Science.gov

Sample records for grim business-as-usual forecast

  1. Where does biodiversity go from here? A grim business-as-usual forecast and a hopeful portfolio of partial solutions

    PubMed Central

    Ehrlich, Paul R.; Pringle, Robert M.

    2008-01-01

    The threats to the future of biodiversity are many and well known. They include habitat conversion, environmental toxification, climate change, and direct exploitation of wildlife, among others. Moreover, the projected addition of 2.6 billion people by mid-century will almost certainly have a greater environmental impact than that of the last 2.6 billion. Collectively, these trends portend a grim future for biodiversity under a business-as-usual scenario. These threats and their interactions are formidable, but we review seven strategies that, if implemented soundly and scaled up dramatically, would preserve a substantial portion of global biodiversity. These are actions to stabilize the human population and reduce its material consumption, the deployment of endowment funds and other strategies to ensure the efficacy and permanence of conservation areas, steps to make human-dominated landscapes hospitable to biodiversity, measures to account for the economic costs of habitat degradation, the ecological reclamation of degraded lands and repatriation of extirpated species, the education and empowerment of people in the rural tropics, and the fundamental transformation of human attitudes about nature. Like the carbon “stabilization wedges” outlined by Pacala and Socolow [Pacala S, Socolow R (2004) Stabilization wedges: Solving the climate problem for the next 50 years with current technologies. Science 305:968–972] (1), the science and technologies needed to effect this vision already exist. The remaining challenges are largely social, political, and economic. Although academic conservation biology still has an important role to play in developing technical tools and knowledge, success at this juncture hinges more on a massive mobilization of effort to do things that have traditionally been outside the scope of the discipline. PMID:18695214

  2. Colloquium paper: where does biodiversity go from here? A grim business-as-usual forecast and a hopeful portfolio of partial solutions.

    PubMed

    Ehrlich, Paul R; Pringle, Robert M

    2008-08-12

    The threats to the future of biodiversity are many and well known. They include habitat conversion, environmental toxification, climate change, and direct exploitation of wildlife, among others. Moreover, the projected addition of 2.6 billion people by mid-century will almost certainly have a greater environmental impact than that of the last 2.6 billion. Collectively, these trends portend a grim future for biodiversity under a business-as-usual scenario. These threats and their interactions are formidable, but we review seven strategies that, if implemented soundly and scaled up dramatically, would preserve a substantial portion of global biodiversity. These are actions to stabilize the human population and reduce its material consumption, the deployment of endowment funds and other strategies to ensure the efficacy and permanence of conservation areas, steps to make human-dominated landscapes hospitable to biodiversity, measures to account for the economic costs of habitat degradation, the ecological reclamation of degraded lands and repatriation of extirpated species, the education and empowerment of people in the rural tropics, and the fundamental transformation of human attitudes about nature. Like the carbon "stabilization wedges" outlined by Pacala and Socolow [Pacala S, Socolow R (2004) Stabilization wedges: Solving the climate problem for the next 50 years with current technologies. Science 305:968-972] (1), the science and technologies needed to effect this vision already exist. The remaining challenges are largely social, political, and economic. Although academic conservation biology still has an important role to play in developing technical tools and knowledge, success at this juncture hinges more on a massive mobilization of effort to do things that have traditionally been outside the scope of the discipline.

  3. The "Business-As-Usual" growth of global primary energy use and carbon dioxide emissions - historical trends and near-term forecasts

    NASA Astrophysics Data System (ADS)

    Jarvis, A.; Hewitt, C. N.

    2014-09-01

    We analyse the global primary energy use and total CO2 emissions time series since 1850 and show that their relative growth rates appear to exhibit periodicity with a fundamental timescale of ~60 years and with significant harmonic behaviour. Quantifying the inertia inherent in these dynamics allows forecasting of future "business as usual" energy needs and their associated CO2 emissions. Our best estimates for 2020 are 800 EJ yr-1 for global energy use and 14 Gt yr-1 for global CO2 emissions, with both being above almost all other published forecasts. This suggests the energy and total CO2 emissions landscape in 2020 may be significantly more challenging than currently envisaged.

  4. Geoengineering, Climate Harm, and Business as Usual

    NASA Astrophysics Data System (ADS)

    Jankunis, F. J.; Peacock, K.

    2014-12-01

    We define geoengineering (GE) as the intentional use of technology to change the planet's climate. Many people believe GE is different in kind rather than degree from any other organized activity in human history. In fact, humans caused changes in the planet's climate long before the industrial age, and all organisms engineer their environments directly or indirectly. The relevant difference between this cumulative and generally inadvertent activity and GE is the presence of intention. Now that science has revealed the extent to which humans can change the climate, however, even the continuance of Business as Usual (BAU) is, in effect, a form of intentional GE, albeit one that will cause significant climate harm, defined as effects such as sea level rise that will impact human well-being. But as with all forms of engineering, the devil is in the details: what forms of GE should be tried first? Some methods, such as large-scale afforestation, are low risk but have long-term payoffs; others, such as aerosol injection into the stratosphere, could help buy time in a warming crisis but have unknown side-effects and little long-term future. Climate change is a world-wide, inter-generational tragedy of the commons. Rational choice theory, the spatial and temporal extension of the problem, poorly fitted moral frameworks, and political maneuvering are all factors that inhibit solutions to the climate tragedy of the commons. The longer that such factors are allowed to dominate decision-making (or the lack thereof) the more likely it is that humanity will be forced to resort to riskier and more drastic forms of GE. We argue that this fact brings an additional measure of urgency to the search for ways to engineer the climate differently so as to avoid climate harm in the most lasting and least risky way.

  5. Building Florida's Future: Quality and Access or Business as Usual?

    ERIC Educational Resources Information Center

    Board of Governors, State University System of Florida, 2006

    2006-01-01

    How many of Florida's four million children should expect to attend the State University System someday? And what should they find when they arrive? The bare minimum? Or world-class universities with facilities on a par with the best the nation has to offer? This report states that a "business as usual" approach has corroded the link…

  6. Partner stalking: psychological dominance or "business as usual"?

    PubMed

    Logan, Tk; Walker, Robert

    2009-07-01

    Partner stalking may remain one of the least clearly understood forms of intimate violence. This review examines the literature guided by two main goals: (a) to examine how partner stalking is distinct from nonpartner forms of stalking and (b) to describe areas of research on partner stalking that need to be systematically addressed to deepen the understanding of partner stalking and to craft more effective mental health and criminal justice responses. These areas of research include three overarching questions: (a) Is partner stalking a unique form of psychological dominance or is it just "business as usual"? (b) What components characterize stalking differently from business as usual for women? and (c) How is psychological distress within the context of partner stalking best characterized?

  7. Mortality estimation based on Business as Usual Scenario

    NASA Astrophysics Data System (ADS)

    Pozzer, Andrea; Lelieveld, Jos; Barlas, Ceren

    2013-04-01

    Air pollution by fine particulate matter (PM2.5) and ozone (O3) has increased strongly with industrialization and urbanization. Epidemiological studies have shown that these pollutants increase lung cancer, cardiopulmonary and respiratory mortality. The atmospheric chemistry general circulation model EMAC has been used to estimate the concentration of such pollutants in recent and future years (2005, 2010, 2025 and 2050), based on a Business as Usual scenario. The emission scenario assumes that population and economic growth largely determine energy consumption and consequent pollution sources ("business as usual"). Based on the modeled pollutants concentrations and the UN estimates of population growth in the future, we assessed the premature mortality and the years of human life lost (YLL) caused by anthropogenic PM2.5 and O3 for epidemiological regions defined by the World Health Organization. The premature mortality for people of 30 years and older were estimated using a health impact function using parameters derived from epidemiological studies. Our results suggest that with a Business as Usual scenario, the ratio between mortality and population would increase of ~ 50% by 2050. This ratio, together with the increase of world population, would lead by the year 2050 to 8.9 millions premature deaths, equivalent to 79 millions of YYL.

  8. Doing "Business as Usual": Dynamics of Voice in Community Organizing Talk

    ERIC Educational Resources Information Center

    O'Connor, Kevin; Hanny, Courtney; Lewis, Cameron

    2011-01-01

    This article examines discourse in a community change project committed to undoing "business as usual"--attempts to "fix" problems within the community without involvement of residents in the process. We show how, despite commitments to recognizing community "voice," participants' orientation to powerful "centering institutions" (Jan Blommaert…

  9. Future reef decalcification under a business-as-usual CO2 emission scenario.

    PubMed

    Dove, Sophie G; Kline, David I; Pantos, Olga; Angly, Florent E; Tyson, Gene W; Hoegh-Guldberg, Ove

    2013-09-17

    Increasing atmospheric partial pressure of CO2 (pCO2) is a major threat to coral reefs, but some argue that the threat is mitigated by factors such as the variability in the response of coral calcification to acidification, differences in bleaching susceptibility, and the potential for rapid adaptation to anthropogenic warming. However the evidence for these mitigating factors tends to involve experimental studies on corals, as opposed to coral reefs, and rarely includes the influence of multiple variables (e.g., temperature and acidification) within regimes that include diurnal and seasonal variability. Here, we demonstrate that the inclusion of all these factors results in the decalcification of patch-reefs under business-as-usual scenarios and reduced, although positive, calcification under reduced-emission scenarios. Primary productivity was found to remain constant across all scenarios, despite significant bleaching and coral mortality under both future scenarios. Daylight calcification decreased and nocturnal decalcification increased sharply from the preindustrial and control conditions to the future scenarios of low (reduced emissions) and high (business-as-usual) increases in pCO2. These changes coincided with deeply negative carbonate budgets, a shift toward smaller carbonate sediments, and an increase in the abundance of sediment microbes under the business-as-usual emission scenario. Experimental coral reefs demonstrated highest net calcification rates and lowest rates of coral mortality under preindustrial conditions, suggesting that reef processes may not have been able to keep pace with the relatively minor environmental changes that have occurred during the last century. Taken together, our results have serious implications for the future of coral reefs under business-as-usual environmental changes projected for the coming decades and century.

  10. Integrating telehealth in to 'business as usual': Is it really possible?

    PubMed

    Jury, Susan C; Kornberg, Andrew J

    2016-12-01

    The Royal Children's Hospital, Melbourne, began offering web-based telehealth video consultation in 2011, with the principle being that telehealth should be integrated into 'business as usual'. In telehealth literature, key differences between telehealth and in-person consultations can make this hard to achieve, so an audit was performed that revealed many small gaps in the process.A total of 125 telehealth appointments were booked during the study period. Of these, 13% (n = 16) were rescheduled, cancelled or changed to face-to-face appointments, and up to two main issues were identified for the remaining appointments. Some 69% of the remaining 108 appointments (n = 75) were completed successfully, with 23% (n = 25) completely seamless end to end. Overall, 39 issues were administrative (40%), 34 technical (35%) and 24 scheduling (25%); nine (8%) required some minor troubleshooting.For long-term sustainability, integrating telehealth into business as usual needs to remain the target. Scheduling and technical glitches were the main barriers to seamless telehealth. Several issues have now been addressed with the introduction of an electronic medical record, and the development of standardised processes and staff training.

  11. Business as Usual: A Lack of Institutional Innovation in Global Health Governance

    PubMed Central

    Lee, Kelley

    2017-01-01

    There were once again high expectations that a major global health event - the Ebola virus outbreak of 2014-2015 - would trigger meaningfully World Health Organization (WHO) reform and strengthen global health governance (GHG). Rather than a "turning point," however, the global community has gone back to business as usual. This has occurred against a backdrop of worldwide political turmoil, characterised by a growing rejection of existing political leaders and state-centric institutions. Debates about GHG so far have given insufficient attention to the need for institutional innovation. This entails rethinking the traditional bureaucratic model of postwar intergovernmental organizations which is disconnected from the transboundary, fast-paced nature of today’s globalizing world.

  12. Effects of business-as-usual anthropogenic emissions on air quality

    NASA Astrophysics Data System (ADS)

    Pozzer, A.; Zimmermann, P.; Doering, U. M.; van Aardenne, J.; Tost, H.; Dentener, F.; Janssens-Maenhout, G.; Lelieveld, J.

    2012-08-01

    The atmospheric chemistry general circulation model EMAC has been used to estimate the impact of anthropogenic emission changes on global and regional air quality in recent and future years (2005, 2010, 2025 and 2050). The emission scenario assumes that population and economic growth largely determine energy and food consumption and consequent pollution sources with the current technologies ("business as usual"). This scenario is chosen to show the effects of not implementing legislation to prevent additional climate change and growing air pollution, other than what is in place for the base year 2005, representing a pessimistic (but plausible) future. By comparing with recent observations, it is shown that the model reproduces the main features of regional air pollution distributions though with some imprecisions inherent to the coarse horizontal resolution (~100 km) and simplified bottom-up emission input. To identify possible future hot spots of poor air quality, a multi pollutant index (MPI), suited for global model output, has been applied. It appears that East and South Asia and the Middle East represent such hotspots due to very high pollutant concentrations, while a general increase of MPIs is observed in all populated regions in the Northern Hemisphere. In East Asia a range of pollutant gases and fine particulate matter (PM2.5) is projected to reach very high levels from 2005 onward, while in South Asia air pollution, including ozone, will grow rapidly towards the middle of the century. Around the Persian Gulf, where natural PM2.5 concentrations are already high (desert dust), ozone levels are expected to increase strongly. The population weighted MPI (PW-MPI), which combines demographic and pollutant concentration projections, shows that a rapidly increasing number of people worldwide will experience reduced air quality during the first half of the 21st century. Following this business as usual scenario, it is projected that air quality for the global

  13. Effects of business-as-usual anthropogenic emissions on air quality

    NASA Astrophysics Data System (ADS)

    Pozzer, A.; Zimmermann, P.; Doering, U. M.; van Aardenne, J.; Tost, H.; Dentener, F.; Janssens-Maenhout, G.; Lelieveld, J.

    2012-04-01

    The atmospheric chemistry general circulation model EMAC has been used to estimate the impact of anthropogenic emission changes on global and regional air quality in recent and future years (2005, 2010, 2025 and 2050). The emission scenario assumes that population and economic growth largely determine energy and food consumption and consequent pollution sources with the current technologies ("business as usual"). This scenario is chosen to show the effects of not implementing legislation to prevent additional climate change and growing air pollution, other than what is in place for the base year 2005, representing a pessimistic (but feasible) future. By comparing with recent observations, it is shown that the model reproduces the main features of regional air pollution distributions though with some imprecisions inherent to the coarse horizontal resolution (~100 km) and simplified bottom-up emission input. To identify possible future hot spots of poor air quality, a multi pollutant index (MPI), suited for global model output, has been applied. It appears that East and South Asia and the Middle East represent such hotspots due to very high pollutant concentrations, although a general increase of MPIs is observed in all populated regions in the Northern Hemisphere. In East Asia a range of pollutant gases and fine particulate matter (PM2.5) is projected to reach very high levels from 2005 onward, while in South Asia air pollution, including ozone, will grow rapidly towards the middle of the century. Around the Arabian Gulf, where natural PM2.5 concentrations are already high (desert dust), ozone levels are expected to increase strongly. The per capita MPI (PCMPI), which combines demographic and pollutants concentrations projections, shows that a rapidly increasing number of people worldwide will experience reduced air quality during the first half of the 21st century. Following the business as usual scenario, it is projected that air quality for the global average

  14. Vietnam's forest transition in retrospect: demonstrating weaknesses in business-as-usual scenarios for REDD.

    PubMed

    Ankersen, Jeppe; Grogan, Kenneth; Mertz, Ole; Fensholt, Rasmus; Castella, Jean-Christophe; Lestrelin, Guillaume; Nguyen, Dinh Tien; Danielsen, Finn; Brofeldt, Søren; Rasmussen, Kjeld

    2015-05-01

    One of the prerequisites of the REDD+ mechanism is to effectively predict business-as-usual (BAU) scenarios for change in forest cover. This would enable estimation of how much carbon emission a project could potentially prevent and thus how much carbon credit should be rewarded. However, different factors like forest degradation and the lack of linearity in forest cover transitions challenge the accuracy of such scenarios. Here we predict and validate such BAU scenarios retrospectively based on forest cover changes at village and district level in North Central Vietnam. With the government's efforts to increase the forest cover, land use policies led to gradual abandonment of shifting cultivation since the 1990s. We analyzed Landsat images from 1973, 1989, 1998, 2000, and 2011 and found that the policies in the areas studied did lead to increased forest cover after a long period of decline, but that this increase could mainly be attributed to an increase in open forest and shrub areas. We compared Landsat classifications with participatory maps of land cover/use in 1998 and 2012 that indicated more forest degradation than was captured by the Landsat analysis. The BAU scenarios were heavily dependent on which years were chosen for the reference period. This suggests that hypothetical REDD+ activities in the past, when based on the remote sensing data available at that time, would have been unable to correctly estimate changes in carbon stocks and thus produce relevant BAU scenarios.

  15. Vietnam's Forest Transition in Retrospect: Demonstrating Weaknesses in Business-as-Usual Scenarios for REDD+

    NASA Astrophysics Data System (ADS)

    Ankersen, Jeppe; Grogan, Kenneth; Mertz, Ole; Fensholt, Rasmus; Castella, Jean-Christophe; Lestrelin, Guillaume; Nguyen, Dinh Tien; Danielsen, Finn; Brofeldt, Søren; Rasmussen, Kjeld

    2015-05-01

    One of the prerequisites of the REDD+ mechanism is to effectively predict business-as-usual (BAU) scenarios for change in forest cover. This would enable estimation of how much carbon emission a project could potentially prevent and thus how much carbon credit should be rewarded. However, different factors like forest degradation and the lack of linearity in forest cover transitions challenge the accuracy of such scenarios. Here we predict and validate such BAU scenarios retrospectively based on forest cover changes at village and district level in North Central Vietnam. With the government's efforts to increase the forest cover, land use policies led to gradual abandonment of shifting cultivation since the 1990s. We analyzed Landsat images from 1973, 1989, 1998, 2000, and 2011 and found that the policies in the areas studied did lead to increased forest cover after a long period of decline, but that this increase could mainly be attributed to an increase in open forest and shrub areas. We compared Landsat classifications with participatory maps of land cover/use in 1998 and 2012 that indicated more forest degradation than was captured by the Landsat analysis. The BAU scenarios were heavily dependent on which years were chosen for the reference period. This suggests that hypothetical REDD+ activities in the past, when based on the remote sensing data available at that time, would have been unable to correctly estimate changes in carbon stocks and thus produce relevant BAU scenarios.

  16. Business as Usual

    ERIC Educational Resources Information Center

    Cohen, Jeremy

    2010-01-01

    Even in an industry where rapid change is the status quo, it takes a special kind of company to handle the training challenges posed by a major corporate acquisition and massive product rollout. No one has ever accused Verizon of thinking small-scale when it comes to training initiatives, but over the last year, the telecommunications giant…

  17. Does environmental certification in coffee promote "business as usual"? A case study from the Western Ghats, India.

    PubMed

    Bose, Arshiya; Vira, Bhaskar; Garcia, Claude

    2016-12-01

    Conservation initiatives are designed to address threats to forests and biodiversity, often through partnerships with natural-resource users who are incentivized to change their land-use and livelihood practices to avoid further biodiversity loss. In particular, direct incentives programmes that provide monetary benefits are commended for being effective in achieving conservation across short timescales. In biodiversity-rich areas, outside protected areas, such as coffee agroforestry systems, direct incentives, such as certification schemes, are used to motivate coffee producers to maintain native tree species, natural vegetation, restrict wildlife hunting, and conserve soil and water, in addition to encouraging welfare of workers. However, despite these claims, there is a lack of strong evidence of the on-ground impact of such schemes. To assess the conservation importance of certification, we describe a case study in the Western Ghats biodiversity hotspot of India, in which coffee growers are provided price incentives to adopt Rainforest Alliance certification standards. We analyse the conservation and social outcomes of this programme by studying peoples' experiences of participating in certification. Despite high compliance and effective implementation, we find a strong case for the endorsement of 'business as usual' with no changes in farm management as a result of certification. We find that such 'business as usual' participation in certification creates grounds for diminishing credibility and local support for conservation efforts. Working towards locally relevant conservation interventions, rather than implementing global blueprints, may lead to more meaningful biodiversity conservation and increased community support for conservation initiatives in coffee landscapes.

  18. Probabilistic Forecast for 21st Century Climate Based on an Ensemble of Simulations using a Business-As-Usual Scenario

    NASA Astrophysics Data System (ADS)

    Scott, J. R.; Forest, C. E.; Sokolov, A. P.; Dutkiewicz, S.

    2011-12-01

    The behavior of the climate system is examined in an ensemble of runs using an Earth System Model of intermediate complexity. Climate "parameters" varied are the climate sensitivity, the aerosol forcing, and the strength of ocean heat uptake. Variations in the latter were accomplished by changing the strength of the oceans' background vertical mixing. While climate sensitivity and aerosol forcing can be varied over rather wide ranges, it is more difficult to create such variation in heat uptake while maintaining a realistic overturning ocean circulation. Therefore, separate ensembles were carried out for a few values of the vertical diffusion coefficient. Joint probability distributions for climate sensitivity and aerosol forcing are constructed by comparing results from 20th century simulations with available observational data. These distributions are then used to generate ensembles of 21st century simulations; results allow us to construct probabilistic distributions for changes in important climate change variables such as surface air temperature, sea level rise, and magnitude of the AMOC. Changes in the rate of air-sea flux of CO2 and the export of carbon into the deep ocean are also examined.

  19. Changes in snowmelt runoff timing in western North America under a 'business as usual' climate change scenario

    USGS Publications Warehouse

    Stewart, I.T.; Cayan, D.R.; Dettinger, M.D.

    2004-01-01

    Spring snowmelt is the most important contribution of many rivers in western North America. If climate changes, this contribution may change. A shift in the timing of springtime snowmelt towards earlier in the year already is observed during 1948-2000 in many western rivers. Streamflow timing changes for the 1995-2099 period are projected using regression relations between observed streamflow-timing responses in each river, measured by the temporal centroid of streamflow (CT) each year, and local temperature (TI) and precipitation (PI) indices. Under 21st century warming trends predicted by the Parallel Climate Model (PCM) under business-as-usual greenhouse-gas emissions, streamflow timing trends across much of western North America suggest even earlier springtime snowmelt than observed to date. Projected CT changes are consistent with observed rates and directions of change during the past five decades, and are strongest in the Pacific Northwest, Sierra Nevada, and Rocky Mountains, where many rivers eventually run 30-40 days earlier. The modest PI changes projected by PCM yield minimal CT changes. The responses of CT to the simultaneous effects of projected TI and PI trends are dominated by the TI changes. Regression-based CT projections agree with those from physically-based simulations of rivers in the Pacific Northwest and Sierra Nevada.

  20. Regional Assessment of Urban Impacts on Landcover and Open Space Finds a Smart Urban Growth Policy Performs Little Better than Business as Usual

    PubMed Central

    Thorne, James H.; Santos, Maria J.; Bjorkman, Jacquelyn H.

    2013-01-01

    Assessment of landscape change is critical for attainment of regional sustainability goals. Urban growth assessments are needed because over half the global population now lives in cities, which impact biodiversity, ecosystem structure and ecological processes. Open space protection is needed to preserve these attributes, and provide the resources humans need. The San Francisco Bay Area, California, is challenged to accommodate a population increase of 3.07 million while maintaining the region’s ecosystems and biodiversity. Our analysis of 9275 km2 in the Bay Area links historic trends for three measures: urban growth, protected open space, and landcover types over the last 70 years to future 2050 projections of urban growth and open space. Protected open space totaled 348 km2 (3.7% of the area) in 1940, and expanded to 2221 km2 (20.2%) currently. An additional 1038 km2 of protected open space is targeted (35.1%). Urban area historically increased from 396.5 km2 to 2239 km2 (24.1% of the area). Urban growth during this time mostly occurred at the expense of agricultural landscapes (62.9%) rather than natural vegetation. Smart Growth development has been advanced as a preferred alternative in many planning circles, but we found that it conserved only marginally more open space than Business-as-usual when using an urban growth model to portray policies for future urban growth. Scenarios to 2050 suggest urban development on non-urban lands of 1091, 956, or 179 km2, under Business-as-usual, Smart Growth and Infill policy growth scenarios, respectively. The Smart Growth policy converts 88% of natural lands and agriculture used by Business-as-usual, while Infill used only 40% of those lands. Given the historic rate of urban growth, 0.25%/year, and limited space available, the Infill scenario is recommended. While the data may differ, the use of an historic and future framework to track these three variables can be easily applied to other metropolitan areas. PMID

  1. Regional assessment of urban impacts on landcover and open space finds a smart urban growth policy performs little better than business as usual.

    PubMed

    Thorne, James H; Santos, Maria J; Bjorkman, Jacquelyn H

    2013-01-01

    Assessment of landscape change is critical for attainment of regional sustainability goals. Urban growth assessments are needed because over half the global population now lives in cities, which impact biodiversity, ecosystem structure and ecological processes. Open space protection is needed to preserve these attributes, and provide the resources humans need. The San Francisco Bay Area, California, is challenged to accommodate a population increase of 3.07 million while maintaining the region's ecosystems and biodiversity. Our analysis of 9275 km² in the Bay Area links historic trends for three measures: urban growth, protected open space, and landcover types over the last 70 years to future 2050 projections of urban growth and open space. Protected open space totaled 348 km² (3.7% of the area) in 1940, and expanded to 2221 km² (20.2%) currently. An additional 1038 km² of protected open space is targeted (35.1%). Urban area historically increased from 396.5 km² to 2239 km² (24.1% of the area). Urban growth during this time mostly occurred at the expense of agricultural landscapes (62.9%) rather than natural vegetation. Smart Growth development has been advanced as a preferred alternative in many planning circles, but we found that it conserved only marginally more open space than Business-as-usual when using an urban growth model to portray policies for future urban growth. Scenarios to 2050 suggest urban development on non-urban lands of 1091, 956, or 179 km², under Business-as-usual, Smart Growth and Infill policy growth scenarios, respectively. The Smart Growth policy converts 88% of natural lands and agriculture used by Business-as-usual, while Infill used only 40% of those lands. Given the historic rate of urban growth, 0.25%/year, and limited space available, the Infill scenario is recommended. While the data may differ, the use of an historic and future framework to track these three variables can be easily applied to other metropolitan areas.

  2. Effects of "Reduced" and "Business-As-Usual" CO2 Emission Scenarios on the Algal Territories of the Damselfish Pomacentrus wardi (Pomacentridae).

    PubMed

    Bender, Dorothea; Champ, Connor Michael; Kline, David; Diaz-Pulido, Guillermo; Dove, Sophie

    2015-01-01

    Turf algae are a very important component of coral reefs, featuring high growth and turnover rates, whilst covering large areas of substrate. As food for many organisms, turf algae have an important role in the ecosystem. Farming damselfish can modify the species composition and productivity of such algal assemblages, while defending them against intruders. Like all organisms however, turf algae and damselfishes have the potential to be affected by future changes in seawater (SW) temperature and pCO2. In this study, algal assemblages, in the presence and absence of farming Pomacentrus wardi were exposed to two combinations of SW temperature and pCO2 levels projected for the austral spring of 2100 (the B1 "reduced" and the A1FI "business-as-usual" CO2 emission scenarios) at Heron Island (GBR, Australia). These assemblages were dominated by the presence of red algae and non-epiphytic cyanobacteria, i.e. cyanobacteria that grow attached to the substrate rather than on filamentous algae. The endpoint algal composition was mostly controlled by the presence/absence of farming damselfish, despite a large variability found between the algal assemblages of individual fish. Different scenarios appeared to be responsible for a mild, species specific change in community composition, observable in some brown and green algae, but only in the absence of farming fish. Farming fish appeared unaffected by the conditions to which they were exposed. Algal biomass reductions were found under "reduced" CO2 emission, but not "business-as-usual" scenarios. This suggests that action taken to limit CO2 emissions may, if the majority of algae behave similarly across all seasons, reduce the potential for phase shifts that lead to algal dominated communities. At the same time the availability of food resources to damselfish and other herbivores would be smaller under "reduced" emission scenarios.

  3. Antibiotic research and development: business as usual?

    PubMed

    Harbarth, S; Theuretzbacher, U; Hackett, J

    2015-01-01

    The global burden of antibiotic resistance is tremendous and, without new anti-infective strategies, will continue to increase in the coming decades. Despite the growing need for new antibiotics, few pharmaceutical companies today retain active antibacterial drug discovery programmes. One reason is that it is scientifically challenging to discover new antibiotics that are active against the antibiotic-resistant bacteria of current clinical concern. However, the main hurdle is diminishing economic incentives. Increased global calls to minimize the overuse of antibiotics, the cost of meeting regulatory requirements and the low prices of currently marketed antibiotics are strong deterrents to antibacterial drug development programmes. New economic models that create incentives for the discovery of new antibiotics and yet reconcile these incentives with responsible antibiotic use are long overdue. DRIVE-AB is a €9.4 million public-private consortium, funded by the EU Innovative Medicines Initiative, that aims to define a standard for the responsible use of antibiotics and to develop, test and recommend new economic models to incentivize investment in producing new anti-infective agents.

