent. For this reason the main objective of the German research project EWeLiNE is to improve the quality the underlying numerical weather predictions towards energy operations. In this project, the German Meteorological Service (DWD), the Fraunhofer Institute for Wind Energy and Energy System Technology, and three of the German transmission system operators (TSOs) are working together to improve the weather and power forecasts. Probabilistic predictions are of particular interest, as the quantification of uncertainties provides an important tool for risk management. Theoretical considerations suggest that it can be advantageous to use probabilistic information to represent and respond to the remaining uncertainties in the forecasts. However, it remains a challenge to integrate this information into the decision making processes related to market participation and power systems operations. The project is planned and carried out in close cooperation with the involved TSOs in order to ensure the usability of the products developed. It will conclude with a demonstration phase, in which the improved models and newly developed products are combined into a process chain and used to provide information to TSOs in a real-time decision support tool. The use of a web-based development platform enables short development cycles and agile adaptation to evolving user needs. This contribution will present the EWeLiNE project and discuss ideas on how to incorporate probabilistic information into the users' current decision making processes.

Discriminant analysis forecasting model of first trimester pregnancy outcomes developed by following 9,963 infertile patients after in vitro fertilization.

PubMed

Yi, Yan; Li, Xihong; Ouyang, Yan; Lin, Ge; Lu, Guangxiu; Gong, Fei

2016-05-01

To investigate a forecasting method developed to predict first trimester pregnancy outcomes using the first routine ultrasound scan for early pregnancy on days 27-29 after ET and to determine whether to perform a repeated scan several days later based on this forecasting method. Prospective analysis. Infertile patients at an assisted reproductive technology center. A total of 9,963 patients with an early singleton pregnancy after in vitro fertilization (IVF)-ET. None. Ongoing pregnancy >12 weeks of gestation. The classification score of ongoing pregnancy was equal to (1.57 × Maternal age) + (1.01 × Mean sac diameter) + (-0.19 × Crown-rump length) + 25.15 (if cardiac activity is present) + 1.30 (if intrauterine hematomas are present) - 47.35. The classification score of early pregnancy loss was equal to (1.66 × Maternal age) + (0.84 × Mean sac diameter) + (-0.38 × Crown-rump length) + 8.69 (if cardiac activity is present) + 1.60 (if intrauterine hematomas are present) - 34.77. In verification samples, 94.44% of cases were correctly classified using these forecasting models. The discriminant forecasting models are accurate in predicting first trimester pregnancy outcomes based on the first scan for early pregnancy after ET. When the predictive result is ongoing pregnancy, a second scan can be postponed until 11-14 weeks if no symptoms of abdominal pain or vaginal bleeding are present. When the predictive results suggest early pregnancy loss, repeated scans are imperative to avoid a misdiagnosis before evacuating the uterus. Copyright © 2016 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

An integrated modeling framework for real-time irrigation scheduling: the benefit of spectroscopy and weather forecasts

NASA Astrophysics Data System (ADS)