  4. Business as Usual? Not in Vermont.

    ERIC Educational Resources Information Center

    Proulx, Raymond J.; Jimerson, Lorna

    1998-01-01

    Vermont's Equal Education Opportunity Act of 1997 will radically increase the proportion of state money designated for public education and transform the entire state taxation system. Spurred by a court decision invalidating the state's school finance system, Act 60 establishes a statewide property tax for a general state support grant, includes…

  5. The Escalation of Business as Usual

    ERIC Educational Resources Information Center

    Tuchman, Gaye

    2011-01-01

    An academic plan is a business plan disguised in the regalia donned for significant public ceremonies--black cap and gown, colorful hood, and, of course, gold tassel. Several years ago, the University of Connecticut started to plan for the economic disaster that was at the time so obviously in the future of higher education institutions. A formal…

  6. Teaching across Borders: Business as Usual?

    ERIC Educational Resources Information Center

    Allen, Bobbe McGhie

    2011-01-01

    The quest to comprehend how cultural differences can impact learning is one of those intriguing challenges that continue to beguile some scholars and educational leaders even at a time that is characterized as globalized. This dissertation is a qualitative case study about teaching to culturally diverse populations and is primarily based on the…

  7. GRIM: General Relativistic Implicit Magnetohydrodynamics

    NASA Astrophysics Data System (ADS)

    Chandra, Mani; Foucart, Francois; Gammie, Charles F.

    2017-02-01

    GRIM (General Relativistic Implicit Magnetohydrodynamics) evolves a covariant extended magnetohydrodynamics model derived by treating non-ideal effects as a perturbation of ideal magnetohydrodynamics. Non-ideal effects are modeled through heat conduction along magnetic field lines and a difference between the pressure parallel and perpendicular to the field lines. The model relies on an effective collisionality in the disc from wave-particle scattering and velocity-space (mirror and firehose) instabilities. GRIM, which runs on CPUs as well as on GPUs, combines time evolution and primitive variable inversion needed for conservative schemes into a single step using only the residuals of the governing equations as inputs. This enables the code to be physics agnostic as well as flexible regarding time-stepping schemes.

  8. Indicators for European Union Policies. Business as Usual?

    ERIC Educational Resources Information Center

    Saltelli, Andrea; D'Hombres, Beatrice; Jesinghaus, Jochen; Manca, Anna Rita; Mascherini, Massimiliano; Nardo, Michela; Saisana, Michaela

    2011-01-01

    This paper looks at the role of "statistics-based knowledge" in the making of EU policy. We highlight "shortcomings" in the use of statistical indicators made in the course of the Lisbon strategy, ended in 2010. In our opinion the shortcomings are: (i) The paradox of the "coexistence" within the same European…

  9. Working With Suicidal Clients: "Not" Business as Usual

    ERIC Educational Resources Information Center

    Ellis, Thomas E.; Goldston, David B.

    2012-01-01

    In this introduction to a special series of articles on working with suicidal clients, we note that much of the recent growth in theory and research pertaining to suicidal individuals has been contributed by cognitive-behavioral theorists and researchers. This work has established that suicidal people manifest important cognitive vulnerabilities…

  10. Business as Usual? Not for These Middle-Grades Students

    ERIC Educational Resources Information Center

    Crawford, Heather; Wiest, Lynda

    2011-01-01

    A perpetual dilemma of schooling is how to help students develop skills needed for everyday life, including the work world. Quantitative literacy, also called numeracy, involves an ability to apply essential mathematics skills to authentic or near-authentic tasks. Carefully planned classroom activities can help students develop these important…

  11. Business as Usual: Amazon.com and the Academic Library

    ERIC Educational Resources Information Center

    Van Ullen, Mary K.; Germain, Carol Anne

    2002-01-01

    In 1999, Steve Coffman proposed that libraries form a single interlibrary loan based entity patterned after Amazon.com. This study examined the suitability of Amazon.com's Web interface and record enhancements for academic libraries. Amazon.com could not deliver circulating monographs in the University at Albany Libraries' collection quickly…

  12. Insurance benefits under the ADA: Discrimination or business as usual?

    SciTech Connect

    McFadden, M.E.

    1993-12-31

    In December 1987, John McGann discovered he had AIDS. In July 1988, his employer altered his health insurance policy by reducing lifetime coverage for AIDS to $5,000, while maintaining the million-dollar limit for all other health conditions. The United States Court of Appeals for the Fifth Circuit upheld the employer`s right to make that change. The Supreme Court denied certiori. Public outcry was immediate and voluminous. The Solicitor General argued that the new Americans with Disabilities Act would save future John McGanns from the same treatment, but the validity of this optimistic prediction is yet to be determined. The Americans with Disabilities Act of 1990 (ADA) is landmark legislation that bars discrimination against the disabled in all aspects of employment, public services, and accommodations. The Act broadly defines disability to include illnesses such as AIDS and cancer, as well as limitations on mobility, vision, and hearing. The ADA indisputably creates a private cause of action for discrimination on the basis of disability. However, depending on the standard of review chosen by the federal courts, this cause of action may or may not provide much protection to those claiming discrimination on the basis of disability in employee benefits and insurance. This article discusses the ADA`s coverage of insurance and benefits in light of the possible standards courts might use to evaluate actions of parties in suits alleging discrimination in these areas and applies those standards of review to the facts of the McGann case. 146 refs.

  13. Establishing Wraparound Fidelity: Not Business as Usual. Symposium.

    ERIC Educational Resources Information Center

    Malysiak, Rosalyn; Duchnowski, Albert J.; Dollard, Norin; Slewczkowski, Robert; Black, Marcia; Greeson, Michael

    Three summaries of papers presented in a symposium examine issues in the wraparound model of providing case management and mental health services to children and adolescents with emotional/behavioral disorders. The papers describe 30 months of participatory program evaluation and simultaneous program development between the University of South…

  14. Business as Usual? It's Just Not an Option

    ERIC Educational Resources Information Center

    Blewitt, John

    2010-01-01

    There is no doubt that in order to address the serious challenges arising from anthropogenic--or human-produced--climate change, Britain, along with the rest of the world, needs to adopt policies and develop skills that will create a low-carbon economy with a highly effective use of renewable and natural resources. People need to create the…

  15. The Learning Outcomes Project: Not Business as Usual

    ERIC Educational Resources Information Center

    Heiland, Linda; Switzer-Kemper, Cathy

    2007-01-01

    Central Arizona College successfully defined student learning outcomes and is building a culture of evidence to support the Learning Paradigm. Recent data indicate great strides in the improvement of student learning. Qualitative research produced meaningful comparisons of leadership and faculty perceptions of the process of developing student…

  16. Global/Regional Integrated Model System (GRIMs): Double Fourier Series (DFS) Dynamical Core

    NASA Astrophysics Data System (ADS)

    Koo, M.; Hong, S.

    2013-12-01

    A multi-scale atmospheric/oceanic model system with unified physics, the Global/Regional Integrated Model system (GRIMs) has been created for use in numerical weather prediction, seasonal simulations, and climate research projects, from global to regional scales. It includes not only the model code, but also the test cases and scripts. The model system is developed and practiced by taking advantage of both operational and research applications. We outlines the history of GRIMs, its current applications, and plans for future development, providing a summary useful to present and future users. In addition to the traditional spherical harmonics (SPH) dynamical core, a new spectral method with a double Fourier series (DFS) is available in the GRIMs (Table 1). The new DFS dynamical core with full physics is evaluated against the SPH dynamical core in terms of short-range forecast capability for a heavy rainfall event and seasonal simulation framework. Comparison of the two dynamical cores demonstrates that the new DFS dynamical core exhibits performance comparable to the SPH in terms of simulated climatology accuracy and the forecast of a heavy rainfall event. Most importantly, the DFS algorithm guarantees improved computational efficiency in the cluster computer as the model resolution increases, which is consistent with theoretical values computed from the dry primitive equation model framework of Cheong (Fig. 1). The current study shows that, at higher resolutions, the DFS approach can be a competitive dynamical core because the DFS algorithm provides the advantages of both the spectral method for high numerical accuracy and the grid-point method for high performance computing in the aspect of computational cost. GRIMs dynamical cores

  17. Updates in the Global/Regional Integrated Model system (GRIMs)-Double Fourier Series (DFS) Dynamical Core

    NASA Astrophysics Data System (ADS)

    Koo, M. S.; Park, H.; Park, S. H.; Hong, S. Y.

    2014-12-01

    The Global/Regional Integrated Model system (GRIMs)-double Fourier series (DFS) spectral dynamical core has been developed to overcome the limitation of traditional spectral model using spherical harmonics in terms of computational cost at very high resolution. Recently, the GRIMs-DFS dynamical core was updated in two respects: (1) better scalability on high-performance computing platform; and (2) reduction of numerical time-stepping error. To improve the parallel efficiency, the archived wave domain was designed not to be sliced in the meridional direction, but to be decomposed in the horizontal and vertical directions. Although the computational cost slightly increased due to the requirement of temporary work array, the revised DFS dynamical core yielded higher scalability in terms of the wall-clock-time than the original one. In addition, its efficiency gain became greater with the increase of horizontal resolution when the number of processors is increased. The Robert-Asselin-Williams (RAW) time filter has been proposed as a simple improvement to the widely used Robert-Asselin filter, in order to reduce time-stepping errors in semi-implicit leapfrog integration. This new approach was implemented into the GRIMs-DFS dynamical core and its impact was quantitatively evaluated on medium-range forecast and seasonal ensemble prediction frameworks. Preliminary results showed that the RAW time-filter properly reduced spurious light rainfalls that might be produced from unphysical computational mode generated by leap-frog time stepping. Further details will be presented in the conference.

  18. grim: A Flexible, Conservative Scheme for Relativistic Fluid Theories

    NASA Astrophysics Data System (ADS)

    Chandra, Mani; Foucart, Francois; Gammie, Charles F.

    2017-03-01

    Hot, diffuse, relativistic plasmas such as sub-Eddington black-hole accretion flows are expected to be collisionless, yet are commonly modeled as a fluid using ideal general relativistic magnetohydrodynamics (GRMHD). Dissipative effects such as heat conduction and viscosity can be important in a collisionless plasma and will potentially alter the dynamics and radiative properties of the flow from that in ideal fluid models; we refer to models that include these processes as Extended GRMHD. Here we describe a new conservative code, grim, that enables all of the above and additional physics to be efficiently incorporated. grim combines time evolution and primitive variable inversion needed for conservative schemes into a single step using an algorithm that only requires the residuals of the governing equations as inputs. This algorithm enables the code to be physics agnostic as well as flexibility regarding time-stepping schemes. grim runs on CPUs, as well as on GPUs, using the same code. We formulate a performance model and use it to show that our implementation runs optimally on both architectures. grim correctly captures classical GRMHD test problems as well as a new suite of linear and nonlinear test problems with anisotropic conduction and viscosity in special and general relativity. As tests and example applications, we resolve the shock substructure due to the presence of dissipation, and report on relativistic versions of the magneto-thermal instability and heat flux driven buoyancy instability, which arise due to anisotropic heat conduction, and of the firehose instability, which occurs due to anisotropic pressure (i.e., viscosity). Finally, we show an example integration of an accretion flow around a Kerr black hole, using Extended GRMHD.

  19. The UN Decade of Education for Sustainable Development: Business as Usual in the End

    ERIC Educational Resources Information Center

    Huckle, John; Wals, Arjen E. J.

    2015-01-01

    An analysis of the literature supporting the UN Decade of Education for Sustainable Development and a sample of its key products suggests that it failed to acknowledge or challenge neoliberalism as a hegemonic force blocking transitions towards genuine sustainability. The authors argue that the rationale for the Decade was idealistic and that…

  20. Business as Usual? A Review of Continuing Professional Education and Adult Learning

    ERIC Educational Resources Information Center

    Wittnebel, Leo

    2012-01-01

    The commodification of education in all forms has created a lucrative trade, particularly within the realm of continuing professional education. Mandated across a wide spectrum of industries, and particularly salient in healthcare due to rapid advances in medicine and technology, professional education is said to be the vehicle that keeps…

  1. Business as Usual or Brave New World? A College President's Perspective.

    ERIC Educational Resources Information Center

    Keohane, Nannerl O.

    1986-01-01

    The Sloan Foundation's New Liberal Arts Program aims to make a fundamental transformation in the liberal arts curriculum, by infusing applied mathematics and technological literacy. The program is examined by the president of Wellesley College in the context of current philosophical and practical constraints in higher education. (MSE)

  2. A Look in the Mirror: Challenging "Business As Usual" in Teacher Preparation

    ERIC Educational Resources Information Center

    Chou, Victoria

    2005-01-01

    The "raison d'etre" for traditional schools of education has radically shifted in recent years. Research demonstrates that schools have been remarkably unsuccessful at reducing the unacceptable achievement gap between black and Latino students, on the one hand, and white students, on the other, and some have laid the blame at the feet of…

  3. India’s Seventh Fire-Year Plan: New Departures or Business as Usual?

    DTIC Science & Technology

    1986-01-01

    output of food faster than the population was growing; (2) creating a solid industrial base across the whole spectrum of productsz- chemicals , electrical...reliance in basic industries, such as steel, machine tools, defense goods, heavy electricals, and primary chemicals , appears in retrospect to have been...tneir tecnnologies are growing obsolete. Hydropower turbines, the steel mills, chemical plants, and the railways all need substantial renovation and

  4. "No-Business-As-Usual German": A Critical Pedagogy of Business German

    ERIC Educational Resources Information Center

    Robinson, Benjamin

    2004-01-01

    In this article, the author describes his "Business German" course. His course sought to narrate a dialectic of agency and institution. He started by asserting a distinction between the intending subject--with its plural desires, interests, and identifications--and the world it acts in, through and upon. This distinction between acting subject and…

  5. It's Not Business as Usual: New and Emerging Career in Marketing, Finance, and Management

    ERIC Educational Resources Information Center

    Miller, April J.

    2010-01-01

    There have been many changes in the field of business as a result of technological advancements, government regulations, and shifts in focus. These new career opportunities have arisen as a result: social media marketers, financial examiners, and project managers. In this article, the author discusses these new and emerging career opportunities in…

  6. Interpreted consultations as 'business as usual'? An analysis of organisational routines in general practices.

    PubMed

    Greenhalgh, Trisha; Voisey, Christopher; Robb, Nadia

    2007-09-01

    UK general practices operate in an environment of high linguistic diversity, because of recent large-scale immigration and of the NHS's commitment to provide a professional interpreter to any patient if needed. Much activity in general practice is co-ordinated and patterned into organisational routines (defined as repeated patterns of interdependent actions, involving multiple actors, bound by rules and customs) that tend to be stable and to persist. If we want to understand how general practices are responding to pressures to develop new routines, such as interpreted consultations, we need to understand how existing organisational routines change. This will then help us to address a second question, which is how the interpreted consultation itself is being enacted and changing as it becomes routinised (or not) in everyday general practice. In seeking answers to these two questions, we undertook a qualitative study of narratives of interpreted primary care consultations in three London boroughs with large minority ethnic populations. In 69 individual interviews and two focus groups, we sought accounts of interpreted consultations from service users, professional interpreters, family member interpreters, general practitioners, practice nurses, receptionists, and practice managers. We asked participants to tell us both positive and negative stories of their experiences. We analysed these data by searching for instances of concepts relating to the organisational routine, the meaning of the interpreted consultation to the practice, and the sociology of medical work. Our findings identified a number of general properties of the interpreted consultation as an organisational routine, including the wide variation in the form of adoption, the stability of the routine, the adaptability of the routine, and the strength of the routine. Our second key finding was that this variation could be partly explained by characteristics of the practice as an organisation, especially whether it was traditional (small, family-run, 'personal' identity, typically multilingual, loose division of labour, relatively insular) or contemporary (large, bureaucratic, 'efficient' identity, typically monolingual, clear division of labour, richly networked). We conclude that there is a fruitful research agenda to be explored that links the organisational dimension of interpreting services with studies of clinical care and outcomes.

  7. Beyond Business as Usual? Better Buying Power and the Prospects for Change in Defense Acquisition

    DTIC Science & Technology

    2014-04-30

    Battlefield [Speech]. Washington, DC: DoD. Salamon , L. (2002). The tools of government: A guide to the new governance. Lester Salamon (Ed.), New...partnerships. Indeed, as an intellectual endeavor, policy implementation is at present very “tools-focused” (see Salamon , 2002). Despite its

  8. GRIM-19 inhibits v-Src-induced cell motility by interfering with cytoskeletal restructuring

    PubMed Central

    Sun, Peng; Nallar, Shreeram C.; Kalakonda, Sudhakar; Lindner, Daniel J.; Martin, Stuart S.; Kalvakolanu, Dhananjaya V.

    2008-01-01

    GRIM-19 (Gene associated with Retinoid-Interferon-induced Mortality 19) is a novel tumor suppressor regulated by Interferon/retinoid combination. We have recently shown that GRIM-19 inhibits v-Src-induced oncogenic transformation and metastatic behavior of cells. Oncogenic v-Src induces cell motility by cytoskeletal remodeling especially the formation of podosomes and. Here we show that GRIM-19 inhibited the v-Src-induced cell motility by inhibiting cytoskeletal remodeling i.e., podosome formation. We also show that the N-terminus of GRIM-19 played a major role in this process and identified critical residues in this region. More importantly, we show that tumor-associated GRIM-19 mutations disrupted its ability to inhibit v-Src-induced cell motility. These actions appear to occur independently of STAT3, a known target of GRIM-19-mediated inhibition. Lastly, tumor-associated GRIM-19 mutants significantly lost their ability to control v-Src-induced metastases in vivo, indicating the biological and pathological significance of these observations. PMID:19151760

  9. Structural analysis of a functional DIAP1 fragment bound to grim and hid peptides.

    PubMed

    Wu, J W; Cocina, A E; Chai, J; Hay, B A; Shi, Y

    2001-07-01

    The inhibitor of apoptosis protein DIAP1 suppresses apoptosis in Drosophila, with the second BIR domain (BIR2) playing an important role. Three proteins, Hid, Grim, and Reaper, promote apoptosis, in part by binding to DIAP1 through their conserved N-terminal sequences. The crystal structures of DIAP1-BIR2 by itself and in complex with the N-terminal peptides from Hid and Grim reveal that these peptides bind a surface groove on DIAP1, with the first four amino acids mimicking the binding of the Smac tetrapeptide to XIAP. The next 3 residues also contribute to binding through hydrophobic interactions. Interestingly, peptide binding induces the formation of an additional alpha helix in DIAP1. Our study reveals the structural conservation and diversity necessary for the binding of IAPs by the Drosophila Hid/Grim/Reaper and the mammalian Smac proteins.

  10. Navy Mobility Fuels Forecasting System Phase 6 report: Impacts of a military disruption on Navy fuel availability and quality

    SciTech Connect

    Hadder, G.R.; Davis, R.M.

    1990-09-01

    The Refinery Yield Model of the Navy Mobility Fuels Forecasting System has been used to study the impacts of a severe military disruption on the production of Navy JP-5 jet fuel and F-76 marine diesel fuel in the year 1995. The global petroleum supply reduction due to the disruption was about 40 percent of the business-as-usual supply. Regional production cost increases for JP-5 were between $3 and $11 per gallon during the disruption. For F-76, the production cost increases were between $3 and $5 per gallon. The disruption caused substantial degradations for certain fuel quality properties of F-76 produced in the Pacific basin and in southern Europe. During both business-as-usual and disruption, the most prevalent Navy fuel quality problem was F-76 instability due to high levels of light cycle oils. 37 refs., 1 fig., 21 tabs.

  11. Acid-Sulfate-Weathering Activity in Shergottite Sites on Mars Recorded in Grim Glasses

    NASA Technical Reports Server (NTRS)

    Rao, M. N.; Nyquist, L. E.; Ross, K.; Sutton, S. R.; Schwandt, C. S.

    2011-01-01

    Based on mass spectrometric studies of sulfur species in Shergotty and EET79001, [1] and [2] showed that sulfates and sulfides occur in different proportions in shergottites. Sulfur speciation studies in gas-rich impact-melt (GRIM) glasses in EET79001 by the XANES method [3] showed that S K-XANES spectra in GRIM glasses from Lith A indicate that S is associated with Ca and Al presumably as sulfides/sulfates whereas the XANES spectra of amorphous sulfide globules in GRIM glasses from Lith B indicate that S is associated with Fe as FeS. In these amorphous iron sulfide globules, [4] found no Ni using FE-SEM and suggested that the globules resulting from immiscible sulfide melt may not be related to the igneous iron sulfides having approximately 1-3% Ni. Furthermore, in the amorphous iron sulfides from 507 GRIM glass, [5] determined delta(sup 34)S values ranging from +3.5%o to -3.1%o using Nano-SIMS. These values plot between the delta(sup 34)S value of +5.25%o determined in the sulfate fraction in Shergotty [6] at one extreme and the value of -1.7%o obtained for igneous sulfides in EET79001 and Shergotty [7] at the other. These results suggest that the amorphous Fe-S globules likely originated by shock reduction of secondary iron sulfate phases occurring in the regolith precursor materials during impact [7]. Sulfates in the regolith materials near the basaltic shergottite sites on Mars owe their origin to surficial acid-sulfate interactions. We examine the nature of these reactions by studying the composition of the end products in altered regolith materials. For the parent material composition, we use that of the host shergottite material in which the impact glasses are situated.

  12. Enhanced control of end-group composition in poly(3-hexylthiophene)s prepared by GRIM

    SciTech Connect

    Kochemba, William Michael; Kilbey, II, S Michael; Pickel, Deanna L

    2012-01-01

    The ability to prepare well-defined semiconducting polymers is essential for understanding the link between structure and function in organic photovoltaic devices. A general method for enhanced control of the degree of functionality of end-functionalized poly(3-hexylthiophene)s (P3HT) prepared by Grignard Metathesis (GRIM) polymerization has been developed. In the absence of additives, the degree of functionality of end-functional P3HTs prepared by quenching of the GRIM polymerization with a Grignard reagent is dependent on the Grignard reagent utilized. In this study, additives such as styrene and 1-pentene are shown to alter the end-group composition of tolyl-functionalized P3HTs as determined by MALDI-TOF MS. In particular, when quenching the GRIM polymerization with tolylmagnesium bromide a modest decrease in the difunctional product is observed, and the yield of the monofunctional product increases significantly. Temperature and lithium chloride (LiCl) addition also play impactful roles. Monofunctional P3HT is found to be the major product (65%) when the functionalization is done in the presence of LiCl and styrene at 0oC, whereas in the absence of additives the monofunctional product is present at only 20%.

  13. Business as Usual: An Assessment of Donald Rumsfeld’s Transformation Vision and Transformation’s Prospects for the Future

    DTIC Science & Technology

    2008-06-01

    Usual: An Assessment of Donald Rumsfeld’s Transformation Vision and Transformation’s Prospects for the Future No. 18 June 2008 ISSN 1863-6039...SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report (SAR) 18 . NUMBER OF PAGES...Prescribed by ANSI Std Z39- 18 The George C. Marshall European Center for Security Studies The George C. Marshall European Center for Security

  14. Becoming a Truly Helpful Teacher: Considerably More Challenging, and Potentially More Fun, than Merely Doing Business as Usual

    ERIC Educational Resources Information Center

    Jason, Hilliard

    2007-01-01

    Few medical faculty members are adequately prepared for their instructional responsibilities. Our educational traditions were established before we had research-based understandings of the teaching-learning process and before brain research began informing our understandings of how humans achieve lasting learning. Yet, there are several advantages…

  15. Earthwatch and the HSBC Climate Partnership: Taking Stock of Forest Carbon Worldwide While Changing Business As Usual

    NASA Astrophysics Data System (ADS)

    Borgatti, R.; Bebber, D. P.; Riutta, T.; Murthy, I.; Ren, H.; Parker, G.; Capretz, R.; Phillips, R.

    2011-12-01

    For the last 40 years, Earthwatch Institute has engaged people and communities in citizen science projects around the world, focusing on topics ranging from climate change in South American rainforests to wildlife conservation on the Mongolian Steppe. In collaboration with the financial institution HSBC and five research partners, Earthwatch has just completed a global, five-year (2007-2012) climate change research project in temperate and tropical forests representative of managed forests worldwide (www.earthwatch.org/hcp). This work was completed in part by more than 2200 HSBC staff members who worked side by side with scientists to collect forest data at five centers, one each in India, China, England, Brazil and the United States. This talk will present findings from this unprecedented climate change research program and highlight research findings specific to each of the countries. In addition to the results from the quantitative research collection, some of the key management outreach and business outcomes resulting from this research will be presented.

  16. NDI Acquisition. An Alternative to Business as Usual. Report of the DSMC 1991-1992 Military Research Fellows

    DTIC Science & Technology

    1992-10-01

    future to continued high standard, tem or component is delivered, and technological supremacy demonstrated by U.S. forces. The expanded use of markt ...suppliers. If price analysis out social policy. This is clearly the case alone cannot demonstrate price reason- in the area of developing women-owned...measures are successful, others are sure to fol- evitable as the federal government at- low. tempts to balance social and economic objectives

  17. Oxidation States of Grim Glasses in EET79001 Based on Vanadium Valence

    NASA Technical Reports Server (NTRS)

    Sutton, S. R.; Rao, M. N.; Nyquist, L. E.

    2010-01-01

    Gas-rich impact-melt (GRIM) glasses in SNC meteorites are very rich in Martian atmospheric noble gases and sulfur suggesting a possible occurrence of regolith-derived secondary mineral assemblages in these samples. Previously, we have studied two GRIM glasses, 506 and 507, from EET79001 Lith A and Lith B, respectively, for elemental abundances and spatial distribution of sulfur using EMPA (WDS) and FE-SEM (EDS) techniques and for sulfur-speciation using K-edge XANES techniques. These elemental and FE-SEM micro-graph data at several locations in the GRIM glasses from Shergotty (DBS), Zagami 994 and EET79001, Lith B showed that FeO and SO3 are positively correlated (SO3 represents a mixture of sulfide and sulfate). FE-SEM (EDS) study revealed that the sulfur-rich pockets in these glasses contain numerous micron-sized iron-sulfide (Fe-S) globules sequestered throughout the volume. However, in some areas (though less frequently), we detected significant Fe-S-O signals suggesting the occurrence of iron sulfate. These GRIM glasses were studied by K-edge microXANES techniques for sulfur speciation in association with iron in sulfur-rich areas. In both samples, we found the sulfur speciation dominated by sulfide with minor oxidized sulfur mixed in with various proportions. The abundance of oxidized sulfur was greater in 506 than in 507. Based on these results, we hypothesize that sulfur initially existed as sulfate in the glass precursor materials and, on shock-impact melting of the precursor materials producing these glasses, the oxidized sulfur was reduced to predominately sulfide. In order to further test this hypothesis, we have used microXANES to measure the valence states of vanadium in GRIM glasses from Lith A and Lith B to complement and compare with previous analogous measurements on Lith C (note: 506 and 507 contain the largest amounts of martian atmospheric gases but the gas-contents in Lith C measured by are unknown). Vanadium is ideal for addressing this re

  18. GRIM REAPER peptide binds to receptor kinase PRK5 to trigger cell death in Arabidopsis

    PubMed Central

    Wrzaczek, Michael; Vainonen, Julia P; Stael, Simon; Tsiatsiani, Liana; Help-Rinta-Rahko, Hanna; Gauthier, Adrien; Kaufholdt, David; Bollhöner, Benjamin; Lamminmäki, Airi; Staes, An; Gevaert, Kris; Tuominen, Hannele; Van Breusegem, Frank; Helariutta, Ykä; Kangasjärvi, Jaakko

    2015-01-01

    Recognition of extracellular peptides by plasma membrane-localized receptor proteins is commonly used in signal transduction. In plants, very little is known about how extracellular peptides are processed and activated in order to allow recognition by receptors. Here, we show that induction of cell death in planta by a secreted plant protein GRIM REAPER (GRI) is dependent on the activity of the type II metacaspase METACASPASE-9. GRI is cleaved by METACASPASE-9 in vitro resulting in the release of an 11 amino acid peptide. This peptide bound in vivo to the extracellular domain of the plasma membrane-localized, atypical leucine-rich repeat receptor-like kinase POLLEN-SPECIFIC RECEPTOR-LIKE KINASE 5 (PRK5) and was sufficient to induce oxidative stress/ROS-dependent cell death. This shows a signaling pathway in plants from processing and activation of an extracellular protein to recognition by its receptor. PMID:25398910

  19. GRIM REAPER peptide binds to receptor kinase PRK5 to trigger cell death in Arabidopsis.

    PubMed

    Wrzaczek, Michael; Vainonen, Julia P; Stael, Simon; Tsiatsiani, Liana; Help-Rinta-Rahko, Hanna; Gauthier, Adrien; Kaufholdt, David; Bollhöner, Benjamin; Lamminmäki, Airi; Staes, An; Gevaert, Kris; Tuominen, Hannele; Van Breusegem, Frank; Helariutta, Ykä; Kangasjärvi, Jaakko

    2015-01-02

    Recognition of extracellular peptides by plasma membrane-localized receptor proteins is commonly used in signal transduction. In plants, very little is known about how extracellular peptides are processed and activated in order to allow recognition by receptors. Here, we show that induction of cell death in planta by a secreted plant protein GRIM REAPER (GRI) is dependent on the activity of the type II metacaspase METACASPASE-9. GRI is cleaved by METACASPASE-9 in vitro resulting in the release of an 11 amino acid peptide. This peptide bound in vivo to the extracellular domain of the plasma membrane-localized, atypical leucine-rich repeat receptor-like kinase POLLEN-SPECIFIC RECEPTOR-LIKE KINASE 5 (PRK5) and was sufficient to induce oxidative stress/ROS-dependent cell death. This shows a signaling pathway in plants from processing and activation of an extracellular protein to recognition by its receptor.

  20. Forecasting forecast skill

    NASA Technical Reports Server (NTRS)

    Kalnay, Eugenia; Dalcher, Amnon

    1987-01-01

    It is shown that it is possible to predict the skill of numerical weather forecasts - a quantity which is variable from day to day and region to region. This has been accomplished using as predictor the dispersion (measured by the average correlation) between members of an ensemble of forecasts started from five different analyses. The analyses had been previously derived for satellite-data-impact studies and included, in the Northern Hemisphere, moderate perturbations associated with the use of different observing systems. When the Northern Hemisphere was used as a verification region, the prediction of skill was rather poor. This is due to the fact that such a large area usually contains regions with excellent forecasts as well as regions with poor forecasts, and does not allow for discrimination between them. However, when regional verifications were used, the ensemble forecast dispersion provided a very good prediction of the quality of the individual forecasts.

  1. Observation of sea-salt fraction in sub-100 nm diameter particles at Cape Grim

    NASA Astrophysics Data System (ADS)

    Cravigan, Luke T.; Ristovski, Zoran; Modini, Robin L.; Keywood, Melita D.; Gras, John L.

    2015-03-01

    Volatility-hygroscopicity tandem differential mobility analyzer measurements were used to infer the composition of sub-100 nm diameter Southern Ocean marine aerosols at Cape Grim in November and December 2007. This study focuses on a short-lived high sea spray aerosol (SSA) event on 7-8 December with two externally mixed modes in the Hygroscopic Growth Factor (HGF) distributions (90% relative humidity (RH)), one at HGF > 2 and another at HGF~1.5. The particles with HGF > 2 displayed a deliquescent transition at 73-75% RH and were nonvolatile up to 280°C, which identified them as SSA particles with a large inorganic sea-salt fraction. SSA HGFs were 3-13% below those for pure sea-salt particles, indicating an organic volume fraction (OVF) of up to 11-46%. Observed high inorganic fractions in sub-100 nm SSA is contrary to similar, earlier studies. HGFs increased with decreasing particle diameter over the range 16-97 nm, suggesting a decreased OVF, again contrary to earlier studies. SSA comprised up to 69% of the sub-100 nm particle number, corresponding to concentrations of 110-290 cm-3. Air mass back trajectories indicate that SSA particles were produced 1500 km, 20-40 h upwind of Cape Grim. Transmission electron microscopy (TEM) and X-ray spectrometry measurements of sub-100 nm aerosols collected from the same location, and at the same time, displayed a distinct lack of sea salt. Results herein highlight the potential for biases in TEM analysis of the chemical composition of marine aerosols.

  2. Navy Mobility Fuels Forecasting System report: Navy fuel production in the year 2000

    SciTech Connect

    Hadder, G.R.; Davis, R.M.

    1991-09-01

    The Refinery Yield Model of the Navy Mobility Fuels Forecasting System has been used to study the feasibility and quality of Navy JP-5 jet fuel and F-76 marine diesel fuel for two scenarios in the year 2000. Both scenarios account for environmental regulations for fuels produced in the US and assume that Eastern Europe, the USSR, and the People's Republic of China have free market economies. One scenario is based on business-as-usual market conditions for the year 2000. The second scenario is similar to first except that USSR crude oil production is 24 percent lower. During lower oil production in the USSR., there are no adverse effects on Navy fuel availability, but JP-5 is generally a poorer quality fuel relative to business-as-usual in the year 2000. In comparison with 1990, there are two potential problems areas for future Navy fuel quality. The first problem is increased aromaticity of domestically produced Navy fuels. Higher percentages of aromatics could have adverse effects on storage, handling, and combustion characteristics of both JP-5 and F-76. The second, and related, problem is that highly aromatic light cycle oils are blended into F-76 at percentages which promote fuel instability. It is recommended that the Navy continue to monitor the projected trend toward increased aromaticity in JP-5 and F-76 and high percentages of light cycle oils in F-76. These potential problems should be important considerations in research and development for future Navy engines.

  3. Navy Mobility Fuels Forecasting System report: Navy fuel production in the year 2000

    SciTech Connect

    Hadder, G.R.; Davis, R.M.

    1991-09-01

    The Refinery Yield Model of the Navy Mobility Fuels Forecasting System has been used to study the feasibility and quality of Navy JP-5 jet fuel and F-76 marine diesel fuel for two scenarios in the year 2000. Both scenarios account for environmental regulations for fuels produced in the US and assume that Eastern Europe, the USSR, and the People`s Republic of China have free market economies. One scenario is based on business-as-usual market conditions for the year 2000. The second scenario is similar to first except that USSR crude oil production is 24 percent lower. During lower oil production in the USSR., there are no adverse effects on Navy fuel availability, but JP-5 is generally a poorer quality fuel relative to business-as-usual in the year 2000. In comparison with 1990, there are two potential problems areas for future Navy fuel quality. The first problem is increased aromaticity of domestically produced Navy fuels. Higher percentages of aromatics could have adverse effects on storage, handling, and combustion characteristics of both JP-5 and F-76. The second, and related, problem is that highly aromatic light cycle oils are blended into F-76 at percentages which promote fuel instability. It is recommended that the Navy continue to monitor the projected trend toward increased aromaticity in JP-5 and F-76 and high percentages of light cycle oils in F-76. These potential problems should be important considerations in research and development for future Navy engines.

  4. Characterisation of J(O1D) at Cape Grim 2000-2005

    NASA Astrophysics Data System (ADS)

    Wilson, S. R.

    2015-07-01

    Estimates of the rate of production of excited oxygen atoms due to the photolysis of ozone (J(O1D)) have been derived from radiation measurements carried out at Cape Grim, Tasmania (40.6° S, 144.7° E). The individual measurements have a total uncertainty of 16 % (1σ). These estimates agree well with model estimates of clear-sky photolysis rates. Observations spanning 2000-2005 have been used to quantify the impact of season, clouds and ozone column amount. The annual cycle of J(O1D) has been investigated via monthly means. These means show an interannual variation (monthly standard deviation) of 9 %, but in midsummer and midwinter this reduces to 3-5 %. Variations in solar zenith angle and total column ozone explain 86 % of the observed variability in the measured photolysis rates. The impact of total column ozone, expressed as a radiation amplification factor (RAF), is found to be ~ 1.53, in agreement with model estimates. This ozone dependence explains 20 % of the variation observed at medium solar zenith angles (30-50°). The impact of clouds results in a median reduction of 30 % in J(O1D) for the same solar zenith angle range. Including estimates of cloudiness derived from long-wave radiation measurements resulted in a statistically significant fit to observations, but the quality of the fit did not increase significantly as measured by the adjusted R2.

  5. Aerosol Optical Depth at Cape Grim 1986 - 2014: What does it tell us?

    NASA Astrophysics Data System (ADS)

    Wilson, Stephen

    2015-04-01

    The Cape Grim Baseline Air Pollution Station is located near the northwest tip of Tasmania (Australia), a site chosen to permit measurement of the atmospheric environment over the southern oceans. Atmospheric measurements began in the late 1970s, and observations of Aerosol Optical Depth (AOD) using automated sunphotometers began in 1986. Since then, measurements have continued with a range of different instruments operating at a varying number of wavelengths. The site is challenging for these measurements as it is exposed to a sea-salt laden atmosphere, which presents both instrumental issues (corrosion) and measurement complications (salt fouling of the windows) in addition to the high frequency of cloud. The dataset has been processed to produce a record of half-hourly AOD for the period 1986 - 2014 and investigated for internal consistency. In general the AOD is small (around 0.05 at 500nm). The impact of the Mount Pinatubo eruption in 1991 can be clearly observed, along with a persistent annual cycle. This has been further analyzed fitting to all wavelengths measured to derive an averaged optical depth (at 500 nm) and some preliminary aerosol size distribution information.

  6. All-polymer photovoltaic devices of poly(3-(4-n-octyl)-phenylthiophene) from Grignard Metathesis (GRIM) polymerization.

    PubMed

    Holcombe, Thomas W; Woo, Claire H; Kavulak, David F J; Thompson, Barry C; Fréchet, Jean M J

    2009-10-14

    The synthesis of poly[3-(4-n-octyl)-phenylthiophene] (POPT) from Grignard Metathesis (GRIM) is reported. GRIM POPT is found to have favorable electronic, optical, and processing properties for organic photovoltaics (OPVs). Space-charge limited current and field effect transistor measurements for POPT yielded hole mobilities of 1 x 10(-4) cm(2)/(V s) and 0.05 cm(2)/(V s), respectively. Spincasting GRIM POPT from chlorobenzene yields a thin film with a 1.8 eV band gap, and PC(61)BM:POPT bulk heterojection devices provide a peak performance of 3.1%. Additionally, an efficiency of 2.0% is achieved in an all-polymer, bilayer OPV using poly[2-methoxy-5-(2'-ethylhexyloxy)-1,4-(1-cyanovinylene)phenylene] (CNPPV) as an acceptor. This state-of-the-art all-polymer device is analyzed in comparison to the analogous poly(3-hexylthiophene) (P3HT)/CNPPV device. Counter to expectations based on more favorable energy level alignment, greater active layer light absorption, and similar hole mobility, P3HT/CNPPV devices perform less well than POPT/CNPPV devices with a peak efficiency of 0.93%.

  7. The Australian Air Quality Forecasting System: the use of green scenarios of motor vehicle usage as an educational tool.

    PubMed

    Cope, Martin; Hess, Dale; Lee, Sunhee; Tory, Kevin; Burgers, Manuela; Lilley, Bill

    2008-07-01

    The Australian Air Quality Forecasting System (AAQFS) is one of several newly emerging, high-resolution, numerical air quality forecasting systems. The system is briefly described. A public education application of the air quality impact of motor vehicle usage is explored by computing the concentration and dosage of particulate matter less than 10 microm in aerodynamic diameter (PM10) for a commuter traveling to work between Geelong and Melbourne, Victoria, Australia, under "business-as-usual" and "green" scenarios. This application could be routinely incorporated into systems like AAQFS. Two methodologies for calculating the dosage are described: one for operational use and one for more detailed applications. The Clean Air Research Programme-Personal Exposure Study in Melbourne provides support for this operational methodology. The more detailed methodology is illustrated using a system for predicting concentrations due to near-road emissions of PM10 and applied in Sydney.

  8. Navy mobility fuels forecasting system report: World petroleum trade forecasts for the year 2000

    SciTech Connect

    Das, S.

    1991-12-01

    The Middle East will continue to play the dominant role of a petroleum supplier in the world oil market in the year 2000, according to business-as-usual forecasts published by the US Department of Energy. However, interesting trade patterns will emerge as a result of the democratization in the Soviet Union and Eastern Europe. US petroleum imports will increase from 46% in 1989 to 49% in 2000. A significantly higher level of US petroleum imports (principally products) will be coming from Japan, the Soviet Union, and Eastern Europe. Several regions, the Far East, Japan, Latin American, and Africa will import more petroleum. Much uncertainty remains about of the level future Soviet crude oil production. USSR net petroleum exports will decrease; however, the United States and Canada will receive some of their imports from the Soviet Union due to changes in the world trade patterns. The Soviet Union can avoid becoming a net petroleum importer as long as it (1) maintains enough crude oil production to meet its own consumption and (2) maintains its existing refining capacities. Eastern Europe will import approximately 50% of its crude oil from the Middle East.

  9. Biomass burning emissions of trace gases and particles in marine air at Cape Grim, Tasmania

    NASA Astrophysics Data System (ADS)

    Lawson, S. J.; Keywood, M. D.; Galbally, I. E.; Gras, J. L.; Cainey, J. M.; Cope, M. E.; Krummel, P. B.; Fraser, P. J.; Steele, L. P.; Bentley, S. T.; Meyer, C. P.; Ristovski, Z.; Goldstein, A. H.

    2015-12-01

    Biomass burning (BB) plumes were measured at the Cape Grim Baseline Air Pollution Station during the 2006 Precursors to Particles campaign, when emissions from a fire on nearby Robbins Island impacted the station. Measurements made included non-methane organic compounds (NMOCs) (PTR-MS), particle number size distribution, condensation nuclei (CN) > 3 nm, black carbon (BC) concentration, cloud condensation nuclei (CCN) number, ozone (O3), methane (CH4), carbon monoxide (CO), hydrogen (H2), carbon dioxide (CO2), nitrous oxide (N2O), halocarbons and meteorology. During the first plume strike event (BB1), a 4 h enhancement of CO (max ~ 2100 ppb), BC (~ 1400 ng m-3) and particles > 3 nm (~ 13 000 cm-3) with dominant particle mode of 120 nm were observed overnight. A wind direction change lead to a dramatic reduction in BB tracers and a drop in the dominant particle mode to 50 nm. The dominant mode increased in size to 80 nm over 5 h in calm sunny conditions, accompanied by an increase in ozone. Due to an enhancement in BC but not CO during particle growth, the presence of BB emissions during this period could not be confirmed. The ability of particles > 80 nm (CN80) to act as CCN at 0.5 % supersaturation was investigated. The ΔCCN / ΔCN80 ratio was lowest during the fresh BB plume (56 ± 8 %), higher during the particle growth period (77 ± 4 %) and higher still (104 ± 3 %) in background marine air. Particle size distributions indicate that changes to particle chemical composition, rather than particle size, are driving these changes. Hourly average CCN during both BB events were between 2000 and 5000 CCN cm-3, which were enhanced above typical background levels by a factor of 6-34, highlighting the dramatic impact BB plumes can have on CCN number in clean marine regions. During the 29 h of the second plume strike event (BB2) CO, BC and a range of NMOCs including acetonitrile and hydrogen cyanide (HCN) were clearly enhanced and some enhancements in O3 were observed

  10. Shaking things up or business as usual? The influence of female corporate executives and board of directors on women's managerial representation.

    PubMed

    Skaggs, Sheryl; Stainback, Kevin; Duncan, Phyllis

    2012-07-01

    Previous theory and research suggests that workplace gender composition at the highest organizational levels should play a crucial role in reducing gender linked inequalities in the workplace. In this article, we examine how the presence of women in top corporate positions influences female managerial representation at the establishment-level. Using a unique multi-level dataset of 5679 establishments nested within 81 Fortune 1000 corporations, we find that having more women on corporate boards, but not in executive positions, at the firm-level is associated with greater female managerial representation at the establishment-level. The results also show that women are more likely to be in management positions when employed in young, large, and managerially intensive workplaces, as well as those with a larger percentage of female non-managers. Implications for future research and policy implementation are discussed.

  11. Social change or business as usual at city hall? Examining an urban municipal government's response to neighbourhood-level health inequities.

    PubMed

    Cahuas, Madelaine C; Wakefield, Sarah; Peng, Yun

    2015-05-01

    There is a renewed interest in the potential of municipal governments working collaboratively with local communities to address health inequities. A growing body of literature has also highlighted the benefits and limitations of participatory approaches in neighbourhood interventions initiated by municipal governments. However, few studies have investigated how neighbourhood interventions tackling health inequities work in real-time and in context, from the perspectives of Community Developers (CDs) who promote community participation. This study uses a process evaluation approach and semi-structured interviews with CDs to explore the challenges they face in implementing a community development, participatory process in the City of Hamilton's strategy to reduce health inequities - Neighbourhood Action. Findings demonstrate that municipal government can facilitate and suppress community participation in complex ways. CDs serve as significant but conflicted intermediaries as they negotiate and navigate power differentials between city and community actors, while also facing structural challenges. We conclude that community participation is important to bottom-up, resident-led social change, and that CDs are central to this work.

  12. Customer Choice or Business as Usual?: Promoting Innovation in the Design of WIA Training Programs Through the Individual Training Account Experiment.

    ERIC Educational Resources Information Center

    Perez-Johnson, Irma; Decker, Paul

    The Workforce Investment Act (WIA) of 1998 requires that workforce investment areas establish individual training accounts (ITAs) that provide vouchers customers can use to pay for training. The United States Department of Labor is supporting the ITA experiment, during which new customers determined to be eligible for training will be randomly…

  13. The Role of Chapter Meetings: Business as Usual or a Course in Leadership Development? and Why FBLA-PBL? The Importance of Student Organizations.

    ERIC Educational Resources Information Center

    Fracaroli, Mary Lynn; Fitzhugh-Pemberton, Gladys

    1996-01-01

    Fracaroli describes ways advisors can use vocational student organizations as leadership laboratories. Fitzhugh-Pemberton explains the value to students of joining Future Business Leaders of America-Phi Beta Lambda. (SK)

  14. Claude Bernard Distinguished Lecture. Becoming a truly helpful teacher: considerably more challenging, and potentially more fun, than merely doing business as usual.

    PubMed

    Jason, Hilliard

    2007-12-01

    Few medical faculty members are adequately prepared for their instructional responsibilities. Our educational traditions were established before we had research-based understandings of the teaching-learning process and before brain research began informing our understandings of how humans achieve lasting learning. Yet, there are several advantages you may have. If your expertise is at one of the frontiers of human biology, your teaching can be inherently fascinating to aspiring health professionals. If your work has implications for human health, you have another potential basis for engaging future clinicians. And, thanks to Claude Bernard's influence, you likely are "process oriented," a necessary mindset for being an effective teacher. There are also challenges you may face. Your medical students will mostly become clinicians. Unless you can help them see connections between your offerings and their future work, you may not capture and sustain their interest. To be effective, teachers, like clinicians, need to be interactive, make on-the-spot decisions, and be "emotional literate." If you aren't comfortable with these demands, you may have work to do toward becoming a truly helpful teacher. Program changes may be needed. Might your program need to change 1) from being adversarial and controlling to being supportive and trust based or 2) from mainly dispensing information to mainly asking and inviting questions? In conclusion, making changes toward becoming a truly helpful teacher can bring benefits to your students while increasing your sense of satisfaction and fulfillment as a teacher. If you choose to change, be gentle with yourself, as you should be when expecting your students to make important changes.

  15. Forecasting Skill

    DTIC Science & Technology

    1981-01-01

    and in synoptic meteorology, many feel the improvements in forecasting the weather (clouds, winds , precipitation, and obstructions to vision) have...and maximum temperature) are each awarded marks 2, 1, or 0 according to whether the forecast is correct, 8 - *- -**■*- ———"—- - -■ t0m 1 MM—IB I...rate of improve- ment of 10% as roughly comparable to the improvement rate obtained by the numerical models. The following types of forecasts seem to

  16. 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.

  17. Forecasting Earthquakes

    NASA Technical Reports Server (NTRS)

    1994-01-01

    In this video there are scenes of damage from the Northridge Earthquake and interviews with Dr. Andrea Donnelan, Geophysics at JPL, and Dr. Jim Dolan, earthquake geologist from Cal. Tech. The interviews discuss earthquake forecasting by tracking changes in the earth's crust using antenna receiving signals from a series of satellites called the Global Positioning System (GPS).

  18. Reasonable Forecasts

    ERIC Educational Resources Information Center

    Taylor, Kelley R.

    2010-01-01

    This article presents a sample legal battle that illustrates school officials' "reasonable forecasts" of substantial disruption in the school environment. In 2006, two students from a Texas high school came to school carrying purses decorated with images of the Confederate flag. The school district has a zero-tolerance policy for…

  19. Turbulence forecasting

    NASA Technical Reports Server (NTRS)

    Chandler, C. L.

    1987-01-01

    In order to forecast turbulence, one needs to have an understanding of the cause of turbulence. Therefore, an attempt is made to show the atmospheric structure that often results when aircraft encounter moderate or greater turbulence. The analysis is based on thousands of hours of observations of flights over the past 39 years of aviation meteorology.

  20. TRAVEL FORECASTER

    NASA Technical Reports Server (NTRS)

    Mauldin, L. E.

    1994-01-01

    Business travel planning within an organization is often a time-consuming task. Travel Forecaster is a menu-driven, easy-to-use program which plans, forecasts cost, and tracks actual vs. planned cost for business-related travel of a division or branch of an organization and compiles this information into a database to aid the travel planner. The program's ability to handle multiple trip entries makes it a valuable time-saving device. Travel Forecaster takes full advantage of relational data base properties so that information that remains constant, such as per diem rates and airline fares (which are unique for each city), needs entering only once. A typical entry would include selection with the mouse of the traveler's name and destination city from pop-up lists, and typed entries for number of travel days and purpose of the trip. Multiple persons can be selected from the pop-up lists and multiple trips are accommodated by entering the number of days by each appropriate month on the entry form. An estimated travel cost is not required of the user as it is calculated by a Fourth Dimension formula. With this information, the program can produce output of trips by month with subtotal and total cost for either organization or sub-entity of an organization; or produce outputs of trips by month with subtotal and total cost for international-only travel. It will also provide monthly and cumulative formats of planned vs. actual outputs in data or graph form. Travel Forecaster users can do custom queries to search and sort information in the database, and it can create custom reports with the user-friendly report generator. Travel Forecaster 1.1 is a database program for use with Fourth Dimension Runtime 2.1.1. It requires a Macintosh Plus running System 6.0.3 or later, 2Mb of RAM and a hard disk. The standard distribution medium for this package is one 3.5 inch 800K Macintosh format diskette. Travel Forecaster was developed in 1991. Macintosh is a registered trademark of

  1. Forecaster's dilemma: Extreme events and forecast evaluation

    NASA Astrophysics Data System (ADS)

    Lerch, Sebastian; Thorarinsdottir, Thordis; Ravazzolo, Francesco; Gneiting, Tilmann

    2015-04-01

    In discussions of the quality of forecasts in the media and public, attention often focuses on the predictive performance in the case of extreme events. Intuitively, accurate predictions on the subset of extreme events seem to suggest better predictive ability. However, it can be demonstrated that restricting conventional forecast verification methods to subsets of observations might have unexpected and undesired effects and may discredit even the most skillful forecasters. Hand-picking extreme events is incompatible with the theoretical assumptions of established forecast verification methods, thus confronting forecasters with what we refer to as the forecaster's dilemma. For probabilistic forecasts, weighted proper scoring rules provide suitable alternatives for forecast evaluation with an emphasis on extreme events. Using theoretical arguments, simulation experiments and a case study on probabilistic forecasts of wind speed over Germany, we illustrate the forecaster's dilemma and the use of weighted proper scoring rules.

  2. GhMCS1, the Cotton Orthologue of Human GRIM-19, Is a Subunit of Mitochondrial Complex I and Associated with Cotton Fibre Growth

    PubMed Central

    Dong, Chun-Juan; Wu, Ai-Min; Du, Shao-Jun; Tang, Kai; Wang, Yun; Liu, Jin-Yuan

    2016-01-01

    GRIM-19 (Gene associated with Retinoid-Interferon-induced Mortality 19) is a subunit of mitochondrial respiratory complex I in mammalian systems, and it has been demonstrated to be a multifunctional protein involved in the cell cycle, cell motility and innate immunity. However, little is known about the molecular functions of its homologues in plants. Here, we characterised GhMCS1, an orthologue of human GRIM-19 from cotton (Gossypium hirsutum L.), and found that it was essential for maintaining complex integrity and mitochondrial function in cotton. GhMCS1 was detected in various cotton tissues, with high levels expressed in developing fibres and flowers and lower levels in leaves, roots and ovules. In fibres at different developmental stages, GhMCS1 expression peaked at 5–15 days post anthesis (dpa) and then decreased at 20 dpa and diminished at 25 dpa. By Western blot analysis, GhMCS1 was observed to be localised to the mitochondria of cotton leaves and to colocalise with complex I. In Arabidopsis, GhMCS1 overexpression enhanced the assembly of complex I and thus respiratory activity, whereas the GhMCS1 homologue (At1g04630) knockdown mutants showed significantly decreased respiratory activities. Furthermore, the mutants presented with some phenotypic changes, such as smaller whole-plant architecture, poorly developed seeds and fewer trichomes. More importantly, in the cotton fibres, both the GhMCS1 transcript and protein levels were correlated with respiratory activity and fibre developmental phase. Our results suggest that GhMCS1, a functional ortholog of the human GRIM-19, is an essential subunit of mitochondrial complex I and is involved in cotton fibre development. The present data may deepen our knowledge on the potential roles of mitochondria in fibre morphogenesis. PMID:27632161

  3. Today's Grim Jobs Report

    ERIC Educational Resources Information Center

    Fogg, Neeta P.; Harrington, Paul E.

    2010-01-01

    June 2009 is seen by many as the end of the Great Recession. Strong growth in GDP following massive monetary and fiscal responses to the collapse in housing and financial markets meant that the economy was on the mend. Yet a year later, 1.1 million "fewer" people are working, and the unemployment rate is stuck at 9.5%. Worse still, more than one…

  4. Biomass burning emissions of trace gases and particles in marine air at Cape Grim, Tasmania, 41° S

    NASA Astrophysics Data System (ADS)

    Lawson, S. J.; Keywood, M. D.; Galbally, I. E.; Gras, J. L.; Cainey, J. M.; Cope, M. E.; Krummel, P. B.; Fraser, P. J.; Steele, L. P.; Bentley, S. T.; Meyer, C. P.; Ristovski, Z.; Goldstein, A. H.

    2015-07-01

    Biomass burning (BB) plumes were measured at the Cape Grim Baseline Air Pollution Station during the 2006 Precursors to Particles campaign, when emissions from a fire on nearby Robbins Island impacted the station. Measurements made included non methane organic compounds (NMOCs) (PTR-MS), particle number size distribution, condensation nuclei (CN) > 3 nm, black carbon (BC) concentration, cloud condensation nuclei (CCN) number, ozone (O3), methane (CH4), carbon monixide (CO), hydrogen (H2), carbon dioxide (CO2), nitrous oxide (N2O), halocarbons and meteorology. During the first plume strike event (BB1), a four hour enhancement of CO (max ~ 2100 ppb), BC (~ 1400 ng m-3) and particles > 3 nm (~ 13 000 cm-3) with dominant particle mode of 120 nm were observed overnight. Dilution of the plume resulted in a drop in the dominant particle mode to 50 nm, and then growth to 80 nm over 5 h. This was accompanied by an increase in O3, suggesting that photochemical processing of air and condensation of low volatility oxidation products may be driving particle growth. The ability of particles > 80 nm (CN80) to act as CCN at 0.5 % supersaturation was investigated. The ΔCCN / ΔCN80 ratio was lowest during the fresh BB plume (56 %), higher during the particle growth event (77 %) and higher still (104 %) in background marine air. Particle size distributions indicate that changes to particle chemical composition, rather than particle size, are driving these changes. Hourly average CCN during both BB events were between 2000-5000 CCN cm-3, which were enhanced above typical background levels by a factor of 6-34, highlighting the dramatic impact BB plumes can have on CCN number in clean marine regions. During the 29 h of the second plume strike event (BB2) CO, BC and a range of NMOCs including acetonitrile and hydrogen cyanide (HCN) were clearly enhanced and some enhancements in O3 were observed (ΔO3 / ΔCO 0.001-0.074). A shortlived increase in NMOCs by a factor of 10 corresponded

  5. Forecast Mekong

    USGS Publications Warehouse

    Turnipseed, D. Phil

    2011-01-01

    Forecast Mekong is part of the U.S. Department of State's Lower Mekong Initiative, which was launched in 2009 by Secretary Hillary Clinton and the Foreign Ministers of Cambodia, Laos, Thailand, and Vietnam to enhance partnerships between the U.S. and the Lower Mekong River countries in the areas of environment, health, education, and infrastructure. The U.S. Geological Survey (USGS) is working in close cooperation with the U.S. Department of State to use research and data from the Lower Mekong Basin to provide hands-on results that will help decision makers in Lower Mekong River countries in the planning and design for restoration, conservation, and management efforts in the basin.

  6. Improved Anvil Forecasting

    NASA Technical Reports Server (NTRS)

    Lambert, Winifred C.

    2000-01-01

    This report describes the outcome of Phase 1 of the AMU's Improved Anvil Forecasting task. Forecasters in the 45th Weather Squadron and the Spaceflight Meteorology Group have found that anvil forecasting is a difficult task when predicting LCC and FR violations. The purpose of this task is to determine the technical feasibility of creating an anvil-forecasting tool. Work on this study was separated into three steps: literature search, forecaster discussions, and determination of technical feasibility. The literature search revealed no existing anvil-forecasting techniques. However, there appears to be growing interest in anvils in recent years. If this interest continues to grow, more information will be available to aid in developing a reliable anvil-forecasting tool. The forecaster discussion step revealed an array of methods on how better forecasting techniques could be developed. The forecasters have ideas based on sound meteorological principles and personal experience in forecasting and analyzing anvils. Based on the information gathered in the discussions with the forecasters, the conclusion of this report is that it is technically feasible at this time to develop an anvil forecasting technique that will significantly contribute to the confidence in anvil forecasts.

  7. Verifications of the medium-range forecasts of KIAPS integrated model

    NASA Astrophysics Data System (ADS)

    Lee, Eun-Hee; Lee, Juwon; Choi, In-Jin

    2016-04-01

    The Korea Institute of Atmospheric Prediction System, KIAPS, was established to carry out a national project in developing a new global forecast system from 2011 to 2019. The initial version of KIAPS Integrated Model, KIM, consisted of a spectral element dynamical core on a cubed sphere and a standard physics package from existing models such as the GRIMs, WRF, and GFS. Then KIM2.0 was released with the advanced or newly developed physics, dynamics, and data assimilation. Last July, its semi-real time forecast for 5 days has been operated every 00 and 12 UTC with the fully coupled 3D Var data assimilation system. Performance of KIM forecasts is evaluated both for the period of the selected testbed cases and for the semi-real time operational period, to examine the model improvement along with the upgrade and to figure out the model bias. Standardized statistical verification is also conducted including verification against analyses and observations (e.g., sonde and precipitation data). These will be summarized in this presentation. Additionally, surface verification using SYNOP observations and spatial verification for precipitation applied to meet the need for more informative forecast evaluations will be discussed.

  8. Stochastic demographic forecasting.

    PubMed

    Lee, R D

    1992-11-01

    "This paper describes a particular approach to stochastic population forecasting, which is implemented for the U.S.A. through 2065. Statistical time series methods are combined with demographic models to produce plausible long run forecasts of vital rates, with probability distributions. The resulting mortality forecasts imply gains in future life expectancy that are roughly twice as large as those forecast by the Office of the Social Security Actuary.... Resulting stochastic forecasts of the elderly population, elderly dependency ratios, and payroll tax rates for health, education and pensions are presented."