Brook, Anna; Polinova, Maria; Housh, Mashor

2016-04-01

Agriculture and agricultural landscapes are increasingly under pressure to meet the demands of a constantly increasing human population and globally changing food patterns. At the same time, there is rising concern that climate change and food security will harm agriculture in many regions of the world (Nelson et al., 2009). Facing those treats, majority of Mediterranean countries had chosen irrigated agriculture. For crop plants water is one of the most important inputs, as it is responsible for crop growth, production and it ensures the efficiency of other inputs (e.g. seeds, fertilizers and pesticide) but its use is in competition with other local sectors (e.g. industry, urban human use). Thus, well-timed availability of water is vital to agriculture for ensured yields. The increasing demand for irrigation has necessitated the need for optimal irrigation scheduling techniques that coordinate the timing and amount of irrigation to optimally manage the water use in agriculture systems. The irrigation scheduling problem can be challenging as farmers try to deal with different conflicting objectives of maximizing their yield while minimizing irrigation water use. Another challenge in the irrigation scheduling problem is attributed to the uncertain factors involved in the plant growth process during the growing season. Most notable, the climatic factors such as evapotranspiration and rainfall, these uncertain factors add a third objective to the farmer perspective, namely, minimizing the risk associated with these uncertain factors. Nevertheless, advancements in weather forecasting reduced the uncertainty level associated with future climatic data. Thus, climatic forecasts can be reliably employed to guide optimal irrigation schedule scheme when coupled with stochastic optimization models (Housh et al., 2012). Many studies have concluded that optimal irrigation decisions can provide substantial economic value over conventional irrigation decisions (Wang and Cai 2009). These studies have only incorporated short-term (weekly) forecasts, missing the potential benefit of the mid-term (seasonal) climate forecasts The latest progress in new data acquisition technologies (mainly in the field of Earth observation by remote sensing and imaging spectroscopy systems) as well as the state-of-the-art achievements in the fields of geographical information systems (GIS), computer science and climate and climate impact modelling enable to develop both integrated modelling and realistic spatial simulations. The present method is the use of field spectroscopy technology to keep constant monitoring of the field. The majority of previously developed decision support systems use satellite remote sensing data that provide very limited capabilities (conventional and basic parameters). The alternative is to use a more progressive technology of hyperspectral airborne or ground-based imagery data that provide an exhaustive description of the field. Nevertheless, this alternative is known to be very costly and complex. As such, we will present a low-cost imaging spectroscopy technology supported by detailed and fine-resolution field spectroscopy as a cost effective option for near field real-time monitoring tool. In order to solve the soil water balance and to predict the water irrigation volume a pedological survey is realized in the evaluation study areas.The remote sensing and field spectroscopy were applied to integrate continuous feedbacks from the field (e.g. soil moisture, organic/inorganic carbon, nitrogen, salinity, fertilizers, sulphur acid, texture; crop water-stress, plant stage, LAI , chlorophyll, biomass, yield prediction applying PROSPECT+SILT ; Fraction of Absorbed Photosynthetically Active Radiation FAPAR) estimated based on remote sensing information to minimize the errors associated with crop simulation process. A stochastic optimization model will be formulated that take into account both mid-term seasonal probabilistic climate prediction and short-term weekly forecasts. In order to optimize the water resource use, the irrigation scheduling will be defined by use a simulation model of soil-plant and atmosphere system (e.g. SWAP model, Van Dam et al., 2008). The use of this tool is necessary to: i) take into account the soil spatial variability; ii) to predict the system behaviour under the forecasted climate; iii) define the optimized irrigation water volumes. Given this knowledge in the three domains of optimization under uncertainty, spectroscopy/remote sensing and climate forecasting, we will be presented as an integrated framework for deriving optimal irrigation decisions. References Nelson, Gerald C., et al. Climate change: Impact on agriculture and costs of adaptation. Vol. 21. Intl Food Policy Res Inst, 2009. Housh, Mashor, Avi Ostfeld, and Uri Shamir. "Seasonal multi-year optimal management of quantities and salinities in regional water supply systems." Environmental Modelling & Software 37 (2012): 55-67. Wang, Dingbao, and Ximing Cai. "Irrigation scheduling - Role of weather forecasting and farmers' behavior." Journal of Water Resources Planning and Management 135.5 (2009): 364-372. Van Dam, J. C., et al. SWAP version 3.2: Theory description and user manual. No. 1649. Wageningen, The Netherlands: Alterra, 2008.

[Guidelines for budget impact analysis of health technologies in Brazil].