  9. Forecast-skill-based simulation of streamflow forecasts

    NASA Astrophysics Data System (ADS)

    Zhao, Tongtiegang; Zhao, Jianshi

    2014-09-01

    Streamflow forecasts are updated periodically in real time, thereby facilitating forecast evolution. This study proposes a forecast-skill-based model of forecast evolution that is able to simulate dynamically updated streamflow forecasts. The proposed model applies stochastic models that deal with streamflow variability to generate streamflow scenarios, which represent cases without forecast skill of future streamflow. The model then employs a coefficient of prediction to determine forecast skill and to quantify the streamflow variability ratio explained by the forecast. By updating the coefficients of prediction periodically, the model efficiently captures the evolution of streamflow forecast. Simulated forecast uncertainty increases with increasing lead time; and simulated uncertainty during a specific future period decreases over time. We combine the statistical model with an optimization model and design a hypothetical case study of reservoir operation. The results indicate the significance of forecast skill in forecast-based reservoir operation. Shortage index reduces as forecast skill increases and ensemble forecast outperforms deterministic forecast at a similar forecast skill level. Moreover, an effective forecast horizon exists beyond which more forecast information does not contribute to reservoir operation and higher forecast skill results in longer effective forecast horizon. The results illustrate that the statistical model is efficient in simulating forecast evolution and facilitates analysis of forecast-based decision making.

  10. Targeted observations to improve tropical cyclone track forecasts in the Atlantic and eastern Pacific basins

    NASA Astrophysics Data System (ADS)

    Aberson, Sim David

    third limit, though the results are inconclusive. Due to limited aircraft resources, optimal observing strategies for these missions must be developed. Since observations in areas of decaying error modes are unlikely to have large impact on subsequent forecasts, such strategies should be based on taking observations in those geographic locations corresponding to the most rapidly growing error modes in the numerical models and on known deficiencies in current data assimilation systems. Here, the most rapidly growing modes are represented by areas of large forecast spread in the NCEP bred-mode global ensemble forecasting system. The sampling strategy requires sampling the entire target region at approximately the same resolution as the North American rawinsonde network to limit the possibly spurious spread of information from dropwindsonde observations into data-sparse regions where errors are likely to grow. When only the subset of data in these fully-sampled target regions is assimilated into the numerical models, statistically significant reduction of the track forecast errors of up to 25% within the critical first two days of the forecast are seen. These model improvements are comparable with the cumulative business-as-usual track forecast model improvements expected over eighteen years.

  11. No evidence for change of the atmospheric helium isotope composition since 1978 from re-analysis of the Cape Grim Air Archive

    NASA Astrophysics Data System (ADS)

    Mabry, Jennifer C.; Lan, Tefang; Boucher, Christine; Burnard, Peter G.; Brennwald, Matthias S.; Langenfelds, Ray; Marty, Bernard

    2015-10-01

    The helium isotope composition of air might have changed since the industrial revolution due to the release of 4He-rich crustal helium during exploitation of fossil fuels. Thereby, variation of the atmospheric helium isotope ratio (3He/4He) has been proposed as a possible new atmospheric tracer of industrial activity. However, the magnitude of such change is debated, with possible values ranging from 0 to about 2 ‰ /yr (Sano et al., 1989; Hoffman and Nier, 1993; Pierson-Wickmann et al., 2001; Brennwald et al., 2013; Lupton and Evans, 2013). A new analytical facility for high precision (2‰, 2σ) analysis of the 3He/4He ratio of air has been developed at CRPG Nancy (France) capable of investigating permil level variations. Previously, Brennwald et al. (2013) analyzed a selection of air samples archived since 1978 at Cape Grim, Tasmania, by the Commonwealth Scientific and Industrial Research Organisation (CSIRO). They reported a mean temporal decrease of the 3He/4He ratio of 0.23-0.30‰/yr. Re-analysis of aliquots of the same samples using the new high-precision instrument showed no significant temporal decrease of the 3He/4He ratio (0.0095 ± 0.033‰ /yr, 2σ) in the time interval 1978-2011. These new data constrain the mean He content of globally produced natural gas to about 0.034% or less, which is about 3× lower than commonly quoted.

  12. Weather forecasting expert system study

    NASA Technical Reports Server (NTRS)

    1985-01-01

    Weather forecasting is critical to both the Space Transportation System (STS) ground operations and the launch/landing activities at NASA Kennedy Space Center (KSC). The current launch frequency places significant demands on the USAF weather forecasters at the Cape Canaveral Forecasting Facility (CCFF), who currently provide the weather forecasting for all STS operations. As launch frequency increases, KSC's weather forecasting problems will be great magnified. The single most important problem is the shortage of highly skilled forecasting personnel. The development of forecasting expertise is difficult and requires several years of experience. Frequent personnel changes within the forecasting staff jeopardize the accumulation and retention of experience-based weather forecasting expertise. The primary purpose of this project was to assess the feasibility of using Artificial Intelligence (AI) techniques to ameliorate this shortage of experts by capturing aria incorporating the forecasting knowledge of current expert forecasters into a Weather Forecasting Expert System (WFES) which would then be made available to less experienced duty forecasters.

  13. Future freeze forecasting

    NASA Technical Reports Server (NTRS)

    Bartholic, J. F.; Sutherland, R. A.

    1979-01-01

    Real time GOES thermal data acquisition, an energy balance minimum temperature prediction model and a statistical model are incorporated into a minicomputer system. These components make up the operational "Satellite Freeze Forecast System" being used to aid NOAA, NWS forecasters in developing their freeze forecasts. The general concept of the system is presented in this paper. Specific detailed aspects of the system can be found in the reference cited.

  14. Forecaster priorities for improving probabilistic flood forecasts

    NASA Astrophysics Data System (ADS)

    Wetterhall, Fredrik; Pappenberger, Florian; Alfieri, Lorenzo; Cloke, Hannah; Thielen, Jutta

    2014-05-01

    Hydrological ensemble prediction systems (HEPS) have in recent years been increasingly used for the operational forecasting of floods by European hydrometeorological agencies. The most obvious advantage of HEPS is that more of the uncertainty in the modelling system can be assessed. In addition, ensemble prediction systems generally have better skill than deterministic systems both in the terms of the mean forecast performance and the potential forecasting of extreme events. Research efforts have so far mostly been devoted to the improvement of the physical and technical aspects of the model systems, such as increased resolution in time and space and better description of physical processes. Developments like these are certainly needed; however, in this paper we argue that there are other areas of HEPS that need urgent attention. This was also the result from a group exercise and a survey conducted to operational forecasters within the European Flood Awareness System (EFAS) to identify the top priorities of improvement regarding their own system. They turned out to span a range of areas, the most popular being to include verification of an assessment of past forecast performance, a multi-model approach for hydrological modelling, to increase the forecast skill on the medium range (>3 days) and more focus on education and training on the interpretation of forecasts. In light of limited resources, we suggest a simple model to classify the identified priorities in terms of their cost and complexity to decide in which order to tackle them. This model is then used to create an action plan of short-, medium- and long-term research priorities with the ultimate goal of an optimal improvement of EFAS in particular and to spur the development of operational HEPS in general.

  15. Weather assessment and forecasting

    NASA Technical Reports Server (NTRS)

    1977-01-01

    Data management program activities centered around the analyses of selected far-term Office of Applications (OA) objectives, with the intent of determining if significant data-related problems would be encountered and if so what alternative solutions would be possible. Three far-term (1985 and beyond) OA objectives selected for analyses as having potential significant data problems were large-scale weather forecasting, local weather and severe storms forecasting, and global marine weather forecasting. An overview of general weather forecasting activities and their implications upon the ground based data system is provided. Selected topics were specifically oriented to the use of satellites.

  16. Forecasting Future Trends in Education

    ERIC Educational Resources Information Center

    Collazo, Andres; And Others

    1977-01-01

    Describes a forecasting model sensitive to the major factors influencing educational outcomes, presents several forecasts based on alternative sets of assumptions, and discusses the implications of these forecasts, including ways to subvert them. (Author/JG)

  17. Aviation Forecasting in ICAO

    NASA Technical Reports Server (NTRS)

    Mcmahon, J.

    1972-01-01

    Opinions or plans of qualified experts in the field are used for forecasting future requirements for air navigational facilities and services of international civil aviation. ICAO periodically collects information from Stators and operates on anticipated future operations, consolidates this information, and forecasts the future level of activity at different airports.

  18. A global non-hydrostatic weather forecast model in KIAPS using the spectral element on a cubed sphere

    NASA Astrophysics Data System (ADS)

    Choi, Suk-Jin; Lee, Eun-Hee; Hong, Song-You

    2016-04-01

    This presentation covers an introduction to the current state of a non-hydrostatic global atmospheric model to be named the KIAPS integrated model (KIM). Efforts to resolve an excessive dissipation in small scales in KIM will be discussed. Also, simulated results for several idealized benchmark tests and full-physics forecasts will be shown. The dynamical core of the model is using the Euler equation set in a flux form based on the terrain following mass-based vertical coordinate, which is discretized by horizontal spectral element method (SEM) and the vertical finite difference method (FDM) for the spatial discretization and a time-split third-order Runge-Kutta (RK3) for the time discretization. Owing to the virtue of SEM and the explicit time integrator, KIM can achieve easily a high level of scalability. The physics package coupled with the dynamical core is a standard physics package from existing models such as the GRIMs, WRF, and GFS.

  19. AIDS. Grim news for Asia.

    PubMed

    1992-12-04

    While Asia was the last region to be exposed to the global spread of HIV and AIDS, the incidence of HIV infection there is increasing fastest. The Asian Development Bank predicts mortality from AIDS will cause some town and village populations to begin declining by the year 2000. With an estimated 1 million people infected in India, and 400,000 in Thailand, these 2 countries are particularly exposed to the risk of epidemic HIV spread. In 5 years, more people may be affected by AIDS in India than anywhere else in the world. Concern over a growing presence of HIV is also merited for the Philippines, Indonesia, China, and the drug trade's Golden Triangle. The Second International Conference on AIDS in Asia and the Pacific in November 1992 stressed that AIDS no longer affects only homosexual and IV drug using populations. 50% of new infections worldwide in the first half of 1992 were among women, 65% of Thailand's AIDS cases are among heterosexuals, and 3-5% of Thailand's long-haul truck drivers have tested positive for HIV infection. HIV and AIDS robs economies and societies of their best workers. The immediate costs of caring for AIDS patients will pale next to the far greater losses to be realized in private sector economic productivity. Asia's more developed economies will probably be able to survive the epidemic, but small, poor countries like Laos will wilt. Prompt action must be taken to overcome public and religious ignorance and objections to promoting and using condoms throughout the region. For the first time, Beijing has organized an AIDS awareness conference for male homosexuals. Further, Singapore has implemented compulsory testing for lower-income foreign workers. Pakistan has even solicited educational assistance and support from Islamic religious leaders; similar action is being considered in Bangladesh.

  20. How grim is hepatocellular carcinoma?

    PubMed Central

    Weledji, Elroy P.; Enow Orock, George; Ngowe, Marcelin N.; Nsagha, Dickson Shey

    2014-01-01

    Hepatocellular carcinoma (HCC) is a complex disease and a major cause of death in high endemic areas of hepatitis B virus (HBV) or hepatitis C virus (HCV) infection. HCC has gone from being a universal death sentence to a cancer that can be prevented, detected at an early stage and effectively treated. Liver resection or tumour ablation techniques may be effective bridge to liver transplantation if they fulfill the Milan criteria. The areas of progress in HCC are in the control of HBV or HCV and the development of adjuvant or neoadjuvant therapies. PMID:25568791

  1. Statistical evaluation of forecasts.

    PubMed

    Mader, Malenka; Mader, Wolfgang; Gluckman, Bruce J; Timmer, Jens; Schelter, Björn

    2014-08-01

    Reliable forecasts of extreme but rare events, such as earthquakes, financial crashes, and epileptic seizures, would render interventions and precautions possible. Therefore, forecasting methods have been developed which intend to raise an alarm if an extreme event is about to occur. In order to statistically validate the performance of a prediction system, it must be compared to the performance of a random predictor, which raises alarms independent of the events. Such a random predictor can be obtained by bootstrapping or analytically. We propose an analytic statistical framework which, in contrast to conventional methods, allows for validating independently the sensitivity and specificity of a forecasting method. Moreover, our method accounts for the periods during which an event has to remain absent or occur after a respective forecast.

  2. Statistical evaluation of forecasts

    NASA Astrophysics Data System (ADS)

    Mader, Malenka; Mader, Wolfgang; Gluckman, Bruce J.; Timmer, Jens; Schelter, Björn

    2014-08-01

    Reliable forecasts of extreme but rare events, such as earthquakes, financial crashes, and epileptic seizures, would render interventions and precautions possible. Therefore, forecasting methods have been developed which intend to raise an alarm if an extreme event is about to occur. In order to statistically validate the performance of a prediction system, it must be compared to the performance of a random predictor, which raises alarms independent of the events. Such a random predictor can be obtained by bootstrapping or analytically. We propose an analytic statistical framework which, in contrast to conventional methods, allows for validating independently the sensitivity and specificity of a forecasting method. Moreover, our method accounts for the periods during which an event has to remain absent or occur after a respective forecast.

  3. Precipitation and temperature ensemble forecasts from single-value forecasts

    NASA Astrophysics Data System (ADS)

    Schaake, J.; Demargne, J.; Hartman, R.; Mullusky, M.; Welles, E.; Wu, L.; Herr, H.; Fan, X.; Seo, D. J.

    2007-04-01

    A procedure is presented to construct ensemble forecasts from single-value forecasts of precipitation and temperature. This involves dividing the spatial forecast domain and total forecast period into a number of parts that are treated as separate forecast events. The spatial domain is divided into hydrologic sub-basins. The total forecast period is divided into time periods, one for each model time step. For each event archived values of forecasts and corresponding observations are used to model the joint distribution of forecasts and observations. The conditional distribution of observations for a given single-value forecast is used to represent the corresponding probability distribution of events that may occur for that forecast. This conditional forecast distribution subsequently is used to create ensemble members that vary in space and time using the "Schaake Shuffle" (Clark et al, 2004). The resulting ensemble members have the same space-time patterns as historical observations so that space-time joint relationships between events that have a significant effect on hydrological response tend to be preserved. Forecast uncertainty is space and time-scale dependent. For a given lead time to the beginning of the valid period of an event, forecast uncertainty depends on the length of the forecast valid time period and the spatial area to which the forecast applies. Although the "Schaake Shuffle" procedure, when applied to construct ensemble members from a time-series of single value forecasts, may preserve some of this scale dependency, it may not be sufficient without additional constraint. To account more fully for the time-dependent structure of forecast uncertainty, events for additional "aggregate" forecast periods are defined as accumulations of different "base" forecast periods. The generated ensemble members can be ingested by an Ensemble Streamflow Prediction system to produce ensemble forecasts of streamflow and other hydrological variables that reflect

  4. An overview of health forecasting.

    PubMed

    Soyiri, Ireneous N; Reidpath, Daniel D

    2013-01-01

    Health forecasting is a novel area of forecasting, and a valuable tool for predicting future health events or situations such as demands for health services and healthcare needs. It facilitates preventive medicine and health care intervention strategies, by pre-informing health service providers to take appropriate mitigating actions to minimize risks and manage demand. Health forecasting requires reliable data, information and appropriate analytical tools for the prediction of specific health conditions or situations. There is no single approach to health forecasting, and so various methods have often been adopted to forecast aggregate or specific health conditions. Meanwhile, there are no defined health forecasting horizons (time frames) to match the choices of health forecasting methods/approaches that are often applied. The key principles of health forecasting have not also been adequately described to guide the process. This paper provides a brief introduction and theoretical analysis of health forecasting. It describes the key issues that are important for health forecasting, including: definitions, principles of health forecasting, and the properties of health data, which influence the choices of health forecasting methods. Other matters related to the value of health forecasting, and the general challenges associated with developing and using health forecasting services are discussed. This overview is a stimulus for further discussions on standardizing health forecasting approaches and methods that will facilitate health care and health services delivery.

  5. Earthquake Forecasting, Validation and Verification

    NASA Astrophysics Data System (ADS)

    Rundle, J.; Holliday, J.; Turcotte, D.; Donnellan, A.; Tiampo, K.; Klein, B.

    2009-05-01

    Techniques for earthquake forecasting are in development using both seismicity data mining methods, as well as numerical simulations. The former rely on the development of methods to recognize patterns in data, while the latter rely on the use of dynamical models that attempt to faithfully replicate the actual fault systems. Testing such forecasts is necessary not only to determine forecast quality, but also to improve forecasts. A large number of techniques to validate and verify forecasts have been developed for weather and financial applications. Many of these have been elaborated in public locations, including, for example, the URL as listed below. Typically, the goal is to test for forecast resolution, reliability and sharpness. A good forecast is characterized by consistency, quality and value. Most, if not all of these forecast verification procedures can be readily applied to earthquake forecasts as well. In this talk, we discuss both methods of forecasting, as well as validation and verification using a number of these standard methods. We show how these test methods might be useful for both fault-based forecasting, a group of forecast methods that includes the WGCEP and simulator-based renewal models, and grid-based forecasting, which includes the Relative Intensity, Pattern Informatics, and smoothed seismicity methods. We find that applying these standard methods of forecast verification is straightforward. Judgments about the quality of a given forecast method can often depend on the test applied, as well as on the preconceptions and biases of the persons conducting the tests.

  6. Proceedings: Eleventh forecasting symposium. Forecasting in a competitive electricity market

    SciTech Connect

    Vogt, T.; Ignelzi, P.

    1998-10-01

    EPRI`s Eleventh Forecasting Symposium: ``Forecasting in a Competitive Electricity Market`` was held in Arlington, Virginia, in November 1997. This proceedings documents the symposium`s wide variety of topics, ranging from very-short-term operations issues to mid-term market planning issues. Speakers described the forecasting practices of other industries, predicted forecasting directions in the electric power industry; related their experiences with new forecasting approaches; and suggested further enhancements to forecasting methods, tools, and data. The objectives of the symposium were to explore the expanding roles of forecasting in a competitive market, to exchange information about forecasting techniques under development, and to discuss the forecasting techniques currently used by the electric power industry in and outside the US and in other industries. The 30 papers are arranged under the following topical sections: restructuring and regulatory issues--implications for forecasting; forecasting experiences in other industries; operations-related forecasting; data warehousing and database marketing; forecasting and risk management; understanding and predicting market prices; forecasting methods for the new environment; predicting customer response; and symposium wrap-up.

  7. On forecasting mortality.

    PubMed

    Olshansky, S J

    1988-01-01

    Official forecasts of mortality made by the U.S. Office of the Actuary throughout this century have consistently underestimated observed mortality declines. This is due, in part, to their reliance on the static extrapolation of past trends, an atheoretical statistical method that pays scant attention to the behavioral, medical, and social factors contributing to mortality change. A "multiple cause-delay model" more realistically portrays the effects on mortality of the presence of more favorable risk factors at the population level. Such revised assumptions produce large increases in forecasts of the size of the elderly population, and have a dramatic impact on related estimates of population morbidity, disability, and health care costs.

  8. Forecasting Methods for Institutional Research.

    ERIC Educational Resources Information Center

    Jennings, Linda W.; Young, Dean M.

    1988-01-01

    Increasing demands for accurate forecasts in such areas as student enrollment, energy expenditures, and facility capacity are placing new demands on the institutional researcher. A variety of forecasting models and methods are available, all to be used with caution in long-range forecasting. (Author/MSE)

  9. Corporate Forecasting: Promise and Reality

    ERIC Educational Resources Information Center

    Wheelwright, Steven C.; Clarke, Darral G.

    1976-01-01

    Discusses a survey of forecast preparers and users in 127 major companies in an attempt to assess underlying problems and identify areas for improvement. Concludes that forecasting responsibilities and tasks must be better defined and that forecast preparers and users must become better informed about one another's roles. (Author/JG)

  10. Federal Forecasters Directory, 1995.

    ERIC Educational Resources Information Center

    National Center for Education Statistics (ED), Washington, DC.

    This directory lists employees of the federal government who are involved in forecasting for policy formation and trend prediction purposes. Job title, agency, business address, phone or e-mail number, and specialty areas are listed for each employee. Employees are listed for the following agencies: (1) Bureau of the Census; (2) Bureau of Economic…

  11. Developing air quality forecasts

    NASA Astrophysics Data System (ADS)

    Lee, Pius; Saylor, Rick; Meagher, James

    2012-05-01

    Third International Workshop on Air Quality Forecasting Research; Potomac, Maryland, 29 November to 1 December 2011 Elevated concentrations of both near-surface ozone (O3) and fine particulate matter smaller than 2.5 micrometers in diameter have been implicated in increased mortality and other human health impacts. In light of these known influences on human health, many governments around the world have instituted air quality forecasting systems to provide their citizens with advance warning of impending poor air quality so that they can take actions to limit exposure. In an effort to improve the performance of air quality forecasting systems and provide a forum for the exchange of the latest research in air quality modeling, the International Workshop on Air Quality Forecasting Research (IWAQFR) was established in 2009 and is cosponsored by the U.S. National Oceanic and Atmospheric Administration (NOAA), Environment Canada (EC), and the World Meteorological Organization (WMO). The steering committee for IWAQFR's establishment was composed of Véronique Bouchet, Mike Howe, and Craig Stoud (EC); Greg Carmichael (University of Iowa); Paula Davidson and Jim Meagher (NOAA); and Liisa Jalkanen (WMO). The most recent workshop took place in Maryland.

  12. Probabilistic forecast for climate change over Northern Eurasia

    NASA Astrophysics Data System (ADS)

    Sokolov, Andrei; Monier, Erwan; Kicklighter, David; Scott, Jeffrey; Gao, Xiang; Schlosser, Adam

    2013-04-01

    In this study, we investigate possible climate change over Northern Eurasia and its impact on hydrological and carbon cycles. Northern Eurasia is a major player in the global carbon budget because of boreal forests and wetlands. Permafrost degradation associated with climate change could result in wetlands releasing large amounts of carbon dioxide and methane. Changes in the frequency and magnitude of extreme events, such as extreme precipitation, are likely to have substantial impacts on Northern Eurasia ecosystems. For this reason, it is very important to quantify the possible climate change over Northern Eurasia under different emissions scenarios, while accounting for the uncertainty in the climate response. For several decades, the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change has been investigating uncertainty in climate change using the MIT Integrated Global System Model (IGSM) framework, an integrated assessment model that couples an earth system model of intermediate complexity (with a 2D zonal-mean atmosphere) to a human activity model. Since the IGSM includes a human activity model, it is possible to analyze uncertainties in emissions resulting, for example, from different future climate policies. Another major feature is the flexibility to vary key climate parameters controlling the climate response: climate sensitivity, net aerosol forcing and ocean heat uptake rate. The IGSM has long been used to perform probabilistic forecasts based on estimates of probability density functions of climate parameters. The MIT IGSM-CAM framework links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM), with new modules developed and implemented in CAM to allow climate parameters to be changed to match those of the IGSM. The simulations discussed in this paper were carried out for two emission scenarios and three sets of climate parameters. The "business as usual" and a

  13. Forecasting carbon dioxide emissions.

    PubMed

    Zhao, Xiaobing; Du, Ding

    2015-09-01

    This study extends the literature on forecasting carbon dioxide (CO2) emissions by applying the reduced-form econometrics approach of Schmalensee et al. (1998) to a more recent sample period, the post-1997 period. Using the post-1997 period is motivated by the observation that the strengthening pace of global climate policy may have been accelerated since 1997. Based on our parameter estimates, we project 25% reduction in CO2 emissions by 2050 according to an economic and population growth scenario that is more consistent with recent global trends. Our forecasts are conservative due to that we do not have sufficient data to fully take into account recent developments in the global economy.

  14. Forecasting potential crises

    SciTech Connect

    Neufeld, W.P.

    1984-04-01

    Recently, the Trend Analysis Program (TAP) of the American Council of Life Insurance commissioned the Futures Group of Glastonbury, Connecticut, to examine the potential for large-scale catastrophic events in the near future. TAP was specifically concerned with five potential crises: the warming of the earth's atmosphere, the water shortage, the collapse of the physical infrastructure, the global financial crisis, and the threat of nuclear war. We are often unprepared to take action; in these cases, we lose an advantage we might have otherwise had. This is the whole idea behind forecasting: to foresee possibilities and to project how we can respond. If we are able to create forecasts against which we can test policy options and choices, we may have the luxury of adopting policies ahead of events. Rather than simply fighting fires, we have the option of creating a future more to our choosing. Short descriptions of these five potential crises and, in some cases, possible solutions are presented.

  15. Forecasting Infectious Disease Outbreaks

    NASA Astrophysics Data System (ADS)

    Shaman, J. L.

    2015-12-01

    Dynamic models of infectious disease systems abound and are used to study the epidemiological characteristics of disease outbreaks, the ecological mechanisms affecting transmission, and the suitability of various control and intervention strategies. The dynamics of disease transmission are non-linear and consequently difficult to forecast. Here, we describe combined model-inference frameworks developed for the prediction of infectious diseases. We show that accurate and reliable predictions of seasonal influenza outbreaks can be made using a mathematical model representing population-level influenza transmission dynamics that has been recursively optimized using ensemble data assimilation techniques and real-time estimates of influenza incidence. Operational real-time forecasts of influenza and other infectious diseases have been and are currently being generated.

  16. Uranium price forecasting methods

    SciTech Connect

    Fuller, D.M.

    1994-03-01

    This article reviews a number of forecasting methods that have been applied to uranium prices and compares their relative strengths and weaknesses. The methods reviewed are: (1) judgemental methods, (2) technical analysis, (3) time-series methods, (4) fundamental analysis, and (5) econometric methods. Historically, none of these methods has performed very well, but a well-thought-out model is still useful as a basis from which to adjust to new circumstances and try again.

  17. Frost Forecasting for Fruitgrowers

    NASA Technical Reports Server (NTRS)

    Martsolf, J. D.; Chen, E.

    1983-01-01

    Progress in forecasting from satellite data reviewed. University study found data from satellites displayed in color and used to predict frost are valuable aid to agriculture. Study evaluated scheme to use Earth-temperature data from Geostationary Operational Environmental Satellite in computer model that determines when and where freezing temperatures endanger developing fruit crops, such as apples, peaches and cherries in spring and citrus crops in winter.

  18. Satellite freeze forecast system

    NASA Technical Reports Server (NTRS)

    Martsolf, J. D. (Principal Investigator)

    1983-01-01

    Provisions for back-up operations for the satellite freeze forecast system are discussed including software and hardware maintenance and DS/1000-1V linkage; troubleshooting; and digitized radar usage. The documentation developed; dissemination of data products via television and the IFAS computer network; data base management; predictive models; the installation of and progress towards the operational status of key stations; and digital data acquisition are also considered. The d addition of dew point temperature into the P-model is outlined.

  19. Land-Breeze Forecasting

    NASA Technical Reports Server (NTRS)

    Case, Jonathan L.; Wheeler, Mark M.; Merceret, Francis J. (Technical Monitor)

    2002-01-01

    The nocturnal land breeze at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) is both operationally significant and challenging to forecast. The occurrence and timing of land breezes impact low-level winds, atmospheric stability, low temperatures, and fog development. Accurate predictions of the land breeze are critical for toxic material dispersion forecasts associated with space launch missions, since wind direction and low-level stability can change noticeably with the onset of a land breeze. This report presents a seven-year observational study of land breezes over east-central Florida from 1995 to 2001. This comprehensive analysis was enabled by the high-resolution tower observations over KSC/CCAFS. Five-minute observations of winds, temperature, and moisture along with 9 15-MHz Doppler Radar Wind Profiler data were used to analyze specific land-breeze cases, while the tower data were used to construct a composite climatology. Utilities derived from this climatology were developed to assist forecasters in determining the land-breeze occurrence, timing, and movement based on predicted meteorological conditions.

  20. EU pharmaceutical expenditure forecast

    PubMed Central

    Urbinati, Duccio; Rémuzat, Cécile; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    Background and Objectives With constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States’ pharmaceutical budgets. This model took into account population ageing, as well as current and future country-specific pricing, reimbursement, and market access policies (the project was performed for the European Commission; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). Method In order to have a representative heterogeneity of EU Member States, the following countries were selected for the analysis: France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. A forecasting period of 5 years (2012–2016) was chosen to assess the net pharmaceutical budget impact. A model for generics and biosimilars was developed for each country. The model estimated a separate and combined effect of the direct and indirect impacts of the patent cliff. A second model, estimating the sales development and the risk of development failure, was developed for new drugs. New drugs were reviewed individually to assess their clinical potential and translate it into commercial potential. The forecast was carried out according to three perspectives (healthcare public payer, society, and manufacturer), and several types of distribution chains (retail, hospital, and combined retail and hospital). Probabilistic and deterministic sensitivity analyses were carried out. Results According to the model, all countries experienced drug budget reductions except Poland (+€41 million). Savings were expected to be the highest in the United Kingdom (−€9,367 million), France

  1. Consistency among microphysics-convection-radiation processes in a numerical forecasting model

    NASA Astrophysics Data System (ADS)

    Bae, Soo Ya; Park, Raeseol; Hong, Song-You

    2016-04-01

    Radiative fluxes are mainly affected by the cloud optical properties calculated with effective radius, water path of hydrometeors, and cloud fraction. A prognostic cloud fraction scheme, which considers the cloud fraction with increments as a result of each physics process, is implemented in the Global/Regional Integrated Model system (GRIMs) (Park et al., 2016). However, the original RRTMG scheme does not consider the hydrometeor information from convection processes, resulting in inconsistency between cloud process and radiation activity. To ensure consistency among physics processes, the amount of hydrometeors from both the cumulus parameterization scheme (CPS) and microphysics schemes is explicitly taken into account in computing radiative fluxes. The effects of this modification are tested for a heavy rainfall over Korea to identify the feedback between the precipitation and radiation processes. It is found that the information of hydrometeors from CPS tends to increase water path, which leads to larger cloud optical depth and cooling. Skill scores of the simulated precipitation in a medium-range forecast testbed confirm benefits of the consistent treatment of hydrometeors in both CPS and radiation processes.

  2. Local flood forecasting - From data collection to communicating forecasts

    NASA Astrophysics Data System (ADS)

    Smith, P. J.; Beven, K.

    2013-12-01

    An important aspect of improving resilience to flooding is the provision of timely warnings to flood sensitive locations thus allowing mitigating measures to be implemented. For specific locations such small communities (often in head water catchments) or river side factories the ability of traditional centralised forecasting systems to provide timely & accurate forecasts may be challenged. This is due in part to the finite resources of monitoring agencies which results in courser spatial scales of model and data collection then may be required for the generation of accurate forecasts. One strategy to improve flood resilience at such locations is to develop automated location specific forecasts. In this presentation we outline a methodology to achieve this based on the installation of adequate telemetered monitoring equipment; generally a water level sensor and a rain gauge. This allows the construction of a local flood forecasting model which may be coupled with available precipitation forecasts. The construction of the hydrological forecasting model consists of a guided process which incorporates both data assimilation and the representation of the forecast uncertainty based on post processing. The guided process requires the modeller to make only a few choices thus allowing rapid model deployment and revision. To be of use the derived forecasts must be made available in real time and updated frequently; maybe every five minutes. Traditional practices in issuing warnings dependent on expert interpretation must therefore be altered so that those at the site of interest become their own `experts'. To aid this appropriate presentation of both the predictions and past performance of the model, designed to encourage realistic interpretation of the forecasts and their uncertainties is considered. The resulting forecast chain is demonstrated on UK case studies.

  3. Hydrologic Forecasting and Hydropower Production

    NASA Astrophysics Data System (ADS)

    Wigmosta, M. S.; Voisin, N.; Lettenmaier, D. P.; Coleman, A.; Mishra, V.; Schaner, N. A.

    2011-12-01

    Hydroelectric power production is one of many competing demands for available water along with other priority uses such as irrigation, thermoelectric cooling, municipal, recreation, and environmental performance. Increasingly, hydroelectric generation is being used to offset the intermittent nature of some renewable energy sources such as wind-generated power. An accurate forecast of the magnitude and timing of water supply assists managers in integrated planning and operations to balance competing water uses against current and future supply while protecting against the possibility of water or energy shortages and excesses with real-time actions. We present a medium-range to seasonal ensemble streamflow forecasting system where uncertainty in forecasts is addressed explicitly. The integrated forecast system makes use of remotely-sensed data and automated spatial and temporal data assimilation. Remotely-sensed snow cover, observed snow water equivalent, and observed streamflow data are used to update the hydrologic model state prior to the forecast. In forecast mode, the hydrology model is forced by calibrated ensemble weather/climate forecasts. This system will be fully integrated into a water optimization toolset to inform reservoir and power operations, and guide environmental performance decision making. This flow forecast system development is carried out in agreement with the National Weather Service so that the system can later be incorporated into the NOAA eXperimental Ensemble Forecast Service (XEFS).

  4. Forecasting droughts in East Africa

    NASA Astrophysics Data System (ADS)

    Mwangi, E.; Wetterhall, F.; Dutra, E.; Di Giuseppe, F.; Pappenberger, F.

    2014-02-01

    The humanitarian crises caused by the recent droughts (2008-2009 and 2010-2011) in East Africa have illustrated that the ability to make accurate drought forecasts with sufficient lead time is essential. The use of dynamical model precipitation forecasts in combination with drought indices, such as the Standardized Precipitation Index (SPI), can potentially lead to a better description of drought duration, magnitude and spatial extent. This study evaluates the use of the European Centre for Medium-Range Weather Forecasts (ECMWF) products in forecasting droughts in East Africa. ECMWF seasonal precipitation shows significant skill for March-May and October-December rain seasons when evaluated against measurements from the available in situ stations from East Africa. The forecast for October-December rain season has higher skill than for the March-May season. ECMWF forecasts add value to the consensus forecasts produced during the Greater Horn of Africa Climate Outlook Forum (GHACOF), which is the present operational product for precipitation forecast over East Africa. Complementing the original ECMWF precipitation forecasts with SPI provides additional information on the spatial extent and intensity of the drought event.

  5. Solar Indices Forecasting Tool

    NASA Astrophysics Data System (ADS)

    Henney, Carl John; Shurkin, Kathleen; Arge, Charles; Hill, Frank

    2016-05-01

    Progress to forecast key space weather parameters using SIFT (Solar Indices Forecasting Tool) with the ADAPT (Air Force Data Assimilative Photospheric flux Transport) model is highlighted in this presentation. Using a magnetic flux transport model, ADAPT, we estimate the solar near-side field distribution that is used as input into empirical models for predicting F10.7(solar 10.7 cm, 2.8 GHz, radio flux), the Mg II core-to-wing ratio, and selected bands of solar far ultraviolet (FUV) and extreme ultraviolet (EUV) irradiance. Input to the ADAPT model includes the inferred photospheric magnetic field from the NISP ground-based instruments, GONG & VSM. Besides a status update regarding ADAPT and SIFT models, we will summarize the findings that: 1) the sum of the absolute value of strong magnetic fields, associated with sunspots, is shown to correlate well with the observed daily F10.7 variability (Henney et al. 2012); and 2) the sum of the absolute value of weak magnetic fields, associated with plage regions, is shown to correlate well with EUV and FUV irradiance variability (Henney et al. 2015). This work utilizes data produced collaboratively between Air Force Research Laboratory (AFRL) and the National Solar Observatory (NSO). The ADAPT model development is supported by AFRL. The input data utilized by ADAPT is obtained by NISP (NSO Integrated Synoptic Program). NSO is operated by the Association of Universities for Research in Astronomy (AURA), Inc., under a cooperative agreement with the National Science Foundation (NSF). The 10.7 cm solar radio flux data service, utilized by the ADAPT/SIFT F10.7 forecasting model, is operated by the National Research Council of Canada and National Resources Canada, with the support of the Canadian Space Agency.

  6. Weather Forecasting Aid

    NASA Technical Reports Server (NTRS)

    1979-01-01

    Weather forecasters are usually very precise in reporting such conditions as temperature, wind velocity and humidity. They also provide exact information on barometric pressure at a given moment, and whether the barometer is "rising" or "falling"- but not how rapidly or how slowly it is rising or falling. Until now, there has not been available an instrument which measures precisely the current rate of change of barometric pressure. A meteorological instrument called a barograph traces the historical ups and downs of barometric pressure and plots a rising or falling curve, but, updated every three hours, it is only momentarily accurate at each updating.

  7. Operational Geomagnetic Forecast Service

    NASA Astrophysics Data System (ADS)

    Semeniv, O.; Polonska, A.; Parnowski, A.

    2014-12-01

    The operational forecasting service for real-time geomagnetic indices Dst and Kp was described. The warning time for the Earth to the intersection of the Dst index is 1-4 hours, for the Kp index - 3 hours. The skillscore parameter, which is defined as a decrease of the relative mean square error with respect to the trivial model, was approximately 40% for Dst and 15% for Kp. The service works on-line freely available through STAFF http://www.staff.oma.be/ browser.

  8. Handbook of Forecasting Techniques

    DTIC Science & Technology

    1975-12-01

    SOCIAL POLICYISTANFORD RESEARCH INSTITUTE POLICY RESEARCH, ,R6156T 10 SRI Project VMO-U3738 ~: .. ~ BURNHAM H. DODGE DAVID C. MILLER PETER SCHWARTZ...G.IKruzic, David C.IMillvr DACW 31l75-C-RM7 ~0 IltLATI~ililON NliikAilMMIE AOADORD S0I 0N( LMETPET TASKC Center for the Study of Social Policy A R, I I...methods suitable for a wide range of technological, economic, social , and environmetntal forecasting are selected and discussed. Procedures for using each

  9. Forecasting in Complex Systems

    NASA Astrophysics Data System (ADS)

    Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.

    2014-12-01

    Complex nonlinear systems are typically characterized by many degrees of freedom, as well as interactions between the elements. Interesting examples can be found in the areas of earthquakes and finance. In these two systems, fat tails play an important role in the statistical dynamics. For earthquake systems, the Gutenberg-Richter magnitude-frequency is applicable, whereas for daily returns for the securities in the financial markets are known to be characterized by leptokurtotic statistics in which the tails are power law. Very large fluctuations are present in both systems. In earthquake systems, one has the example of great earthquakes such as the M9.1, March 11, 2011 Tohoku event. In financial systems, one has the example of the market crash of October 19, 1987. Both were largely unexpected events that severely impacted the earth and financial systems systemically. Other examples include the M9.3 Andaman earthquake of December 26, 2004, and the Great Recession which began with the fall of Lehman Brothers investment bank on September 12, 2013. Forecasting the occurrence of these damaging events has great societal importance. In recent years, national funding agencies in a variety of countries have emphasized the importance of societal relevance in research, and in particular, the goal of improved forecasting technology. Previous work has shown that both earthquakes and financial crashes can be described by a common Landau-Ginzburg-type free energy model. These metastable systems are characterized by fat tail statistics near the classical spinodal. Correlations in these systems can grow and recede, but do not imply causation, a common source of misunderstanding. In both systems, a common set of techniques can be used to compute the probabilities of future earthquakes or crashes. In this talk, we describe the basic phenomenology of these systems and emphasize their similarities and differences. We also consider the problem of forecast validation and verification

  10. Forecast Mekong: 2011 update

    USGS Publications Warehouse

    Turnipseed, D. Phil

    2011-01-01

    In 2009, U.S. Secretary of State Hillary R. Clinton joined with the Foreign Ministers of Cambodia, Laos, Thailand, and Vietnam in launching the Lower Mekong Initiative to enhance U.S. engagement with the Lower Mekong countries in the areas of environment, health, education, and infrastructure. Part of the Lower Mekong Initiative, the U.S. Geological Survey's Forecast Mekong project is engaging the United States in scientific research relevant to environmental issues in the Lower Mekong River countries and is staying the course in support of the Mekong Nations with a suite of new projects for 2011.

  11. 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.

  12. Social Indicators and Social Forecasting.

    ERIC Educational Resources Information Center

    Johnston, Denis F.

    The paper identifies major types of social indicators and explains how they can be used in social forecasting. Social indicators are defined as statistical measures relating to major areas of social concern and/or individual well being. Examples of social indicators are projections, forecasts, outlook statements, time-series statistics, and…

  13. Now, Here's the Weather Forecast...

    ERIC Educational Resources Information Center

    Richardson, Mathew

    2013-01-01

    The Met Office has a long history of weather forecasting, creating tailored weather forecasts for customers across the world. Based in Exeter, the Met Office is also home to the Met Office Hadley Centre, a world-leading centre for the study of climate change and its potential impacts. Climate information from the Met Office Hadley Centre is used…

  14. The pioneers of weather forecasting

    NASA Astrophysics Data System (ADS)

    Ballard, Susan

    2016-01-01

    In The Weather Experiment author Peter Moore takes us on a compelling journey through the early history of weather forecasting, bringing to life the personalities, lives and achievements of the men who put in place the building blocks required for forecasts to be possible.

  15. Regional-seasonal weather forecasting

    SciTech Connect

    Abarbanel, H.; Foley, H.; MacDonald, G.; Rothaus, O.; Rudermann, M.; Vesecky, J.

    1980-08-01

    In the interest of allocating heating fuels optimally, the state-of-the-art for seasonal weather forecasting is reviewed. A model using an enormous data base of past weather data is contemplated to improve seasonal forecasts, but present skills do not make that practicable. 90 references. (PSB)

  16. Statistical Earthquake Focal Mechanism Forecasts

    NASA Astrophysics Data System (ADS)

    Kagan, Y. Y.; Jackson, D. D.

    2013-12-01

    The new whole Earth focal mechanism forecast, based on the GCMT catalog, has been created. In the present forecast, the sum of normalized seismic moment tensors within 1000 km radius is calculated and the P- and T-axes for the focal mechanism are evaluated on the basis of the sum. Simultaneously we calculate an average rotation angle between the forecasted mechanism and all the surrounding mechanisms. This average angle shows tectonic complexity of a region and indicates the accuracy of the prediction. The method was originally proposed by Kagan and Jackson (1994, JGR). Recent interest by CSEP and GEM has motivated some improvements, particularly to extend the previous forecast to polar and near-polar regions. The major problem in extending the forecast is the focal mechanism calculation on a spherical surface. In the previous forecast as our average focal mechanism was computed, it was assumed that longitude lines are approximately parallel within 1000 km radius. This is largely accurate in the equatorial and near-equatorial areas. However, when one approaches the 75 degree latitude, the longitude lines are no longer parallel: the bearing (azimuthal) difference at points separated by 1000 km reach about 35 degrees. In most situations a forecast point where we calculate an average focal mechanism is surrounded by earthquakes, so a bias should not be strong due to the difference effect cancellation. But if we move into polar regions, the bearing difference could approach 180 degrees. In a modified program focal mechanisms have been projected on a plane tangent to a sphere at a forecast point. New longitude axes which are parallel in the tangent plane are corrected for the bearing difference. A comparison with the old 75S-75N forecast shows that in equatorial regions the forecasted focal mechanisms are almost the same, and the difference in the forecasted focal mechanisms rotation angle is close to zero. However, though the forecasted focal mechanisms are similar

  17. Weather Forecasting Systems and Methods

    NASA Technical Reports Server (NTRS)

    Mecikalski, John (Inventor); MacKenzie, Wayne M., Jr. (Inventor); Walker, John Robert (Inventor)

    2014-01-01

    A weather forecasting system has weather forecasting logic that receives raw image data from a satellite. The raw image data has values indicative of light and radiance data from the Earth as measured by the satellite, and the weather forecasting logic processes such data to identify cumulus clouds within the satellite images. For each identified cumulus cloud, the weather forecasting logic applies interest field tests to determine a score indicating the likelihood of the cumulus cloud forming precipitation and/or lightning in the future within a certain time period. Based on such scores, the weather forecasting logic predicts in which geographic regions the identified cumulus clouds will produce precipitation and/or lighting within during the time period. Such predictions may then be used to provide a weather map thereby providing users with a graphical illustration of the areas predicted to be affected by precipitation within the time period.

  18. Forecasting global atmospheric CO2

    NASA Astrophysics Data System (ADS)

    Agustí-Panareda, A.; Massart, S.; Chevallier, F.; Boussetta, S.; Balsamo, G.; Beljaars, A.; Ciais, P.; Deutscher, N. M.; Engelen, R.; Jones, L.; Kivi, R.; Paris, J.-D.; Peuch, V.-H.; Sherlock, V.; Vermeulen, A. T.; Wennberg, P. O.; Wunch, D.

    2014-11-01

    A new global atmospheric carbon dioxide (CO2) real-time forecast is now available as part of the pre-operational Monitoring of Atmospheric Composition and Climate - Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO2 forecasting system is that the land surface, including vegetation CO2 fluxes, is modelled online within the IFS. Other CO2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO2 fluxes also lead to accumulating errors in the CO2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO2 fluxes compared to total optimized fluxes and the atmospheric CO2 compared to observations. The largest biases in the atmospheric CO2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO2 analyses based on the assimilation of CO2 products retrieved from satellite measurements and

  19. Forecasting global atmospheric CO2

    NASA Astrophysics Data System (ADS)

    Agustí-Panareda, A.; Massart, S.; Chevallier, F.; Boussetta, S.; Balsamo, G.; Beljaars, A.; Ciais, P.; Deutscher, N. M.; Engelen, R.; Jones, L.; Kivi, R.; Paris, J.-D.; Peuch, V.-H.; Sherlock, V.; Vermeulen, A. T.; Wennberg, P. O.; Wunch, D.

    2014-05-01

    A new global atmospheric carbon dioxide (CO2) real-time forecast is now available as part of the pre-operational Monitoring of Atmospheric Composition and Climate - Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO2 forecasting system is that the land surface, including vegetation CO2 fluxes, is modelled online within the IFS. Other CO2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO2 fluxes also lead to accumulating errors in the CO2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO2 fluxes compared to total optimized fluxes and the atmospheric CO2 compared to observations. The largest biases in the atmospheric CO2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO2 analyses based on the assimilation of CO2 satellite retrievals, as they become available in

  20. GALE improves snow forecasting

    NASA Astrophysics Data System (ADS)

    Scientific results from an intensive study of winter storms on the U.S. East Coast last year contributed to improved weather forecasts of two successive snowstorms that virtually closed down Washington, D.C., for several days in January 1987.In the Genesis of Atlantic Lows Experiment (GALE) field project, scientists took detailed measurements simultaneously from the atmosphere and the ocean to study how these features interact at various stages of an East Coast winter storm, according to project director Richard Dirks, who is with the National Center for Atmospheric Research (NCAR) in Boulder, Colo. “It's interesting that we actually had four storms [in the GALE study] that were of similar intensity to the two East Coast storms” in January 1987, Dirks said. “However, last year the temperatures were warmer, and the storm tracks were located somewhat further offshore and therefore did not significantly affect the northeast corridor with heavy snows.”

  1. Tropical forecasting - Predictability perspective

    NASA Technical Reports Server (NTRS)

    Shukla, J.

    1989-01-01

    Results are presented of classical predictability studies and forecast experiments with observed initial conditions to show the nature of initial error growth and final error equilibration for the tropics and midlatitudes, separately. It is found that the theoretical upper limit of tropical circulation predictability is far less than for midlatitudes. The error growth for a complete general circulation model is compared to a dry version of the same model in which there is no prognostic equation for moisture, and diabatic heat sources are prescribed. It is found that the growth rate of synoptic-scale errors for the dry model is significantly smaller than for the moist model, suggesting that the interactions between dynamics and moist processes are among the important causes of atmospheric flow predictability degradation. Results are then presented of numerical experiments showing that correct specification of the slowly varying boundary condition of SST produces significant improvement in the prediction of time-averaged circulation and rainfall over the tropics.

  2. Forecasting droughts in East Africa

    NASA Astrophysics Data System (ADS)

    Mwangi, Emmah; Wetterhall, Fredrik; Dutra, Emanuel; Di Giuseppe, Francesca; Pappenberger, Florian

    2014-05-01

    The humanitarian crisis caused by the recent droughts (2008-2009 and 2010-2011) in East Africa have illustrated that the ability to make accurate drought predictions with sufficient lead time is essential. The use of dynamical model forecasts in combination with drought indices, such as the Standardized Precipitation Index (SPI), can potentially to lead to a better description of drought duration, magnitude and spatial extent. This study evaluates the use of the European Centre for Medium-Range Weather Forecasts (ECMWF) products in forecasting droughts in East Africa. ECMWF seasonal precipitation shows significant skill for both rain seasons when evaluated against measurements from the available in-situ stations from East Africa. The forecast for October-December rain season has higher skill than for the March-May season. ECMWF forecasts add value to the statistical forecasts produced during the Greater Horn of Africa Climate Outlook Forums (GHACOF), which is the present operational product. Complementing the raw precipitation forecasts with SPI provides additional information on the spatial extent and intensity of the drought event.

  3. Application of quantitative precipitation forecasting and precipitation ensemble prediction for hydrological forecasting

    NASA Astrophysics Data System (ADS)

    Tao, P.; Tie-Yuan, S.; Zhi-Yuan, Y.; Jun-Chao, W.

    2015-05-01

    The precipitation in the forecast period influences flood forecasting precision, due to the uncertainty of the input to the hydrological model. Taking the ZhangHe basin as the example, the research adopts the precipitation forecast and ensemble precipitation forecast product of the AREM model, uses the Xin Anjiang hydrological model, and tests the flood forecasts. The results show that the flood forecast result can be clearly improved when considering precipitation during the forecast period. Hydrological forecast based on Ensemble Precipitation prediction gives better hydrological forecast information, better satisfying the need for risk information for flood prevention and disaster reduction, and has broad development opportunities.

  4. Value of Wind Power Forecasting

    SciTech Connect

    Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

    2011-04-01

    This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

  5. Method Forecasts Global Energy Substitution

    ERIC Educational Resources Information Center

    Chemical and Engineering News, 1975

    1975-01-01

    Describes a model developed to forecast energy demands and determine trends in demand for primary fuels. The energy model essentially considers primary energy sources as competing commodities in a market. (MLH)

  6. Forecast of solar cycle 25

    NASA Astrophysics Data System (ADS)

    Krasotkin, Serge; Shmorgilov, Feodor

    The revised method of equal phase averaging was used to predict the main features of the solar cycle 25. The forecast of Wolf number values was obtained not only for solar cycle maximum but for 16 phases of the cycle. The double-peak structure of the cycle maximum phase is well seen. The problems of the long- and superlong-term forecasts of solar activity are discussed.

  7. Preparing for an Uncertain Forecast

    ERIC Educational Resources Information Center

    Karolak, Eric

    2011-01-01

    Navigating the world of government relations and public policy can be a little like predicting the weather. One can't always be sure what's in store or how it will affect him/her down the road. But there are common patterns and a few basic steps that can help one best prepare for a change in the forecast. Though the forecast is uncertain, early…

  8. Forecasting Thermosphere Density: an Overview

    NASA Astrophysics Data System (ADS)

    Bruinsma, S.

    2015-12-01

    Our knowledge of the thermosphere has improved considerably since 2000 thanks to the availability of high-resolution accelerometer inferred densities. Consequently, precision and shortcomings of thermosphere models are better known. Thermosphere density forecast accuracy is limited by: 1) the accuracy of the thermosphere model 2) the solar and geomagnetic activity forecast 3) the quality of the data assimilation system. The precision of semi-empirical thermosphere models is 10-25%. Solar activity forecasts can be accurate up to 5 days. They become less accurate with time, but some proxies are more forecastable than others. Geomagnetic activity forecasting is more problematic, since in most cases storm events cannot be predicted on any time scale. The forecast accuracy is ultimately bounded by the thermosphere model precision and the (varying) degree to which mainly the solar proxy represents EUV heating of the atmosphere. Both errors can be corrected for by means of near real time (nrt) assimilation of satellite drag data, provided that the data is of high quality. At present, only the classified High Accuracy Satellite Drag Model of the Air Force has that capability operationally, even if other prototype nrt models have been developed. Data assimilation significantly improves density forecasts up to 72-hours out; there is no gain for longer periods due to the short memory of the thermosphere system. Only physical models, e.g. TIMEGCM and CTIPe, can in principle reproduce the dynamic changes in density for example during geomagnetic storms. However, accurate information on atmospheric heating is often missing, or not used. When it is, observed and modeled Traveling Atmospheric Disturbances are very similar. Nonmigrating tides and waves propagating from the lower atmosphere cause longitudinal density variations; sources of geophysical noise for semi-empirical models, they can be predicted qualitatively and sometimes quantitatively with physical models. This

  9. Survey of air cargo forecasting techniques

    NASA Technical Reports Server (NTRS)

    Kuhlthan, A. R.; Vermuri, R. S.

    1978-01-01

    Forecasting techniques currently in use in estimating or predicting the demand for air cargo in various markets are discussed with emphasis on the fundamentals of the different forecasting approaches. References to specific studies are cited when appropriate. The effectiveness of current methods is evaluated and several prospects for future activities or approaches are suggested. Appendices contain summary type analyses of about 50 specific publications on forecasting, and selected bibliographies on air cargo forecasting, air passenger demand forecasting, and general demand and modalsplit modeling.

  10. Municipal water consumption forecast accuracy

    NASA Astrophysics Data System (ADS)

    Fullerton, Thomas M.; Molina, Angel L.

    2010-06-01

    Municipal water consumption planning is an active area of research because of infrastructure construction and maintenance costs, supply constraints, and water quality assurance. In spite of that, relatively few water forecast accuracy assessments have been completed to date, although some internal documentation may exist as part of the proprietary "grey literature." This study utilizes a data set of previously published municipal consumption forecasts to partially fill that gap in the empirical water economics literature. Previously published municipal water econometric forecasts for three public utilities are examined for predictive accuracy against two random walk benchmarks commonly used in regional analyses. Descriptive metrics used to quantify forecast accuracy include root-mean-square error and Theil inequality statistics. Formal statistical assessments are completed using four-pronged error differential regression F tests. Similar to studies for other metropolitan econometric forecasts in areas with similar demographic and labor market characteristics, model predictive performances for the municipal water aggregates in this effort are mixed for each of the municipalities included in the sample. Given the competitiveness of the benchmarks, analysts should employ care when utilizing econometric forecasts of municipal water consumption for planning purposes, comparing them to recent historical observations and trends to insure reliability. Comparative results using data from other markets, including regions facing differing labor and demographic conditions, would also be helpful.

  11. Forecasting droughts in East Africa

    NASA Astrophysics Data System (ADS)

    Mwangi, E.; Wetterhall, F.; Dutra, E.; Di Giuseppe, F.; Pappenberger, F.

    2013-08-01

    The humanitarian crisis caused by the recent droughts (2008-2009 and 2010-2011) in the East African region have illustrated that the ability to make accurate drought predictions with adequate lead time is essential. The use of dynamical model forecasts and drought indices, such as Standardized Precipitation Index (SPI), promises to lead to a better description of drought duration, magnitude and spatial extent. This study evaluates the use of the European Centre for Medium-Range Weather Forecasts (ECMWF) products in forecasting droughts in East Africa. ECMWF seasonal precipitation shows significant skill for both rain seasons when evaluated against measurements from the available in-situ stations from East Africa. The October-December rain season has higher skill that the March-May season. ECMWF forecasts add value to the statistical forecasts produced during the Greater Horn of Africa Climate Outlook Forums (GHACOF) which is the present operational product. Complementing the raw precipitation forecasts with SPI provides additional information on the spatial extend and intensity of the drought event.

  12. Practical Meteor Stream Forecasting

    NASA Technical Reports Server (NTRS)

    Cooke, William J.; Suggs, Robert M.

    2003-01-01

    Inspired by the recent Leonid meteor storms, researchers have made great strides in our ability to predict enhanced meteor activity. However, the necessary calibration of the meteor stream models with Earth-based ZHRs (Zenith Hourly Rates) has placed emphasis on the terran observer and meteor activity predictions are published in such a manner to reflect this emphasis. As a consequence, many predictions are often unusable by the satellite community, which has the most at stake and the greatest interest in meteor forecasting. This paper suggests that stream modelers need to pay more attention to the needs of this community and publish not just durations and times of maxima for Earth, but everything needed to characterize the meteor stream in and out of the plane of the ecliptic, which, at a minimum, consists of the location of maximum stream density (ZHR) and the functional form of the density decay with distance from this point. It is also suggested that some of the terminology associated with meteor showers may need to be more strictly defined in order to eliminate the perception of crying wolf by meteor scientists. An outburst is especially problematic, as it usually denotes an enhancement by a factor of 2 or more to researchers, but conveys the notion of a sky filled with meteors to satellite operators and the public. Experience has also taught that predicted ZHRs often lead to public disappointment, as these values vastly overestimate what is seen.

  13. Statistical earthquake focal mechanism forecasts

    NASA Astrophysics Data System (ADS)

    Kagan, Yan Y.; Jackson, David D.

    2014-04-01

    Forecasts of the focal mechanisms of future shallow (depth 0-70 km) earthquakes are important for seismic hazard estimates and Coulomb stress, and other models of earthquake occurrence. Here we report on a high-resolution global forecast of earthquake rate density as a function of location, magnitude and focal mechanism. In previous publications we reported forecasts of 0.5° spatial resolution, covering the latitude range from -75° to +75°, based on the Global Central Moment Tensor earthquake catalogue. In the new forecasts we have improved the spatial resolution to 0.1° and the latitude range from pole to pole. Our focal mechanism estimates require distance-weighted combinations of observed focal mechanisms within 1000 km of each gridpoint. Simultaneously, we calculate an average rotation angle between the forecasted mechanism and all the surrounding mechanisms, using the method of Kagan & Jackson proposed in 1994. This average angle reveals the level of tectonic complexity of a region and indicates the accuracy of the prediction. The procedure becomes problematical where longitude lines are not approximately parallel, and where shallow earthquakes are so sparse that an adequate sample spans very large distances. North or south of 75°, the azimuths of points 1000 km away may vary by about 35°. We solved this problem by calculating focal mechanisms on a plane tangent to the Earth's surface at each forecast point, correcting for the rotation of the longitude lines at the locations of earthquakes included in the averaging. The corrections are negligible between -30° and +30° latitude, but outside that band uncorrected rotations can be significantly off. Improved forecasts at 0.5° and 0.1° resolution are posted at http://eq.ess.ucla.edu/kagan/glob_gcmt_index.html.

  14. Using ecological forecasting of future vegetation transition and fire frequency change in the Sierra Nevada to assess fire management strategies

    NASA Astrophysics Data System (ADS)

    Thorne, J. H.; Schwartz, M. W.; Holguin, A. J.; Moritz, M.; Batllori, E.; Folger, K.; Nydick, K.

    2013-12-01

    strong upslope shifting of open grassland, chaparral and hardwood types, which may be initiated by increased fire frequencies, particularly where fires have not recently burned within normal fire recurrence interval departures (FRID). An evaluation of four fire management strategies (business as usual; resist change; foster orderly change; protect vital resources) across four combinations of future climate and fire frequency found that no single management strategy was uniformly successful in protecting critical resources across the range of future conditions examined. This limitation is somewhat driven by current management constraints on the amount of management available to resource managers, which suggests management will need to use a triage approach to application of proactive fire management strategies, wherein MOC landscape projections can be used in decision support.