PubMed

Ferreira-Da-Silva, Andre Luis; Ribeiro, Rodrigo Antonini; Santos, Vânia Cristina Canuto; Elias, Flávia Tavares Silva; d'Oliveira, Alexandre Lemgruber Portugal; Polanczyk, Carisi Anne

2012-07-01

Budget impact analysis (BIA) provides operational financial forecasts to implement new technologies in healthcare systems. There were no previous specific recommendations to conduct such analyses in Brazil. This paper reviews BIA methods for health technologies and proposes BIA guidelines for the public and private Brazilian healthcare system. The following recommendations were made: adopt the budget administrator's perspective; use a timeframe of 1 to 5 years; compare reference and alternative scenarios; consider the technology's rate of incorporation; estimate the target population by either an epidemiological approach or measured demand; consider restrictions on technologies' indication or factors that increase the demand for them; consider direct and averted costs; do not adjust for inflation or discounts; preferably, integrate information on a spreadsheet; calculate the incremental budget impact between scenarios; and summarize information in a budget impact report.

AgRISTARS: Foreign commodity production forecasting. The 1980 US/Canada wheat and barley exploratory experiment

NASA Technical Reports Server (NTRS)

Payne, R. W. (Principal Investigator)

1981-01-01

The crop identification procedures used performed were for spring small grains and are conducive to automation. The performance of the machine processing techniques shows a significant improvement over previously evaluated technology; however, the crop calendars require additional development and refinements prior to integration into automated area estimation technology. The integrated technology is capable of producing accurate and consistent spring small grains proportion estimates. Barley proportion estimation technology was not satisfactorily evaluated because LANDSAT sample segment data was not available for high density barley of primary importance in foreign regions and the low density segments examined were not judged to give indicative or unequvocal results. Generally, the spring small grains technology is ready for evaluation in a pilot experiment focusing on sensitivity analysis to a variety of agricultural and meteorological conditions representative of the global environment.

A Response Function Approach for Rapid Far-Field Tsunami Forecasting

NASA Astrophysics Data System (ADS)

Tolkova, Elena; Nicolsky, Dmitry; Wang, Dailin

2017-08-01

Predicting tsunami impacts at remote coasts largely relies on tsunami en-route measurements in an open ocean. In this work, these measurements are used to generate instant tsunami predictions in deep water and near the coast. The predictions are generated as a response or a combination of responses to one or more tsunameters, with each response obtained as a convolution of real-time tsunameter measurements and a pre-computed pulse response function (PRF). Practical implementation of this method requires tables of PRFs in a 3D parameter space: earthquake location-tsunameter-forecasted site. Examples of hindcasting the 2010 Chilean and the 2011 Tohoku-Oki tsunamis along the US West Coast and beyond demonstrated high accuracy of the suggested technology in application to trans-Pacific seismically generated tsunamis.

Space Communications and Data Systems Technologies for Next Generation Earth Science Measurements

NASA Technical Reports Server (NTRS)

Bauer, Robert A.; Reinhart, Richard C.; Hilderman, Don R.; Paulsen, Phillip E.

2003-01-01

The next generation of Earth observing satellites and sensor networks will face challenges in supporting robust high rate communications links from the increasingly sophisticated onboard instruments. Emerging applications will need data rates forecast to be in the 100's to 1000's of Mbps. As mission designers seek smaller spacecraft, challenges exist in reducing the size and power requirements while increasing the capacity of the spacecraft's communications technologies. To meet these challenges, this work looks at three areas of selected space communications and data services technologies, specifically in the development of reflectarray antennas, demonstration of space Internet concepts, and measurement of atmospheric propagation effects on Ka-band signal transmitted from LEO.

Health information technology in oncology practice: a literature review.

PubMed

Fasola, G; Macerelli, M; Follador, A; Rihawi, K; Aprile, G; Della Mea, V

2014-01-01

The adoption and implementation of information technology are dramatically remodeling healthcare services all over the world, resulting in an unstoppable and sometimes overwhelming process. After the introduction of the main elements of electronic health records and a description of what every cancer-care professional should be familiar with, we present a narrative review focusing on the current use of computerized clinical information and decision systems in oncology practice. Following a detailed analysis of the many coveted goals that oncologists have reached while embracing informatics progress, the authors suggest how to overcome the main obstacles for a complete physicians' engagement and for a full information technology adoption, and try to forecast what the future holds.