  15. Automation of energy demand forecasting

    NASA Astrophysics Data System (ADS)

    Siddique, Sanzad

    Automation of energy demand forecasting saves time and effort by searching automatically for an appropriate model in a candidate model space without manual intervention. This thesis introduces a search-based approach that improves the performance of the model searching process for econometrics models. Further improvements in the accuracy of the energy demand forecasting are achieved by integrating nonlinear transformations within the models. This thesis introduces machine learning techniques that are capable of modeling such nonlinearity. Algorithms for learning domain knowledge from time series data using the machine learning methods are also presented. The novel search based approach and the machine learning models are tested with synthetic data as well as with natural gas and electricity demand signals. Experimental results show that the model searching technique is capable of finding an appropriate forecasting model. Further experimental results demonstrate an improved forecasting accuracy achieved by using the novel machine learning techniques introduced in this thesis. This thesis presents an analysis of how the machine learning techniques learn domain knowledge. The learned domain knowledge is used to improve the forecast accuracy.

  16. Advances in Solar Power Forecasting

    NASA Astrophysics Data System (ADS)

    Haupt, S. E.; Kosovic, B.; Drobot, S.

    2014-12-01

    The National Center for Atmospheric Research and partners are building a blended SunCast Solar Power Forecasting system. This system includes several short-range nowcasting models and improves upon longer range numerical weather prediction (NWP) models as part of the "Public-Private-Academic Partnership to Advance Solar Power Forecasting." The nowcasting models being built include statistical learning models that include cloud regime prediction, multiple sky imager-based advection models, satellite image-based advection models, and rapid update NWP models with cloud assimilation. The team has also integrated new modules into the Weather Research and Forecasting Model (WRF) to better predict clouds, aerosols, and irradiance. The modules include a new shallow convection scheme; upgraded physics parameterizations of clouds; new radiative transfer modules that specify GHI, DNI, and DIF prediction; better satellite assimilation methods; and new aerosol estimation methods. These new physical models are incorporated into WRF-Solar, which is then integrated with publically available NWP models via the Dynamic Integrated Forecast (DICast) system as well as the Nowcast Blender to provide seamless forecasts at partner utility and balancing authority commercial solar farms. The improvements will be described and results to date discussed.

  17. Communicating Storm Surge Forecast Uncertainty

    NASA Astrophysics Data System (ADS)

    Troutman, J. A.; Rhome, J.

    2015-12-01

    When it comes to tropical cyclones, storm surge is often the greatest threat to life and property along the coastal United States. The coastal population density has dramatically increased over the past 20 years, putting more people at risk. Informing emergency managers, decision-makers and the public about the potential for wind driven storm surge, however, has been extremely difficult. Recently, the Storm Surge Unit at the National Hurricane Center in Miami, Florida has developed a prototype experimental storm surge watch/warning graphic to help communicate this threat more effectively by identifying areas most at risk for life-threatening storm surge. This prototype is the initial step in the transition toward a NWS storm surge watch/warning system and highlights the inundation levels that have a 10% chance of being exceeded. The guidance for this product is the Probabilistic Hurricane Storm Surge (P-Surge) model, which predicts the probability of various storm surge heights by statistically evaluating numerous SLOSH model simulations. Questions remain, however, if exceedance values in addition to the 10% may be of equal importance to forecasters. P-Surge data from 2014 Hurricane Arthur is used to ascertain the practicality of incorporating other exceedance data into storm surge forecasts. Extracting forecast uncertainty information through analyzing P-surge exceedances overlaid with track and wind intensity forecasts proves to be beneficial for forecasters and decision support.

  18. Forecasting seasonal outbreaks of influenza

    PubMed Central

    Shaman, Jeffrey; Karspeck, Alicia

    2012-01-01

    Influenza recurs seasonally in temperate regions of the world; however, our ability to predict the timing, duration, and magnitude of local seasonal outbreaks of influenza remains limited. Here we develop a framework for initializing real-time forecasts of seasonal influenza outbreaks, using a data assimilation technique commonly applied in numerical weather prediction. The availability of real-time, web-based estimates of local influenza infection rates makes this type of quantitative forecasting possible. Retrospective ensemble forecasts are generated on a weekly basis following assimilation of these web-based estimates for the 2003–2008 influenza seasons in New York City. The findings indicate that real-time skillful predictions of peak timing can be made more than 7 wk in advance of the actual peak. In addition, confidence in those predictions can be inferred from the spread of the forecast ensemble. This work represents an initial step in the development of a statistically rigorous system for real-time forecast of seasonal influenza. PMID:23184969

  19. Forecasting seasonal outbreaks of influenza.

    PubMed

    Shaman, Jeffrey; Karspeck, Alicia

    2012-12-11

    Influenza recurs seasonally in temperate regions of the world; however, our ability to predict the timing, duration, and magnitude of local seasonal outbreaks of influenza remains limited. Here we develop a framework for initializing real-time forecasts of seasonal influenza outbreaks, using a data assimilation technique commonly applied in numerical weather prediction. The availability of real-time, web-based estimates of local influenza infection rates makes this type of quantitative forecasting possible. Retrospective ensemble forecasts are generated on a weekly basis following assimilation of these web-based estimates for the 2003-2008 influenza seasons in New York City. The findings indicate that real-time skillful predictions of peak timing can be made more than 7 wk in advance of the actual peak. In addition, confidence in those predictions can be inferred from the spread of the forecast ensemble. This work represents an initial step in the development of a statistically rigorous system for real-time forecast of seasonal influenza.

  20. Smooth Sailing for Weather Forecasting

    NASA Technical Reports Server (NTRS)

    2002-01-01

    Through a cooperative venture with NASA's Stennis Space Center, WorldWinds, Inc., developed a unique weather and wave vector map using space-based radar satellite information and traditional weather observations. Called WorldWinds, the product provides accurate, near real-time, high-resolution weather forecasts. It was developed for commercial and scientific users. In addition to weather forecasting, the product's applications include maritime and terrestrial transportation, aviation operations, precision farming, offshore oil and gas operations, and coastal hazard response support. Target commercial markets include the operational maritime and aviation communities, oil and gas providers, and recreational yachting interests. Science applications include global long-term prediction and climate change, land-cover and land-use change, and natural hazard issues. Commercial airlines have expressed interest in the product, as it can provide forecasts over remote areas. WorldWinds, Inc., is currently providing its product to commercial weather outlets.

  1. Aggregate vehicle travel forecasting model

    SciTech Connect

    Greene, D.L.; Chin, Shih-Miao; Gibson, R.

    1995-05-01

    This report describes a model for forecasting total US highway travel by all vehicle types, and its implementation in the form of a personal computer program. The model comprises a short-run, econometrically-based module for forecasting through the year 2000, as well as a structural, scenario-based longer term module for forecasting through 2030. The short-term module is driven primarily by economic variables. It includes a detailed vehicle stock model and permits the estimation of fuel use as well as vehicle travel. The longer-tenn module depends on demographic factors to a greater extent, but also on trends in key parameters such as vehicle load factors, and the dematerialization of GNP. Both passenger and freight vehicle movements are accounted for in both modules. The model has been implemented as a compiled program in the Fox-Pro database management system operating in the Windows environment.

  2. GEM: Statistical weather forecasting procedure

    NASA Technical Reports Server (NTRS)

    Miller, R. G.

    1983-01-01

    The objective of the Generalized Exponential Markov (GEM) Program was to develop a weather forecast guidance system that would: predict between 0 to 6 hours all elements in the airways observations; respond instantly to the latest observed conditions of the surface weather; process these observations at local sites on minicomputing equipment; exceed the accuracy of current persistence predictions at the shortest prediction of one hour and beyond; exceed the accuracy of current forecast model output statistics inside eight hours; and be capable of making predictions at one location for all locations where weather information is available.

  3. Acquisition forecast: Fiscal year 1995

    NASA Technical Reports Server (NTRS)

    1995-01-01

    This volume includes projections of all anticipated FY95, and beyond, NASA contract actions above $25,000 that small and small disadvantaged businesses may be able to perform under direct contract with the government or as subcontractors. The forecast consolidates anticipated procurements at each NASA center into an agencywide report, with the aim of increasing industries' advance knowledge of NASA requirements and enhancing competition in contracting. Each center forecast report is divided into three principal categories of procurement: research and development, services, and supplies and equipment.

  4. Accuracy of forecasts in strategic intelligence.

    PubMed

    Mandel, David R; Barnes, Alan

    2014-07-29

    The accuracy of 1,514 strategic intelligence forecasts abstracted from intelligence reports was assessed. The results show that both discrimination and calibration of forecasts was very good. Discrimination was better for senior (versus junior) analysts and for easier (versus harder) forecasts. Miscalibration was mainly due to underconfidence such that analysts assigned more uncertainty than needed given their high level of discrimination. Underconfidence was more pronounced for harder (versus easier) forecasts and for forecasts deemed more (versus less) important for policy decision making. Despite the observed underconfidence, there was a paucity of forecasts in the least informative 0.4-0.6 probability range. Recalibrating the forecasts substantially reduced underconfidence. The findings offer cause for tempered optimism about the accuracy of strategic intelligence forecasts and indicate that intelligence producers aim to promote informativeness while avoiding overstatement.

  5. Forecast communication through the newspaper Part 1: Framing the forecaster

    NASA Astrophysics Data System (ADS)

    Harris, Andrew J. L.

    2015-04-01

    This review is split into two parts both of which address issues of forecast communication of an environmental disaster through the newspaper during a period of crisis. The first part explores the process by which information passes from the scientist or forecaster, through the media filter, to the public. As part of this filter preference, omission, selection of data, source, quote and story, as well as placement of the same information within an individual piece or within the newspaper itself, can serve to distort the message. The result is the introduction of bias and slant—that is, the message becomes distorted so as to favor one side of the argument against another as it passes through the filter. Bias can be used to support spin or agenda setting, so that a particular emphasis becomes placed on the story which exerts an influence on the reader's judgment. The net result of the filter components is either a negative (contrary) or positive (supportive) frame. Tabloidization of the news has also resulted in the use of strong, evocative, exaggerated words, headlines and images to support a frame. I illustrate these various elements of the media filter using coverage of the air space closure due to the April 2010 eruption of Eyjafjallajökull (Iceland). Using the British press coverage of this event it is not difficult to find examples of all media filter elements, application of which resulted in bias against the forecast and forecaster. These actors then became named and blamed. Within this logic, it becomes only too easy for forecasters and scientists to be framed in a negative way through blame culture. The result is that forecast is framed in such a way so as to cause the forecaster to be blamed for all losses associated with the loss-causing event. Within the social amplification of risk framework (SARF), this can amplify a negative impression of the risk, the event and the response. However, actions can be taken to avoid such an outcome. These actions

  6. Forecasting Consumer Adoption of Information Technology and Services--Lessons from Home Video Forecasting.

    ERIC Educational Resources Information Center

    Klopfenstein, Bruce C.

    1989-01-01

    Describes research that examined the strengths and weaknesses of technological forecasting methods by analyzing forecasting studies made for home video players. The discussion covers assessments and explications of correct and incorrect forecasting assumptions, and their implications for forecasting the adoption of home information technologies…

  7. EnrollForecast for Excel: K-12 Enrollment Forecasting Program. Software & User's Guide. [Computer Diskette].

    ERIC Educational Resources Information Center

    Smith, Curtis A.

    "EnrollForecast for Excel" will generate a 5-year forecast of K-12 student enrollment. It will also work for any combination of grades between kindergarten and twelth. The forecasts can be printed as either a table or a graph. The user must provide birth history (only if forecasting kindergarten) and enrollment history information. The user also…

  8. A Delphi forecast of technology in education

    NASA Technical Reports Server (NTRS)

    Robinson, B. E.

    1973-01-01

    The results are reported of a Delphi forecast of the utilization and social impacts of large-scale educational telecommunications technology. The focus is on both forecasting methodology and educational technology. The various methods of forecasting used by futurists are analyzed from the perspective of the most appropriate method for a prognosticator of educational technology, and review and critical analysis are presented of previous forecasts and studies. Graphic responses, summarized comments, and a scenario of education in 1990 are presented.

  9. Can Business Students Forecast Their Own Grade?

    ERIC Educational Resources Information Center

    Hossain, Belayet; Tsigaris, Panagiotis

    2013-01-01

    This study examines grade expectations of two groups of business students for their final course mark. We separate students that are on average "better" forecasters on the basis of them not making significant forecast errors during the semester from those students that are poor forecasters of their final grade. We find that the better…

  10. Student Enrollment Forecasting in Georgia: Lessons Learned.

    ERIC Educational Resources Information Center

    Chan, Tak Cheung; Pool, Harbison; Davidson, Ronald

    2002-01-01

    Study of school district enrollment forecasting in Georgia finds, for example, differences in forecasting accuracy between large and small school districts, the widespread use of the Cohort Survival Technique, a lag in small school districts' use of sophisticated, computer-based enrollment forecasting models. (Contains 34 references.) (PKP)

  11. School Roll Forecasting Methods: A Review.

    ERIC Educational Resources Information Center

    Simpson, Stephen

    1987-01-01

    A review of the literature concerning local school roll forecasting describes the theoretical model common to most local education agency (LEA) forecasts, identifies a variety of issues relevant to this area of LEA planning, and suggests some opportunities for improvement in LEA school roll forecasting. (Author/CB)

  12. Enrollment Trends, Implications and Forecasting Techniques.

    ERIC Educational Resources Information Center

    Finch, Harold L.

    This paper discusses two approaches that are well adapted to school district enrollment forecasting and related planning studies. The author focuses in turn on two enrollment forecasting methods--the Analytical Simulation Approach, and the Modified Cohort Survival Approach. After briefly describing each forecasting method, he presents a short case…

  13. Seasonal Streamflow Forecasts for African Basins

    NASA Astrophysics Data System (ADS)

    Serrat-Capdevila, A.; Valdes, J. B.; Wi, S.; Roy, T.; Roberts, J. B.; Robertson, F. R.; Demaria, E. M.

    2015-12-01

    Using high resolution downscaled seasonal meteorological forecasts we present the development and evaluation of seasonal hydrologic forecasts with Stakeholder Agencies for selected African basins. The meteorological forecasts are produced using the Bias Correction and Spatial Disaggregation (BCSD) methodology applied to NMME hindcasts (North American Multi-Model Ensemble prediction system) to generate a bootstrap resampling of plausible weather forecasts from historical observational data. This set of downscaled forecasts is then used to drive hydrologic models to produce a range of forecasts with uncertainty estimates suitable for water resources planning in African pilot basins (i.e. Upper Zambezi, Mara Basin). In an effort to characterize the utility of these forecasts, we will present an evaluation of these forecast ensembles over the pilot basins, and discuss insights as to their operational applicability by regional actors. Further, these forecasts will be contrasted with those from a standard Ensemble Streamflow Prediction (ESP) approach to seasonal forecasting. The case studies presented here have been developed in the setting of the NASA SERVIR Applied Sciences Team and within the broader context of operational seasonal forecasting in Africa. These efforts are part of a dialogue with relevant planning and management agencies and institutions in Africa, which are in turn exploring how to best use uncertain forecasts for decision making.

  14. Beat the Instructor: An Introductory Forecasting Game

    ERIC Educational Resources Information Center

    Snider, Brent R.; Eliasson, Janice B.

    2013-01-01

    This teaching brief describes a 30-minute game where student groups compete in-class in an introductory time-series forecasting exercise. The students are challenged to "beat the instructor" who competes using forecasting techniques that will be subsequently taught. All forecasts are graphed prior to revealing the randomly generated…

  15. A Course in Economic Forecasting: Rationale and Content.

    ERIC Educational Resources Information Center

    Loomis, David G.; Cox, James E., Jr.

    2000-01-01

    Discusses four reasons why economic forecasting courses are important: (1) forecasting skills are in demand by businesses; (2) forecasters are in demand; (3) forecasting courses have positive externalities; (4) and forecasting provides a real-world context. Describes what should be taught in an economic forecasting course. (CMK)

  16. Operational Planning of Channel Airlift Missions Using Forecasted Demand

    DTIC Science & Technology

    2013-03-01

    9 Forecasting Techniques .............................................................................................11 Forecasting...as they are. There is also a discussion of forecasting techniques and how they are selected and forecasting with air cargo demand. Using forms of...on the airlines themselves for near term scheduling. Forecasting Techniques There are numerous regression and forecasting techniques available to

  17. Understanding and Forecasting Ethnolinguistic Vitality

    ERIC Educational Resources Information Center

    Karan, Mark E.

    2011-01-01

    Forecasting of ethnolinguistic vitality can only be done within a well-functioning descriptive and explanatory model of the dynamics of language stability and shift. It is proposed that the Perceived Benefit Model of Language Shift, used with a taxonomy of language shift motivations, provides that model. The model, based on individual language…

  18. Forecasting Enrollment: An Extrapolative Approach.

    ERIC Educational Resources Information Center

    Barenbaum, Lester; Ricci, Raymond

    1982-01-01

    An enrollment projection model designed and implemented at LaSalle College had five phases: establishing clear goals, model construction, model implementation, model estimation and validation, and using the forecast. The history of LaSalle's model and the elements in decision making are outlined. (MSE)

  19. In Brief: Forecasting meningitis threats

    NASA Astrophysics Data System (ADS)

    Showstack, Randy

    2008-12-01

    The University Corporation for Atmospheric Research (UCAR), in conjunction with a team of health and weather organizations, has launched a project to provide weather forecasts to medical officials in Africa to help reduce outbreaks of meningitis. The forecasts will enable local health care providers to target vaccination programs more effectively. In 2009, meteorologists with the National Center for Atmospheric Research, which is managed by UCAR, will begin issuing 14-day forecasts of atmospheric conditions in Ghana. Later, UCAR plans to work closely with health experts from several African countries to design and test a decision support system to provide health officials with useful meteorological information. ``By targeting forecasts in regions where meningitis is a threat, we may be able to help vulnerable populations. Ultimately, we hope to build on this project and provide information to public health programs battling weather-related diseases in other parts of the world,'' said Rajul Pandya, director of UCAR's Community Building Program. Funding for the project comes from a $900,000 grant from Google.org, the philanthropic arm of the Internet search company.

  20. Worldwide satellite market demand forecast

    NASA Technical Reports Server (NTRS)

    Bowyer, J. M.; Frankfort, M.; Steinnagel, K. M.

    1981-01-01

    The forecast is for the years 1981 - 2000 with benchmark years at 1985, 1990 and 2000. Two typs of markets are considered for this study: Hardware (worldwide total) - satellites, earth stations and control facilities (includes replacements and spares); and non-hardware (addressable by U.S. industry) - planning, launch, turnkey systems and operations. These markets were examined for the INTELSAT System (international systems and domestic and regional systems using leased transponders) and domestic and regional systems. Forecasts were determined for six worldwide regions encompassing 185 countries using actual costs for existing equipment and engineering estimates of costs for advanced systems. Most likely (conservative growth rate estimates) and optimistic (mid range growth rate estimates) scenarios were employed for arriving at the forecasts which are presented in constant 1980 U.S. dollars. The worldwide satellite market demand forecast predicts that the market between 181 and 2000 will range from $35 to $50 billion. Approximately one-half of the world market, $16 to $20 billion, will be generated in the United States.

  1. 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.

  2. Forecasting depression in bipolar disorder.

    PubMed

    Moore, Paul J; Little, Max A; McSharry, Patrick E; Geddes, John R; Goodwin, Guy M

    2012-10-01

    Bipolar disorder is characterized by recurrent episodes of mania and depression and affects about 1% of the adult population. The condition can have a major impact on an individual's ability to function and is associated with a long-term risk of suicide. In this paper, we report on the use of self-rated mood data to forecast the next week's depression ratings. The data used in the study have been collected using SMS text messaging and comprises one time series of approximately weekly mood ratings for each patient. We find a wide variation between series: some exhibit a large change in mean over the monitored period and there is a variation in correlation structure. Almost half of the time series are forecast better by unconditional mean than by persistence. Two methods are employed for forecasting: exponential smoothing and Gaussian process regression. Neither approach gives an improvement over a persistence baseline. We conclude that the depression time series from patients with bipolar disorder are very heterogeneous and that this constrains the accuracy of automated mood forecasting across the set of patients. However, the dataset is a valuable resource and work remains to be done that might result in clinically useful information and tools.

  3. Severe Weather Forecast Decision Aid

    NASA Technical Reports Server (NTRS)

    Bauman, William H., III; Wheeler, Mark

    2005-01-01

    The Applied Meteorology Unit developed a forecast tool that provides an assessment of the likelihood of local convective severe weather for the day in order to enhance protection of personnel and material assets of the 45th Space Wing Cape Canaveral Air Force Station (CCAFS), and Kennedy Space Center (KSC).

  4. Severe Weather Forecast Decision Aid

    NASA Technical Reports Server (NTRS)

    Bauman, William H., III; Wheeler, Mark M.; Short, David A.

    2005-01-01

    This report presents a 15-year climatological study of severe weather events and related severe weather atmospheric parameters. Data sources included local forecast rules, archived sounding data, Cloud-to-Ground Lightning Surveillance System (CGLSS) data, surface and upper air maps, and two severe weather event databases covering east-central Florida. The local forecast rules were used to set threat assessment thresholds for stability parameters that were derived from the sounding data. The severe weather events databases were used to identify days with reported severe weather and the CGLSS data was used to differentiate between lightning and non-lightning days. These data sets provided the foundation for analyzing the stability parameters and synoptic patterns that were used to develop an objective tool to aid in forecasting severe weather events. The period of record for the analysis was May - September, 1989 - 2003. The results indicate that there are certain synoptic patterns more prevalent on days with severe weather and some of the stability parameters are better predictors of severe weather days based on locally tuned threat values. The results also revealed the stability parameters that did not display any skill related to severe weather days. An interactive web-based Severe Weather Decision Aid was developed to assist the duty forecaster by providing a level of objective guidance based on the analysis of the stability parameters, CGLSS data, and synoptic-scale dynamics. The tool will be tested and evaluated during the 2005 warm season.

  5. A Wind Forecasting System for Energy Application

    NASA Astrophysics Data System (ADS)

    Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

    2010-05-01

    Accurate forecasting of available energy is crucial for the efficient management and use of wind power in the national power grid. With energy output critically dependent upon wind strength there is a need to reduce the errors associated wind forecasting. The objective of this research is to get the best possible wind forecasts for the wind energy industry. To achieve this goal, three methods are being applied. First, a mesoscale numerical weather prediction (NWP) model called WRF (Weather Research and Forecasting) is being used to predict wind values over Ireland. Currently, a gird resolution of 10km is used and higher model resolutions are being evaluated to establish whether they are economically viable given the forecast skill improvement they produce. Second, the WRF model is being used in conjunction with ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble forecasts to produce a probabilistic weather forecasting product. Due to the chaotic nature of the atmosphere, a single, deterministic weather forecast can only have limited skill. The ECMWF ensemble methods produce an ensemble of 51 global forecasts, twice a day, by perturbing initial conditions of a 'control' forecast which is the best estimate of the initial state of the atmosphere. This method provides an indication of the reliability of the forecast and a quantitative basis for probabilistic forecasting. The limitation of ensemble forecasting lies in the fact that the perturbed model runs behave differently under different weather patterns and each model run is equally likely to be closest to the observed weather situation. Models have biases, and involve assumptions about physical processes and forcing factors such as underlying topography. Third, Bayesian Model Averaging (BMA) is being applied to the output from the ensemble forecasts in order to statistically post-process the results and achieve a better wind forecasting system. BMA is a promising technique that will offer calibrated

  6. UK physics council sees grim future

    NASA Astrophysics Data System (ADS)

    Brumfiel, Geoff

    2009-11-01

    Britain's high-energy physicists and astronomers are bracing themselves for budget cuts. The Science and Technology Facilities Council (STFC), which funds the United Kingdom's astronomy, particle- and nuclear-physics communities, is short by roughly £40 million (US$66 million) in its annual £450-million cash budget.

  7. Grim Job Talks Are a Buzz Kill

    ERIC Educational Resources Information Center

    Shapiro, Dan

    2012-01-01

    This article takes a look at five mistakes that candidates should avoid making during their research presentations. These mistakes are the following: (1) they didn't do any research on the norms of the campus culture; (2) they presented a single, well-thought-out project that had no future; (3) they didn't use the opportunity to demonstrate their…

  8. Environmental forecasting and turbulence modeling

    NASA Astrophysics Data System (ADS)

    Hunt, J. C. R.

    This review describes the fundamental assumptions and current methodologies of the two main kinds of environmental forecast; the first is valid for a limited period of time into the future and over a limited space-time ‘target’, and is largely determined by the initial and preceding state of the environment, such as the weather or pollution levels, up to the time when the forecast is issued and by its state at the edges of the region being considered; the second kind provides statistical information over long periods of time and/or over large space-time targets, so that they only depend on the statistical averages of the initial and ‘edge’ conditions. Environmental forecasts depend on the various ways that models are constructed. These range from those based on the ‘reductionist’ methodology (i.e., the combination of separate, scientifically based, models for the relevant processes) to those based on statistical methodologies, using a mixture of data and scientifically based empirical modeling. These are, as a rule, focused on specific quantities required for the forecast. The persistence and predictability of events associated with environmental and turbulent flows and the reasons for variation in the accuracy of their forecasts (of the first and second kinds) are now better understood and better modeled. This has partly resulted from using analogous results of disordered chaotic systems, and using the techniques of calculating ensembles of realizations, ideally involving several different models, so as to incorporate in the probabilistic forecasts a wider range of possible events. The rationale for such an approach needs to be developed. However, other insights have resulted from the recognition of the ordered, though randomly occurring, nature of the persistent motions in these flows, whose scales range from those of synoptic weather patterns (whether storms or ‘blocked’ anticyclones) to small scale vortices. These eigen states can be predicted

  9. Short-term ensemble streamflow forecasting using operationally-produced single-valued streamflow forecasts

    NASA Astrophysics Data System (ADS)

    Regonda, Satish; Seo, Dong-Jun; Lawrence, Bill

    2010-05-01

    We present a statistical procedure that generates short-term streamflow ensemble forecasts from single-valued, or deterministic, forecasts operationally produced by the National Weather Service (NWS) River Forecast Centers (RFC). The resulting ensemble forecast provides an estimate of the uncertainty in the single-valued forecast to aid risk-based decision making by the emergency managers and by the users of the forecast products and services. The single-valued forecasts are produced at a 6-hr time step for 5 days into the future, and reflect single-valued short-term quantitative precipitation and temperature forecasts (QPF, QTF) and various run-time modifications (MOD), or manual data assimilation, by human forecasters to reduce various sources of error in the end-to-end forecast process. The proposed procedure generates 5 day-ahead ensemble traces of streamflow from a very parsimonious approximation of the conditional multivariate probability distribution of future streamflow given the single-valued streamflow forecasts, QPF and recent streamflow observations. For parameter estimation and evaluation, we used a 10-year archive of the single-valued river stage forecasts for six forecast points in Oklahoma produced operationally by the Arkansas-Red River Basin River Forecast Center (ABRFC). To evaluate the procedure, we carried out dependent and leave-one-year-out cross validation. The resulting ensemble hindcasts are then verified using the Ensemble Verification System (EVS) developed at the NWS Office of Hydrologic Development (OHD).

  10. Airfreight forecasting methodology and results

    NASA Technical Reports Server (NTRS)

    1978-01-01

    A series of econometric behavioral equations was developed to explain and forecast the evolution of airfreight traffic demand for the total U.S. domestic airfreight system, the total U.S. international airfreight system, and the total scheduled international cargo traffic carried by the top 44 foreign airlines. The basic explanatory variables used in these macromodels were the real gross national products of the countries involved and a measure of relative transportation costs. The results of the econometric analysis reveal that the models explain more than 99 percent of the historical evolution of freight traffic. The long term traffic forecasts generated with these models are based on scenarios of the likely economic outlook in the United States and 31 major foreign countries.

  11. Mesoscale model forecast verification during monsoon 2008

    NASA Astrophysics Data System (ADS)

    Ashrit, Raghavendra; Mohandas, Saji

    2010-08-01

    There have been very few mesoscale modelling studies of the Indian monsoon, with focus on the verification and intercomparison of the operational real time forecasts. With the exception of Das et al (2008), most of the studies in the literature are either the case studies of tropical cyclones and thunderstorms or the sensitivity studies involving physical parameterization or climate simulation studies. Almost all the studies are based on either National Center for Environmental Prediction (NCEP), USA, final analysis fields (NCEP FNL) or the reanalysis data used as initial and lateral boundary conditions for driving the mesoscale model. Here we present a mesoscale model forecast verification and intercomparison study over India involving three mesoscale models: (i) the Weather Research and Forecast (WRF) model developed at the National Center for Atmospheric Research (NCAR), USA, (ii) the MM5 model developed by NCAR, and (iii) the Eta model of the NCEP, USA. The analysis is carried out for the monsoon season, June to September 2008. This study is unique since it is based entirely on the real time global model forecasts of the National Centre for Medium Range Weather Forecasting (NCMRWF) T254 global analysis and forecast system. Based on the evaluation and intercomparison of the mesoscale model forecasts, we recommend the best model for operational real-time forecasts over the Indian region. Although the forecast mean 850 hPa circulation shows realistic monsoon flow and the monsoon trough, the systematic errors over the Arabian Sea indicate an easterly bias to the north (of mean flow) and westerly bias to the south (of mean flow). This suggests that the forecasts feature a southward shift in the monsoon current. The systematic error in the 850 hPa temperature indicates that largely the WRF model forecasts feature warm bias and the MM5 model forecasts feature cold bias. Features common to all the three models include warm bias over northwest India and cold bias over

  12. Forecast of iceberg ensemble drift

    SciTech Connect

    El-Tahan, M.S.; El-Tahan, H.W.; Venkatesh, S.

    1983-05-01

    The objectives of the study are to gain a better understanding of the characteristics of iceberg motion and the factors controlling iceberg drift, and to develop an iceberg ensemble drift forecast system to be operated by the Canadian Atmospheric Environment Service. An extensive review of field and theoretical studies on iceberg behaviour, and the factors controlling iceberg motion has been carried out. Long term and short term behaviour of icebergs are critically examined. A quantitative assessment of the effects of the factors controlling iceberg motion is presented. The study indicated that wind and currents are the primary driving forces. Coriolis Force and ocean surface slope also have significant effects. As for waves, only the higher waves have a significant effect. Iceberg drift is also affected by iceberg size characteristics. Based on the findings of the study a comprehensive computerized forecast system to predict the drift of iceberg ensembles off Canada's east coast has been designed. The expected accuracy of the forecast system is discussed and recommendations are made for future improvements to the system.

  13. Assessment of reservoir system variable forecasts

    NASA Astrophysics Data System (ADS)

    Kistenmacher, Martin; Georgakakos, Aris P.

    2015-05-01

    Forecast ensembles are a convenient means to model water resources uncertainties and to inform planning and management processes. For multipurpose reservoir systems, forecast types include (i) forecasts of upcoming inflows and (ii) forecasts of system variables and outputs such as reservoir levels, releases, flood damage risks, hydropower production, water supply withdrawals, water quality conditions, navigation opportunities, and environmental flows, among others. Forecasts of system variables and outputs are conditional on forecasted inflows as well as on specific management policies and can provide useful information for decision-making processes. Unlike inflow forecasts (in ensemble or other forms), which have been the subject of many previous studies, reservoir system variable and output forecasts are not formally assessed in water resources management theory or practice. This article addresses this gap and develops methods to rectify potential reservoir system forecast inconsistencies and improve the quality of management-relevant information provided to stakeholders and managers. The overarching conclusion is that system variable and output forecast consistency is critical for robust reservoir management and needs to be routinely assessed for any management model used to inform planning and management processes. The above are demonstrated through an application from the Sacramento-American-San Joaquin reservoir system in northern California.

  14. Using Forecasting to Teach Weather Science

    NASA Astrophysics Data System (ADS)

    Tsubota, Y.; Takahashi, T.

    2009-09-01

    Weather affects our lives and hence, is a popular topic in daily conversations and in the media. Therefore, it is not only important to teach weather, but is also a good idea to use 'weather' as a topic in science teaching. Science education has two main objectives: to acquire scientific concepts and methods. Weather forecasting is an adequate theme to teach scientific methods because it is dependent on observation. However, it is not easy to forecast weather using only temporal observation. We need to know the tendency of 'weather change' via consecutive and/or continuous weather observation. Students will acquire scientific-observation skills through weather observation. Data-processing skills would be enhanced through a weather-forecasting contest. A contest should be announced within 5 days of school events, such as a school excursion and field day. Students submit their own weather forecast by gathering weather information through the internet, news paper and so on. A weather-forecasting contest compels the student to observe the weather more often. We currently have some different weather forecasts. For example, American weather-related companies such as ACCU weather and Weather Channel provide weather forecast for the many locations all over the world. Comparing these weather forecasting with actual weather, participants such as students could evaluate the differences between forecasted and actual temperatures. Participants will judge the best weather forecast based on the magnitude of the difference. Also, participants evaluate the 'hitting ratio' of each weather forecast. Students can learn elementary statistics by comparing various weather forecasts. We have developed our weather web-site that provides our own weather forecasting and observation. Students acquire science skills using our weather web-site. We will report our lessen plans and explain our weather web-site.

  15. Forecasting Space Weather from Magnetograms

    NASA Technical Reports Server (NTRS)

    Falconer, David A.; Moore, Ronald L.; Barghouty, Abdulnasser F.; Khazanov, Igor

    2012-01-01

    Large flares and fast CMEs are the drivers of the most severe space weather including Solar Energetic Particle Events (SEP Events). Large flares and their co-produced CMEs are powered by the explosive release of free magnetic energy stored in non-potential magnetic fields of sunspot active regions. The free energy is stored in and released from the low-beta regime of the active region s magnetic field above the photosphere, in the chromosphere and low corona. From our work over the past decade and from similar work of several other groups, it is now well established that (1) a proxy of the free magnetic energy stored above the photosphere can be measured from photospheric magnetograms, maps of the measured field in the photosphere, and (2) an active region s rate of production of major CME/flare eruptions in the coming day or so is strongly correlated with its present measured value of the free-energy proxy. These results have led us to use the large database of SOHO/MDI full-disk magnetograms spanning Solar Cycle 23 to obtain empirical forecasting curves that from an active region s present measured value of the free-energy proxy give the active region s expected rates of production of major flares, CMEs, fast CMEs, and SEP Events in the coming day or so (Falconer et al 2011, Space Weather, 9, S04003). For each type of event, the expected rate is readily converted to the chance that the active region will produce such an event in any given forward time window of a day or so. If the chance is small enough (e.g. <5%), the forecast is All Clear for that type of event. We will present these forecasting curves and demonstrate the accuracy of their forecasts. In addition, we will show that the forecasts for major flares and fast CMEs can be made significantly more accurate by taking into account not only the value of the free energy proxy but also the active region s recent productivity of major flares; specifically, whether the active region has produced a major flare

  16. Skillful seasonal forecasts of Arctic sea ice retreat and advance dates in a dynamical forecast system

    NASA Astrophysics Data System (ADS)

    Sigmond, M.; Reader, M. C.; Flato, G. M.; Merryfield, W. J.; Tivy, A.

    2016-12-01

    The need for skillful seasonal forecasts of Arctic sea ice is rapidly increasing. Technology to perform such forecasts with coupled atmosphere-ocean-sea ice systems has only recently become available, with previous skill evaluations mainly limited to area-integrated quantities. Here we show, based on a large set of retrospective ensemble model forecasts, that a dynamical forecast system produces skillful seasonal forecasts of local sea ice retreat and advance dates - variables that are of great interest to a wide range of end users. Advance dates can generally be skillfully predicted at longer lead times ( 5 months on average) than retreat dates ( 3 months). The skill of retreat date forecasts mainly stems from persistence of initial sea ice anomalies, whereas advance date forecasts benefit from longer time scale and more predictable variability in ocean temperatures. These results suggest that further investments in the development of dynamical seasonal forecast systems may result in significant socioeconomic benefits.

  17. How rolling forecasting facilitates dynamic, agile planning.

    PubMed

    Miller, Debra; Allen, Michael; Schnittger, Stephanie; Hackman, Theresa

    2013-11-01

    Rolling forecasting may be used to replace or supplement the annual budget process. The rolling forecast typically builds on the organization's strategic financial plan, focusing on the first three years of plan projections and comparing the strategic financial plan assumptions with the organization's expected trajectory. Leaders can then identify and respond to gaps between the rolling forecast and the strategic financial plan on an ongoing basis.

  18. Bias correcting precipitation forecasts to improve the skill of seasonal streamflow forecasts

    NASA Astrophysics Data System (ADS)

    Crochemore, Louise; Ramos, Maria-Helena; Pappenberger, Florian

    2016-09-01

    Meteorological centres make sustained efforts to provide seasonal forecasts that are increasingly skilful, which has the potential to benefit streamflow forecasting. Seasonal streamflow forecasts can help to take anticipatory measures for a range of applications, such as water supply or hydropower reservoir operation and drought risk management. This study assesses the skill of seasonal precipitation and streamflow forecasts in France to provide insights into the way bias correcting precipitation forecasts can improve the skill of streamflow forecasts at extended lead times. We apply eight variants of bias correction approaches to the precipitation forecasts prior to generating the streamflow forecasts. The approaches are based on the linear scaling and the distribution mapping methods. A daily hydrological model is applied at the catchment scale to transform precipitation into streamflow. We then evaluate the skill of raw (without bias correction) and bias-corrected precipitation and streamflow ensemble forecasts in 16 catchments in France. The skill of the ensemble forecasts is assessed in reliability, sharpness, accuracy and overall performance. A reference prediction system, based on historical observed precipitation and catchment initial conditions at the time of forecast (i.e. ESP method) is used as benchmark in the computation of the skill. The results show that, in most catchments, raw seasonal precipitation and streamflow forecasts are often more skilful than the conventional ESP method in terms of sharpness. However, they are not significantly better in terms of reliability. Forecast skill is generally improved when applying bias correction. Two bias correction methods show the best performance for the studied catchments, each method being more successful in improving specific attributes of the forecasts: the simple linear scaling of monthly values contributes mainly to increasing forecast sharpness and accuracy, while the empirical distribution mapping

  19. Intermediate-term forecasting of aftershocks from an early aftershock sequence: Bayesian and ensemble forecasting approaches

    NASA Astrophysics Data System (ADS)

    Omi, Takahiro; Ogata, Yosihiko; Hirata, Yoshito; Aihara, Kazuyuki

    2015-04-01

    Because aftershock occurrences can cause significant seismic risks for a considerable time after the main shock, prospective forecasting of the intermediate-term aftershock activity as soon as possible is important. The epidemic-type aftershock sequence (ETAS) model with the maximum likelihood estimate effectively reproduces general aftershock activity including secondary or higher-order aftershocks and can be employed for the forecasting. However, because we cannot always expect the accurate parameter estimation from incomplete early aftershock data where many events are missing, such forecasting using only a single estimated parameter set (plug-in forecasting) can frequently perform poorly. Therefore, we here propose Bayesian forecasting that combines the forecasts by the ETAS model with various probable parameter sets given the data. By conducting forecasting tests of 1 month period aftershocks based on the first 1 day data after the main shock as an example of the early intermediate-term forecasting, we show that the Bayesian forecasting performs better than the plug-in forecasting on average in terms of the log-likelihood score. Furthermore, to improve forecasting of large aftershocks, we apply a nonparametric (NP) model using magnitude data during the learning period and compare its forecasting performance with that of the Gutenberg-Richter (G-R) formula. We show that the NP forecast performs better than the G-R formula in some cases but worse in other cases. Therefore, robust forecasting can be obtained by employing an ensemble forecast that combines the two complementary forecasts. Our proposed method is useful for a stable unbiased intermediate-term assessment of aftershock probabilities.

  20. Assessing probabilistic forecasts of volcanic eruption onsets

    NASA Astrophysics Data System (ADS)

    Bebbington, Mark S.

    2013-12-01

    A method for assessing prospectively the quality of a suite of eruption forecasts is proposed. Any forecast of the next eruption onset from a polygenetic volcano can be converted into a probability distribution for the elapsed time since the forecast is made. This probability distribution, which effectively becomes a statistical P value when the observation is "plugged in," will thus itself have a uniform distribution under the null hypothesis that the forecast correctly describes the process. Given sufficient realizations, which may be on the same or different volcanoes, we can use standard statistical tests, such as the Kolmogorov-Smirnov test, to determine if the forecasts are consistent with the model(s). The use of the Kolmogorov-Smirnov test enables currently open forecasts to be included via the Kaplan-Meier product-limit estimator. While consistent underestimates (or overestimates) of the repose length will result in a median greater (or less) than , the method also assesses whether the method assigns the correct degree of aleatory variability to the forecast. Note that it is possible for the forecasts to be less precise than claimed. This would be indicated by the median of the sample being around , but the quartiles being well outside the interval, for example. The method is illustrated on the author's library of forecasts dating back to 1994, including renewal models and other point processes, on a gallery of approximately 20 volcanoes including Etna, Aso, and Ruapehu.

  1. Optimized Flood Forecasts Using a Statistical Enemble

    NASA Astrophysics Data System (ADS)

    Silver, Micha; Fredj, Erick

    2016-04-01

    The method presented here assembles an optimized flood forecast from a set of consecutive WRF-Hydro simulations by applying coefficients which we derive from straightforward statistical procedures. Several government and research institutions that produce climate data offer ensemble forecasts, which merge predictions from different models to gain a more accurate fit to observed data. Existing ensemble forecasts present climate and weather predictions only. In this research we propose a novel approach to constructing hydrological ensembles for flood forecasting. The ensemble flood forecast is created by combining predictions from the same model, but initiated at different times. An operative flood forecasting system, run by the Israeli Hydrological Service, produces flood forecasts twice daily with a 72 hour forecast period. By collating the output from consecutive simulation runs we have access to multiple overlapping forecasts. We then apply two statistical procedures to blend these consecutive forecasts, resulting in a very close fit to observed flood runoff. We first employ cross-correlation with a time lag to determine a time shift for each of the original, consecutive forecasts. This shift corrects for two possible sources of error: slow or fast moving weather fronts in the base climate data; and mis-calibrations of the WRF-Hydro model in determining the rate of flow of surface runoff and in channels. We apply this time shift to all consecutive forecasts, then run a linear regression with the observed runoff data as the dependent variable and all shifted forecasts as the predictor variables. The solution to the linear regression equation is a set of coefficients that corrects the amplitude errors in the forecasts. These resulting regression coefficients are then applied to the consecutive forecasts producing a statistical ensemble which, by design, closely matches the observed runoff. After performing this procedure over many storm events in the Negev region

  2. Visualization of ocean forecast in BYTHOS

    NASA Astrophysics Data System (ADS)

    Zhuk, E.; Zodiatis, G.; Nikolaidis, A.; Stylianou, S.; Karaolia, A.

    2016-08-01

    The Cyprus Oceanography Center has been constantly searching for new ideas for developing and implementing innovative methods and new developments concerning the use of Information Systems in Oceanography, to suit both the Center's monitoring and forecasting products. Within the frame of this scope two major online managing and visualizing data systems have been developed and utilized, those of CYCOFOS and BYTHOS. The Cyprus Coastal Ocean Forecasting and Observing System - CYCOFOS provides a variety of operational predictions such as ultra high, high and medium resolution ocean forecasts in the Levantine Basin, offshore and coastal sea state forecasts in the Mediterranean and Black Sea, tide forecasting in the Mediterranean, ocean remote sensing in the Eastern Mediterranean and coastal and offshore monitoring. As a rich internet application, BYTHOS enables scientists to search, visualize and download oceanographic data online and in real time. The recent improving of BYTHOS system is the extension with access and visualization of CYCOFOS data and overlay forecast fields and observing data. The CYCOFOS data are stored at OPENDAP Server in netCDF format. To search, process and visualize it the php and python scripts were developed. Data visualization is achieved through Mapserver. The BYTHOS forecast access interface allows to search necessary forecasting field by recognizing type, parameter, region, level and time. Also it provides opportunity to overlay different forecast and observing data that can be used for complex analyze of sea basin aspects.

  3. Combining forecast weights: Why and how?

    NASA Astrophysics Data System (ADS)

    Yin, Yip Chee; Kok-Haur, Ng; Hock-Eam, Lim

    2012-09-01

    This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions, forecast weight averaging can lower the mean squared forecast error obtained from model averaging. In addition, we show that in a linear and homoskedastic environment, this superior predictive ability of forecast weight averaging holds true irrespective whether the coefficients are tested by t statistic or z statistic provided the significant level is within the 10% range. By theoretical proofs and simulation study, we have shown that model averaging like, variance model averaging, simple model averaging and standard error model averaging, each produces mean squared forecast error larger than that of forecast weight averaging. Finally, this result also holds true marginally when applied to business and economic empirical data sets, Gross Domestic Product (GDP growth rate), Consumer Price Index (CPI) and Average Lending Rate (ALR) of Malaysia.

  4. The Economic Value of Air Quality Forecasting

    NASA Astrophysics Data System (ADS)

    Anderson-Sumo, Tasha

    Both long-term and daily air quality forecasts provide an essential component to human health and impact costs. According the American Lung Association, the estimated current annual cost of air pollution related illness in the United States, adjusted for inflation (3% per year), is approximately $152 billion. Many of the risks such as hospital visits and morality are associated with poor air quality days (where the Air Quality Index is greater than 100). Groups such as sensitive groups become more susceptible to the resulting conditions and more accurate forecasts would help to take more appropriate precautions. This research focuses on evaluating the utility of air quality forecasting in terms of its potential impacts by building on air quality forecasting and economical metrics. Our analysis includes data collected during the summertime ozone seasons between 2010 and 2012 from air quality models for the Washington, DC/Baltimore, MD region. The metrics that are relevant to our analysis include: (1) The number of times that a high ozone or particulate matter (PM) episode is correctly forecasted, (2) the number of times that high ozone or PM episode is forecasted when it does not occur and (3) the number of times when the air quality forecast predicts a cleaner air episode when the air was observed to have high ozone or PM. Our collection of data included available air quality model forecasts of ozone and particulate matter data from the U.S. Environmental Protection Agency (EPA)'s AIRNOW as well as observational data of ozone and particulate matter from Clean Air Partners. We evaluated the performance of the air quality forecasts with that of the observational data and found that the forecast models perform well for the Baltimore/Washington region and the time interval observed. We estimate the potential amount for the Baltimore/Washington region accrues to a savings of up to 5,905 lives and 5.9 billion dollars per year. This total assumes perfect compliance with

  5. Geothermal wells: a forecast of drilling activity

    SciTech Connect

    Brown, G.L.; Mansure, A.J.; Miewald, J.N.

    1981-07-01

    Numbers and problems for geothermal wells expected to be drilled in the United States between 1981 and 2000 AD are forecasted. The 3800 wells forecasted for major electric power projects (totaling 6 GWe of capacity) are categorized by type (production, etc.), and by location (The Geysers, etc.). 6000 wells are forecasted for direct heat projects (totaling 0.02 Quads per year). Equations are developed for forecasting the number of wells, and data is presented. Drilling and completion problems in The Geysers, The Imperial Valley, Roosevelt Hot Springs, the Valles Caldera, northern Nevada, Klamath Falls, Reno, Alaska, and Pagosa Springs are discussed. Likely areas for near term direct heat projects are identified.

  6. Wheat yield forecasts using LANDSAT data

    NASA Technical Reports Server (NTRS)

    Colwell, J. E.; Rice, D. P.; Nalepka, R. F.

    1977-01-01

    Several considerations of winter wheat yield prediction using LANDSAT data were discussed. In addition, a simple technique which permits direct early season forecasts of wheat production was described.

  7. Mental Models of Software Forecasting

    NASA Technical Reports Server (NTRS)

    Hihn, J.; Griesel, A.; Bruno, K.; Fouser, T.; Tausworthe, R.

    1993-01-01

    The majority of software engineers resist the use of the currently available cost models. One problem is that the mathematical and statistical models that are currently available do not correspond with the mental models of the software engineers. In an earlier JPL funded study (Hihn and Habib-agahi, 1991) it was found that software engineers prefer to use analogical or analogy-like techniques to derive size and cost estimates, whereas curren CER's hide any analogy in the regression equations. In addition, the currently available models depend upon information which is not available during early planning when the most important forecasts must be made.

  8. National Severe Storms Forecast Center

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The principal mission of the National Severe Storms Forecast Center (NSSFC) is to maintain a continuous watch of weather developments that are capable of producing severe local storms, including tornadoes, and to prepare and issue messages designated as either Weather Outlooks or Tornado or Severe Thunderstorm Watches for dissemination to the public and aviation services. In addition to its assigned responsibility at the national level, the NSSFC is involved in a number of programs at the regional and local levels. Subsequent subsections and paragraphs describe the NSSFC, its users, inputs, outputs, interfaces, capabilities, workload, problem areas, and future plans in more detail.

  9. Forecast Mekong: navigating changing waters

    USGS Publications Warehouse

    Powell, Janine

    2011-01-01

    The U.S. Geological Survey (USGS) is using research and data from the Mekong River Delta in Southeast Asia to compare restoration, conservation, and management efforts there with those done in other major river deltas, such as the Mississippi River Delta in the United States. The project provides a forum to engage regional partners in the Mekong Basin countries to share data and support local research efforts. Ultimately, Forecast Mekong will lead to more informed decisions about how to make the Mekong and Mississippi Deltas resilient in the face of climate change, economic stresses, and other impacts.

  10. Earthquake Scaling, Simulation and Forecasting

    NASA Astrophysics Data System (ADS)

    Sachs, Michael Karl

    Earthquakes are among the most devastating natural events faced by society. In 2011, just two events, the magnitude 6.3 earthquake in Christcurch New Zealand on February 22, and the magnitude 9.0 Tohoku earthquake off the coast of Japan on March 11, caused a combined total of $226 billion in economic losses. Over the last decade, 791,721 deaths were caused by earthquakes. Yet, despite their impact, our ability to accurately predict when earthquakes will occur is limited. This is due, in large part, to the fact that the fault systems that produce earthquakes are non-linear. The result being that very small differences in the systems now result in very big differences in the future, making forecasting difficult. In spite of this, there are patterns that exist in earthquake data. These patterns are often in the form of frequency-magnitude scaling relations that relate the number of smaller events observed to the number of larger events observed. In many cases these scaling relations show consistent behavior over a wide range of scales. This consistency forms the basis of most forecasting techniques. However, the utility of these scaling relations is limited by the size of the earthquake catalogs which, especially in the case of large events, are fairly small and limited to a few 100 years of events. In this dissertation I discuss three areas of earthquake science. The first is an overview of scaling behavior in a variety of complex systems, both models and natural systems. The focus of this area is to understand how this scaling behavior breaks down. The second is a description of the development and testing of an earthquake simulator called Virtual California designed to extend the observed catalog of earthquakes in California. This simulator uses novel techniques borrowed from statistical physics to enable the modeling of large fault systems over long periods of time. The third is an evaluation of existing earthquake forecasts, which focuses on the Regional

  11. Forecasting Influenza Epidemics in Hong Kong.

    PubMed

    Yang, Wan; Cowling, Benjamin J; Lau, Eric H Y; Shaman, Jeffrey

    2015-07-01

    Recent advances in mathematical modeling and inference methodologies have enabled development of systems capable of forecasting seasonal influenza epidemics in temperate regions in real-time. However, in subtropical and tropical regions, influenza epidemics can occur throughout the year, making routine forecast of influenza more challenging. Here we develop and report forecast systems that are able to predict irregular non-seasonal influenza epidemics, using either the ensemble adjustment Kalman filter or a modified particle filter in conjunction with a susceptible-infected-recovered (SIR) model. We applied these model-filter systems to retrospectively forecast influenza epidemics in Hong Kong from January 1998 to December 2013, including the 2009 pandemic. The forecast systems were able to forecast both the peak timing and peak magnitude for 44 epidemics in 16 years caused by individual influenza strains (i.e., seasonal influenza A(H1N1), pandemic A(H1N1), A(H3N2), and B), as well as 19 aggregate epidemics caused by one or more of these influenza strains. Average forecast accuracies were 37% (for both peak timing and magnitude) at 1-3 week leads, and 51% (peak timing) and 50% (peak magnitude) at 0 lead. Forecast accuracy increased as the spread of a given forecast ensemble decreased; the forecast accuracy for peak timing (peak magnitude) increased up to 43% (45%) for H1N1, 93% (89%) for H3N2, and 53% (68%) for influenza B at 1-3 week leads. These findings suggest that accurate forecasts can be made at least 3 weeks in advance for subtropical and tropical regions.

  12. Modeled Forecasts of Dengue Fever in San Juan, Puerto Rico Using NASA Satellite Enhanced Weather Forecasts

    NASA Astrophysics Data System (ADS)

    Morin, C.; Quattrochi, D. A.; Zavodsky, B.; Case, J.

    2015-12-01

    Dengue fever (DF) is an important mosquito transmitted disease that is strongly influenced by meteorological and environmental conditions. Recent research has focused on forecasting DF case numbers based on meteorological data. However, these forecasting tools have generally relied on empirical models that require long DF time series to train. Additionally, their accuracy has been tested retrospectively, using past meteorological data. Consequently, the operational utility of the forecasts are still in question because the error associated with weather and climate forecasts are not reflected in the results. Using up-to-date weekly dengue case numbers for model parameterization and weather forecast data as meteorological input, we produced weekly forecasts of DF cases in San Juan, Puerto Rico. Each week, the past weeks' case counts were used to re-parameterize a process-based DF model driven with updated weather forecast data to generate forecasts of DF case numbers. Real-time weather forecast data was produced using the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) system enhanced using additional high-resolution NASA satellite data. This methodology was conducted in a weekly iterative process with each DF forecast being evaluated using county-level DF cases reported by the Puerto Rico Department of Health. The one week DF forecasts were accurate especially considering the two sources of model error. First, weather forecasts were sometimes inaccurate and generally produced lower than observed temperatures. Second, the DF model was often overly influenced by the previous weeks DF case numbers, though this phenomenon could be lessened by increasing the number of simulations included in the forecast. Although these results are promising, we would like to develop a methodology to produce longer range forecasts so that public health workers can better prepare for dengue epidemics.

  13. [Population forecasts for the Netherlands, 1986-2035].

    PubMed

    Cruijsen, H

    1987-02-01

    Results of the 1986 official population forecasts for the Netherlands are presented, and the assumptions made in their preparation are described. Comparisons are made with forecasts for 1985. Three alternative variations of the forecasts are included. (SUMMARY IN ENG)

  14. 48 CFR 232.072-3 - Cash flow forecasts.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... problems. (c) Single or one-time cash flow forecasts are of limited forecasting power. As such, they should... by comparing a series of previous actual cash flows with the corresponding forecasts and...

  15. Streamflow forecasting using functional regression

    NASA Astrophysics Data System (ADS)

    Masselot, Pierre; Dabo-Niang, Sophie; Chebana, Fateh; Ouarda, Taha B. M. J.

    2016-07-01

    Streamflow, as a natural phenomenon, is continuous in time and so are the meteorological variables which influence its variability. In practice, it can be of interest to forecast the whole flow curve instead of points (daily or hourly). To this end, this paper introduces the functional linear models and adapts it to hydrological forecasting. More precisely, functional linear models are regression models based on curves instead of single values. They allow to consider the whole process instead of a limited number of time points or features. We apply these models to analyse the flow volume and the whole streamflow curve during a given period by using precipitations curves. The functional model is shown to lead to encouraging results. The potential of functional linear models to detect special features that would have been hard to see otherwise is pointed out. The functional model is also compared to the artificial neural network approach and the advantages and disadvantages of both models are discussed. Finally, future research directions involving the functional model in hydrology are presented.

  16. Phantosmia as a meteorological forecaster

    NASA Astrophysics Data System (ADS)

    Aiello, S. R.; Hirsch, A. R.

    2013-09-01

    In normosmics, olfactory ability has been found to vary with ambient humidity, barometric pressure, and season. While hallucinated sensations of phantom pain associated with changes in weather have been described, a linkage to chemosensory hallucinations has heretofore not been reported. A 64-year-old white male with Parkinson's disease presents with 5 years of phantosmia of a smoky burnt wood which changed to onion-gas and then to a noxious skunk-onion excrement odor. Absent upon waking it increases over the day and persists for hours. When severe, there appears a phantom taste with the same qualities as the odor. It is exacerbated by factors that manipulate intranasal pressure, such as coughing. When eating or sniffing, the actual flavors replace the phantosmia. Since onset, he noted the intensity and frequency of the phantosmia forecasted the weather. Two to 3 h before a storm, the phantosmia intensifies from a level 0 to a 7-10, which persists through the entire thunderstorm. Twenty years prior, he reported the ability to forecast the weather, based on pain in a torn meniscus, which vanished after surgical repair. Extensive olfactory testing demonstrates underlying hyposmia. Possible mechanisms for such chemosensory-meteorological linkage includes: air pressure induced synesthesia, disinhibition of spontaneous olfactory discharge, exacerbation of ectopic discharge, affect mediated somatic sensory amplification, and misattribution error with expectation and recall bias. This is the first reported case of weather-induced exacerbation of phantosmia. Further investigation of the connection between chemosensory complaints and ambient weather is warranted.

  17. Chesapeake Bay hypoxic volume forecasts and results

    USGS Publications Warehouse

    Scavia, Donald; Evans, Mary Anne

    2013-01-01

    The 2013 Forecast - Given the average Jan-May 2013 total nitrogen load of 162,028 kg/day, this summer’s hypoxia volume forecast is 6.1 km3, slightly smaller than average size for the period of record and almost the same as 2012. The late July 2013 measured volume was 6.92 km3.

  18. Methods and Techniques of Revenue Forecasting.

    ERIC Educational Resources Information Center

    Caruthers, J. Kent; Wentworth, Cathi L.

    1997-01-01

    Revenue forecasting is the critical first step in most college and university budget-planning processes. While it seems a straightforward exercise, effective forecasting requires consideration of a number of interacting internal and external variables, including demographic trends, economic conditions, and broad social priorities. The challenge…

  19. Toward a Marine Ecological Forecasting System

    DTIC Science & Technology

    2010-06-01

    coral bleaching , living resource distribution, and pathogen progression). An operational ecological forecasting system depends upon the assimilation of...space scales (e.g., harmful algal blooms, dissolved oxygen concentration (hypoxia), water quality/beach closures, coral bleaching , living resource...advance. Two beaches in Lake Michigan have been selected for initial implementation. Forecasting Coral Bleaching in relation to Ocean Temperatures

  20. Climate forecasts for corn producer decision making

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Corn is the most widely grown crop in the Americas, with annual production in the United States of approximately 332 million metric tons. Improved climate forecasts, together with climate-related decision tools for corn producers based on these improved forecasts, could substantially reduce uncertai...

  1. Analog forecasting with dynamics-adapted kernels

    NASA Astrophysics Data System (ADS)

    Zhao, Zhizhen; Giannakis, Dimitrios

    2016-09-01

    Analog forecasting is a nonparametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog forecasting by combining ideas from kernel methods developed in harmonic analysis and machine learning and state-space reconstruction for dynamical systems. A key ingredient of our approach is to replace single-analog forecasting with weighted ensembles of analogs constructed using local similarity kernels. The kernels used here employ a number of dynamics-dependent features designed to improve forecast skill, including Takens’ delay-coordinate maps (to recover information in the initial data lost through partial observations) and a directional dependence on the dynamical vector field generating the data. Mathematically, our approach is closely related to kernel methods for out-of-sample extension of functions, and we discuss alternative strategies based on the Nyström method and the multiscale Laplacian pyramids technique. We illustrate these techniques in applications to forecasting in a low-order deterministic model for atmospheric dynamics with chaotic metastability, and interannual-scale forecasting in the North Pacific sector of a comprehensive climate model. We find that forecasts based on kernel-weighted ensembles have significantly higher skill than the conventional approach following a single analog.

  2. Techniques for Forecasting Air Passenger Traffic

    NASA Technical Reports Server (NTRS)

    Taneja, N.

    1972-01-01

    The basic techniques of forecasting the air passenger traffic are outlined. These techniques can be broadly classified into four categories: judgmental, time-series analysis, market analysis and analytical. The differences between these methods exist, in part, due to the degree of formalization of the forecasting procedure. Emphasis is placed on describing the analytical method.

  3. Forecasting Enrollments with Fuzzy Time Series.

    ERIC Educational Resources Information Center

    Song, Qiang; Chissom, Brad S.

    The concept of fuzzy time series is introduced and used to forecast the enrollment of a university. Fuzzy time series, an aspect of fuzzy set theory, forecasts enrollment using a first-order time-invariant model. To evaluate the model, the conventional linear regression technique is applied and the predicted values obtained are compared to the…

  4. Why preferring parametric forecasting to nonparametric methods?

    PubMed

    Jabot, Franck

    2015-05-07

    A recent series of papers by Charles T. Perretti and collaborators have shown that nonparametric forecasting methods can outperform parametric methods in noisy nonlinear systems. Such a situation can arise because of two main reasons: the instability of parametric inference procedures in chaotic systems which can lead to biased parameter estimates, and the discrepancy between the real system dynamics and the modeled one, a problem that Perretti and collaborators call "the true model myth". Should ecologists go on using the demanding parametric machinery when trying to forecast the dynamics of complex ecosystems? Or should they rely on the elegant nonparametric approach that appears so promising? It will be here argued that ecological forecasting based on parametric models presents two key comparative advantages over nonparametric approaches. First, the likelihood of parametric forecasting failure can be diagnosed thanks to simple Bayesian model checking procedures. Second, when parametric forecasting is diagnosed to be reliable, forecasting uncertainty can be estimated on virtual data generated with the fitted to data parametric model. In contrast, nonparametric techniques provide forecasts with unknown reliability. This argumentation is illustrated with the simple theta-logistic model that was previously used by Perretti and collaborators to make their point. It should convince ecologists to stick to standard parametric approaches, until methods have been developed to assess the reliability of nonparametric forecasting.

  5. Kp Forecast Model Using Unscented Kalman Filtering

    DTIC Science & Technology

    2010-09-01

    a simple persistence model that forecasts the next 3-hr value as being equal to the current value shows a linear correlation coefficient of r = 0.797... correlation coefficient and the RMSE between the forecast value and the actual value. A new skill score that assesses how well the model predicts the

  6. Forecaster: Mass and radii of planets predictor

    NASA Astrophysics Data System (ADS)

    Chen, Jingjing; Kipping, David

    2017-01-01

    Forecaster predicts the mass (or radius) from the radius (or mass) for objects covering nine orders-of-magnitude in mass. It is an unbiased forecasting model built upon a probabilistic mass-radius relation conditioned on a sample of 316 well-constrained objects. It accounts for observational errors, hyper-parameter uncertainties and the intrinsic dispersions observed in the calibration sample.

  7. Occupational Forecasting of Librarians in Australia.

    ERIC Educational Resources Information Center

    Stall, Roy

    This paper reviews the principal sources and methods used by the Manpower Research and Information Branches of the Department of Employment and Industrial Relations (DEIR) to forecast the over or undersupply of librarians in Australia. After differentiating between manpower policy, planning, and forecasting, the role of the commonwealth government…

  8. Forecast of geothermal-drilling activity

    SciTech Connect

    Mansure, A.J.; Brown, G.L.

    1982-07-01

    The number of geothermal wells that will be drilled to support electric power production in the United States through 2000 A.D. are forecasted. Results of the forecast are presented by 5-year periods for the five most significant geothermal resources.

  9. School Science Inspired by Improving Weather Forecasts

    ERIC Educational Resources Information Center

    Reid, Heather; Renfrew, Ian A.; Vaughan, Geraint

    2014-01-01

    High winds and heavy rain are regular features of the British weather, and forecasting these events accurately is a major priority for the Met Office and other forecast providers. This is the challenge facing DIAMET, a project involving university groups from Manchester, Leeds, Reading, and East Anglia, together with the Met Office. DIAMET is part…

  10. Forecasting Workload for Defense Logistics Agency Distribution

    DTIC Science & Technology

    2014-12-01

    NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA MBA PROFESSIONAL REPORT FORECASTING WORKLOAD FOR DEFENSE LOGISTICS AGENCY...DATE December 2014 3. REPORT TYPE AND DATES COVERED MBA Professional Report 4. TITLE AND SUBTITLE FORECASTING WORKLOAD FOR DEFENSE LOGISTICS ...maximum 200 words) The Defense Logistics Agency (DLA) predicts issue and receipt workload for its distribution agency in order to maintain

  11. Resources and Long-Range Forecasts

    ERIC Educational Resources Information Center

    Smith, Waldo E.

    1973-01-01

    The author argues that forecasts of quick depletion of resources in the environment as a result of overpopulation and increased usage may not be free from error. Ignorance still exists in understanding the recovery mechanisms of nature. Long-range forecasts are likely to be wrong in such situations. (PS)

  12. Econometric Models for Forecasting of Macroeconomic Indices

    ERIC Educational Resources Information Center

    Sukhanova, Elena I.; Shirnaeva, Svetlana Y.; Mokronosov, Aleksandr G.

    2016-01-01

    The urgency of the research topic was stipulated by the necessity to carry out an effective controlled process by the economic system which can hardly be imagined without indices forecasting characteristic of this system. An econometric model is a safe tool of forecasting which makes it possible to take into consideration the trend of indices…

  13. Some Initiatives in a Business Forecasting Course

    ERIC Educational Resources Information Center

    Chu, Singfat

    2007-01-01

    The paper reports some initiatives to freshen up the typical undergraduate business forecasting course. These include (1) students doing research and presentations on contemporary tools and industry practices such as neural networks and collaborative forecasting (2) insertion of Logistic Regression in the curriculum (3) productive use of applets…

  14. Flood Forecasting in Wales: Challenges and Solutions

    NASA Astrophysics Data System (ADS)

    How, Andrew; Williams, Christopher

    2015-04-01

    With steep, fast-responding river catchments, exposed coastal reaches with large tidal ranges and large population densities in some of the most at-risk areas; flood forecasting in Wales presents many varied challenges. Utilising advances in computing power and learning from best practice within the United Kingdom and abroad have seen significant improvements in recent years - however, many challenges still remain. Developments in computing and increased processing power comes with a significant price tag; greater numbers of data sources and ensemble feeds brings a better understanding of uncertainty but the wealth of data needs careful management to ensure a clear message of risk is disseminated; new modelling techniques utilise better and faster computation, but lack the history of record and experience gained from the continued use of more established forecasting models. As a flood forecasting team we work to develop coastal and fluvial forecasting models, set them up for operational use and manage the duty role that runs the models in real time. An overview of our current operational flood forecasting system will be presented, along with a discussion on some of the solutions we have in place to address the challenges we face. These include: • real-time updating of fluvial models • rainfall forecasting verification • ensemble forecast data • longer range forecast data • contingency models • offshore to nearshore wave transformation • calculation of wave overtopping

  15. Evaluation and first forecasts of the German Climate Forecast System 1 (GCFS1)

    NASA Astrophysics Data System (ADS)

    Fröhlich, Kristina; Baehr, Johanna; Müller, Wolfgang; Bunzel, Felix; Pohlmann, Holger; Dobrynin, Mikhail

    2016-04-01

    We present the near-operational seasonal forecast system GCFS1 (German Climate Forecast System version 1), based on the CMIP5 version of the global coupled climate model MPI-ESM-LR. For GCFS1 we also present a detailed assessment on the predictive skill of the model. GCFS1 has been developed in cooperation between the Max Planck Institute for Meteorology, University of Hamburg and German Meteorological Service (DWD), the forecasts are conducted by DWD. The system is running at ECMWF with a re-forecast ensemble of 15 member and a forecast ensemble of 30 member. The re-forecasts are initialised with full field nudging in the atmosphere (using ERA Interim), in the ocean (using ORAS4) and in the sea-ice component (using NSIDC sea-ice concentration). For the initialization of the forecasts analyses from the ECMWF NWP model and recent ORAS4 analyses are taken. The ensemble perturbations are, for both re-forecasts and forecasts, generated through bred vectors in the ocean which provide initial perturbations for the ensemble in combination with simple physics perturbations in the atmosphere. Evaluation of the re-forecasted climatologies will be presented for different variables, start dates and regions. The first winter forecast during the strong El Niño phase is also subject of evaluation.

  16. 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.

  17. Forecasting the Chilean Tsunami, February 27 2010

    NASA Astrophysics Data System (ADS)

    Sterling, K.; Knight, W.; Whitmore, P.

    2010-12-01

    The West Coast and Alaska Tsunami Warning Center (WC/ATWC) is responsible for issuing tsunami warnings, advisories, and watches for the United States and Canadian coastlines. Utilizing well defined criteria related to earthquake magnitude and location an initial alert message is transmitted. The situation is monitored closely and analyzed using forecast models and real-time sea level observations. If a tsunami is detected then a tsunami warning, advisory, or watch is issued. On February 27, 2010 at 06:34:14 UTC, a M8.8 earthquake occurred off the coast of Maule, Chile, initiating a tsunami that propagated throughout the Pacific Ocean. With approximately 13 hours before the tsunami arrived on the US west coast, the WC/ATWC utilized all available forecasting tools to refine predicted tsunami amplitudes and inundation estimates, thereby providing the best possible estimates to emergency managers and the public. The guidance from the tsunami forecast models, used in concurrence with sea-level observations, resulted in a tsunami advisory being issued for the Pacific coastal regions of the United States and Canada, the extent of which was expanded and then decreased as the event evolved. The WC/ATWC used two tsunami forecast models: the Alaska Tsunami Forecast Model (ATFM) and the Short-term Inundation Forecasting for Tsunamis (SIFT) to formulate a solution. Each model provided an initial tsunami forecast based on the earthquake magnitude and location that was subsequently refined over the following hours as Deep-ocean Assessment and Reporting of Tsunamis (DART) observations became available. After the DART data was assimilated into the models, the two forecasts were used in conjunction to publicly issue predicted maximum amplitudes for 77 locations along the US west coast and in Alaska. As the tsunami reached the US coastline, tide gauge observations were used in scaling the forecasted maximum amplitudes from the ATFM, thereby increasing the forecast accuracy

  18. Error models for official mortality forecasts.

    PubMed

    Alho, J M; Spencer, B D

    1990-09-01

    "The Office of the Actuary, U.S. Social Security Administration, produces alternative forecasts of mortality to reflect uncertainty about the future.... In this article we identify the components and assumptions of the official forecasts and approximate them by stochastic parametric models. We estimate parameters of the models from past data, derive statistical intervals for the forecasts, and compare them with the official high-low intervals. We use the models to evaluate the forecasts rather than to develop different predictions of the future. Analysis of data from 1972 to 1985 shows that the official intervals for mortality forecasts for males or females aged 45-70 have approximately a 95% chance of including the true mortality rate in any year. For other ages the chances are much less than 95%."

  19. Wind speed forecasting for wind energy applications

    NASA Astrophysics Data System (ADS)

    Liu, Hong

    With more wind energy being integrated into our grid systems, forecasting wind energy has become a necessity for all market participants. Recognizing the market demands, a physical approach to site-specific hub-height wind speed forecasting system has been developed. This system is driven by the outputs from the Canadian Global Environmental Multiscale (GEM) model. A simple interpolation approach benchmarks the forecasting accuracy inherited from GEM. Local, site specific winds are affected on a local scale by a variety of factors including representation of the land surface and local boundary-layer process over heterogeneous terrain which have been a continuing challenge in NWP models like GEM with typical horizontal resolution of order 15-km. In order to resolve these small scale effects, a wind energy industry standard model, WAsP, is coupled with GEM to improve the forecast. Coupling the WAsP model with GEM improves the overall forecasts, but remains unsatisfactory for forecasting winds with abrupt surface condition changes. Subsequently in this study, a new coupler that uses a 2-D RANS model of boundary-layer flow over surface condition changes with improved physics has been developed to further improve the forecasts when winds coming from a water surface to land experience abrupt changes in surface conditions. It has been demonstrated that using vertically averaged wind speeds to represent geostrophic winds for input into the micro-scale models could reduce forecast errors. The hub-height wind speed forecasts could be further improved using a linear MOS approach. The forecasting system has been evaluated, using a wind energy standard evaluation matrix, against data from an 80-m mast located near the north shore of Lake Erie. Coupling with GEM-LAM and a power conversion model using a theoretical power curve have also been investigated. For hub-height wind speeds GEM appears to perform better with a 15-Ian grid than the high resolution GEM-2.5Ian version at the

  20. Space Weather Forecasting: An Enigma

    NASA Astrophysics Data System (ADS)

    Sojka, J. J.

    2012-12-01

    -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.

  1. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast. Technical Appendix: Volume 1.

    SciTech Connect

    1994-02-01

    This publication documents the load forecast scenarios and assumptions used to prepare BPA's Whitebook. It is divided into: intoduction, summary of 1993 Whitebook electricity demand forecast, conservation in the load forecast, projection of medium case electricity sales and underlying drivers, residential sector forecast, commercial sector forecast, industrial sector forecast, non-DSI industrial forecast, direct service industry forecast, and irrigation forecast. Four appendices are included: long-term forecasts, LTOUT forecast, rates and fuel price forecasts, and forecast ranges-calculations.

  2. Testing the Value of Probability Forecasts for Calibrated Combining

    PubMed Central

    Lahiri, Kajal; Peng, Huaming; Zhao, Yongchen

    2014-01-01

    We combine the probability forecasts of a real GDP decline from the U.S. Survey of Professional Forecasters, after trimming the forecasts that do not have “value”, as measured by the Kuiper Skill Score and in the sense of Merton (1981). For this purpose, we use a simple test to evaluate the probability forecasts. The proposed test does not require the probabilities to be converted to binary forecasts before testing, and it accommodates serial correlation and skewness in the forecasts. We find that the number of forecasters making valuable forecasts decreases sharply as the horizon increases. The beta-transformed linear pool combination scheme, based on the valuable individual forecasts, is shown to outperform the simple average for all horizons on a number of performance measures, including calibration and sharpness. The test helps to identify the good forecasters ex ante, and therefore contributes to the accuracy of the combined forecasts. PMID:25530646

  3. Construction Safety Forecast for ITER

    SciTech Connect

    cadwallader, lee charles

    2006-11-01

    The International Thermonuclear Experimental Reactor (ITER) project is poised to begin its construction activity. This paper gives an estimate of construction safety as if the experiment was being built in the United States. This estimate of construction injuries and potential fatalities serves as a useful forecast of what can be expected for construction of such a major facility in any country. These data should be considered by the ITER International Team as it plans for safety during the construction phase. Based on average U.S. construction rates, ITER may expect a lost workday case rate of < 4.0 and a fatality count of 0.5 to 0.9 persons per year.

  4. Clear air turbulence forecasting techniques

    NASA Technical Reports Server (NTRS)

    Keller, J. L.

    1980-01-01

    A method to improve clear air turbulence (CAT) forecasting by more effectively using the currently operational rawinsonde (RW) system is discussed. The method is called the Diagnostic Richardson Number Tendency (DRT) technique. The technique does not attempt to use the RW as a direct detector of the turbulent motion or even of the CAT mechanism structure but rather senses the synoptic scale centers of action which provide the energy to the CAT mechanism at the mesoscale level. The DRT algorithm is deterministic rather than statistical in nature, using the hydrodynamic equations (equations of motion) relevant to the synoptic scale. However, interpretation, by necessity, is probabilistic. What is most important with respect to its operational implementation is that this method uses the same input data as currently used by the operational National Meteorological Center prognostic models.

  5. Decision support for financial forecasting

    SciTech Connect

    Jairam, B.N.; Morris, J.D.; Emrich, M.L.; Hardee, H.K.

    1988-10-01

    A primary mission of the Budget Management Division of the Air Force is fiscal analysis. This involves formulating, justifying, and tracking financial data during budget preparation and execution. An essential requirement of this process is the ready availability and easy manipulation of past and current budget data. This necessitates the decentralization of the data. A prototypical system, BAFS (Budget Analysis and Forecasting System), that provides such a capability is presented. In its current state, the system is designed to be a decision support tool. A brief report of the budget decisions and activities is presented. The system structure and its major components are discussed. An insight into the implementation strategies and the tool used is provided. The paper concludes with a discussion of future enhancements and the system's evolution into an expert system. 4 refs., 3 figs.

  6. Real-time flood forecasting

    USGS Publications Warehouse

    Lai, C.; Tsay, T.-K.; Chien, C.-H.; Wu, I.-L.

    2009-01-01

    Researchers at the Hydroinformatic Research and Development Team (HIRDT) of the National Taiwan University undertook a project to create a real time flood forecasting model, with an aim to predict the current in the Tamsui River Basin. The model was designed based on deterministic approach with mathematic modeling of complex phenomenon, and specific parameter values operated to produce a discrete result. The project also devised a rainfall-stage model that relates the rate of rainfall upland directly to the change of the state of river, and is further related to another typhoon-rainfall model. The geographic information system (GIS) data, based on precise contour model of the terrain, estimate the regions that were perilous to flooding. The HIRDT, in response to the project's progress, also devoted their application of a deterministic model to unsteady flow of thermodynamics to help predict river authorities issue timely warnings and take other emergency measures.

  7. Uses and Applications of Climate Forecasts for Power Utilities.

    NASA Astrophysics Data System (ADS)

    Changnon, Stanley A.; Changnon, Joyce M.; Changnon, David

    1995-05-01

    The uses and potential applications of climate forecasts for electric and gas utilities were assessed 1) to discern needs for improving climate forecasts and guiding future research, and 2) to assist utilities in making wise use of forecasts. In-depth structured interviews were conducted with 56 decision makers in six utilities to assess existing and potential uses of climate forecasts. Only 3 of the 56 use forecasts. Eighty percent of those sampled envisioned applications of climate forecasts, given certain changes and additional information. Primary applications exist in power trading, load forecasting, fuel acquisition, and systems planning, with slight differences in interests between utilities. Utility staff understand probability-based forecasts but desire climatological information related to forecasted outcomes, including analogs similar to the forecasts, and explanations of the forecasts. Desired lead times vary from a week to three months, along with forecasts of up to four seasons ahead. The new NOAA forecasts initiated in 1995 provide the lead times and longer-term forecasts desired. Major hindrances to use of forecasts are hard-to-understand formats, lack of corporate acceptance, and lack of access to expertise. Recent changes in government regulations altered the utility industry, leading to a more competitive world wherein information about future weather conditions assumes much more value. Outreach efforts by government forecast agencies appear valuable to help achieve the appropriate and enhanced use of climate forecasts by the utility industry. An opportunity for service exists also for the private weather sector.

  8. MSSM forecast for the LHC

    NASA Astrophysics Data System (ADS)

    Cabrera, Maria Eugenia; Casas, J. Alberto; de Austri, Roberto Ruiz

    2010-05-01

    We perform a forecast of the MSSM with universal soft terms (CMSSM) for the LHC, based on an improved Bayesian analysis. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises from the Bayesian analysis itself when the experimental value of M Z is considered. This allows to scan the whole parameter space, allowing arbitrarily large soft terms. Still the low-energy region is statistically favoured (even before including dark matter or g-2 constraints). Contrary to other studies, the results are almost unaffected by changing the upper limits taken for the soft terms. The results are also remarkable stable when using flat or logarithmic priors, a fact that arises from the larger statistical weight of the low-energy region in both cases. Then we incorporate all the important experimental constrains to the analysis, obtaining a map of the probability density of the MSSM parameter space, i.e. the forecast of the MSSM. Since not all the experimental information is equally robust, we perform separate analyses depending on the group of observables used. When only the most robust ones are used, the favoured region of the parameter space contains a significant portion outside the LHC reach. This effect gets reinforced if the Higgs mass is not close to its present experimental limit and persits when dark matter constraints are included. Only when the g-2 constraint (based on e + e - data) is considered, the preferred region (for μ > 0) is well inside the LHC scope. We also perform a Bayesian comparison of the positive- and negative- μ possibilities.

  9. Phantosmia as a meteorological forecaster.

    PubMed

    Aiello, S R; Hirsch, A R

    2013-09-01

    In normosmics, olfactory ability has been found to vary with ambient humidity, barometric pressure, and season. While hallucinated sensations of phantom pain associated with changes in weather have been described, a linkage to chemosensory hallucinations has heretofore not been reported. A 64-year-old white male with Parkinson's disease presents with 5 years of phantosmia of a smoky burnt wood which changed to onion-gas and then to a noxious skunk-onion excrement odor. Absent upon waking it increases over the day and persists for hours. When severe, there appears a phantom taste with the same qualities as the odor. It is exacerbated by factors that manipulate intranasal pressure, such as coughing. When eating or sniffing, the actual flavors replace the phantosmia. Since onset, he noted the intensity and frequency of the phantosmia forecasted the weather. Two to 3 h before a storm, the phantosmia intensifies from a level 0 to a 7-10, which persists through the entire thunderstorm. Twenty years prior, he reported the ability to forecast the weather, based on pain in a torn meniscus, which vanished after surgical repair. Extensive olfactory testing demonstrates underlying hyposmia. Possible mechanisms for such chemosensory-meteorological linkage includes: air pressure induced synesthesia, disinhibition of spontaneous olfactory discharge, exacerbation of ectopic discharge, affect mediated somatic sensory amplification, and misattribution error with expectation and recall bias. This is the first reported case of weather-induced exacerbation of phantosmia. Further investigation of the connection between chemosensory complaints and ambient weather is warranted.

  10. 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.

  11. Urban Air Quality Forecasting in Canada

    NASA Astrophysics Data System (ADS)

    Pavlovic, Radenko; Menard, Sylvain; Cousineau, Sophie; Stroud, Craig; Moran, Michael

    2016-04-01

    Environment and Climate Change Canada has been providing air quality (AQ) forecasts for major Canadian urban centers since 2001. Over this period, the Canadian AQ Forecast Program has expanded and evolved. It currently uses the Regional Air Quality Deterministic Prediction System (RAQDPS) modelling framework. At the heart of the RAQDPS is the GEM-MACH model, an on-line coupled meteorology‒chemistry model configured for a North American domain with 10 km horizontal grid spacing and 80 vertical levels. A statistical post-processing model (UMOS-AQ) is then applied to the RAQDPS hourly forecasts for locations with AQ monitors to reduce point forecast bias and error. These outputs provide the primary guidance from which operational meteorologists disseminate Air Quality Health Index (AQHI) forecasts to the public for major urban centres across Canada. During the 2015 summer Pan Am and Parapan Am Games, which were held in Ontario, Canada, an experimental version of the RAQDPS at 2.5 km horizontal grid spacing was run for a domain over the greater Toronto area. Currently, there is ongoing research to develop and assess AQ systems run at 1 km resolution. This presentation will show analyses of operational AQ forecast performance for several pollutants over the last few years in major Canadian urban centres such as Toronto, Montreal, Vancouver, Ottawa, and Calgary. Trends in observed pollution along with short- and long-term development plans for urban AQ forecasting will also be presented.

  12. Precision Fiber Optic Sensor Market Forecast

    NASA Astrophysics Data System (ADS)

    Montgomery, Jeff D.; Glasco, Jon; Dixon, Frank W.

    1986-01-01

    The worldwide market for precision fiber optic sensors is forecasted, 1984-1994. The forecast is based upon o Analysis of fiber optic sensor and related component current technology, and a forecast of technology advancement o Review and projection of demand for precision sensing, and the penetration which fiber optics will make into this market The analysis and projections are based mainly on interviews conducted worldwide with research teams, government agencies, systems contractors, medical and industrial laboratories, component suppliers and others. The worldwide market for precision (interferometric) fiber optic sensing systems is forecasted to exceed $0.8 billion by 1994. The forecast is segmented by geographical region (Europe, Japan and North America) and by function; o Gyroscope o Sonar o Gradiometer/Magnetometer o Other - Chemical Composition - Atmospheric Acoustic - Temperature - Position - Pressure Requirements for components are reviewed. These include special fiber, emitters and detectors, modulators, couplers, switches, integrated optical circuits and integrated optoelectronics. The advancement in component performance is forecasted. The major driving forces creating fiber optic sensor markets are reviewed. These include fiber optic sensor technical and economic advantages, increasingly stringent operational requirements, and technology evolution. The leading fiber optic sensor and related component development programs are reviewed. Component sources are listed. Funding sources for sensor and component development are outlined, and trends forecasted.

  13. National Weather Service Forecast Reference Evapotranspiration

    NASA Astrophysics Data System (ADS)

    Osborne, H. D.; Palmer, C. K.; Krone-Davis, P.; Melton, F. S.; Hobbins, M.

    2013-12-01

    The National Weather Service (NWS), Weather Forecasting Offices (WFOs) are producing daily reference evapotranspiration (ETrc) forecasts or FRET across the Western Region and in other selected locations since 2009, using the Penman - Monteith Reference Evapotranspiration equation for a short canopy (12 cm grasses), adopted by the Environmental Water Resources Institute of the American Society of Civil Engineers (ASCE-EWRI, 2004). The sensitivity of these daily calculations to fluctuations in temperatures, humidity, winds, and sky cover allows forecasters with knowledge of local terrain and weather patterns to better forecast in the ETrc inputs. The daily FRET product then evolved into a suite of products, including a weekly ETrc forecast for better water planning and a tabular point forecast for easy ingest into local water management-models. The ETrc forecast product suite allows water managers, the agricultural community, and the public to make more informed water-use decisions. These products permit operational planning, especially with the impending drought across much of the West. For example, the California Department of Water Resources not only ingests the FRET into their soil moisture models, but uses the FRET calculations when determining the reservoir releases in the Sacramento and American Rivers. We will also focus on the expansion of FRET verification, which compares the daily FRET to the observations of ETo from the California Irrigation Management Information System (CIMIS) across California's Central Valley for the 2012 water year.

  14. A Simulation Optimization Approach to Epidemic Forecasting

    PubMed Central

    Nsoesie, Elaine O.; Beckman, Richard J.; Shashaani, Sara; Nagaraj, Kalyani S.; Marathe, Madhav V.

    2013-01-01

    Reliable forecasts of influenza can aid in the control of both seasonal and pandemic outbreaks. We introduce a simulation optimization (SIMOP) approach for forecasting the influenza epidemic curve. This study represents the final step of a project aimed at using a combination of simulation, classification, statistical and optimization techniques to forecast the epidemic curve and infer underlying model parameters during an influenza outbreak. The SIMOP procedure combines an individual-based model and the Nelder-Mead simplex optimization method. The method is used to forecast epidemics simulated over synthetic social networks representing Montgomery County in Virginia, Miami, Seattle and surrounding metropolitan regions. The results are presented for the first four weeks. Depending on the synthetic network, the peak time could be predicted within a 95% CI as early as seven weeks before the actual peak. The peak infected and total infected were also accurately forecasted for Montgomery County in Virginia within the forecasting period. Forecasting of the epidemic curve for both seasonal and pandemic influenza outbreaks is a complex problem, however this is a preliminary step and the results suggest that more can be achieved in this area. PMID:23826222

  15. Weather forecasting based on hybrid neural model

    NASA Astrophysics Data System (ADS)

    Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.

    2017-02-01

    Making deductions and expectations about climate has been a challenge all through mankind's history. Challenges with exact meteorological directions assist to foresee and handle problems well in time. Different strategies have been investigated using various machine learning techniques in reported forecasting systems. Current research investigates climate as a major challenge for machine information mining and deduction. Accordingly, this paper presents a hybrid neural model (MLP and RBF) to enhance the accuracy of weather forecasting. Proposed hybrid model ensure precise forecasting due to the specialty of climate anticipating frameworks. The study concentrates on the data representing Saudi Arabia weather forecasting. The main input features employed to train individual and hybrid neural networks that include average dew point, minimum temperature, maximum temperature, mean temperature, average relative moistness, precipitation, normal wind speed, high wind speed and average cloudiness. The output layer composed of two neurons to represent rainy and dry weathers. Moreover, trial and error approach is adopted to select an appropriate number of inputs to the hybrid neural network. Correlation coefficient, RMSE and scatter index are the standard yard sticks adopted for forecast accuracy measurement. On individual standing MLP forecasting results are better than RBF, however, the proposed simplified hybrid neural model comes out with better forecasting accuracy as compared to both individual networks. Additionally, results are better than reported in the state of art, using a simple neural structure that reduces training time and complexity.

  16. A method for probabilistic flash flood forecasting

    NASA Astrophysics Data System (ADS)

    Hardy, Jill; Gourley, Jonathan J.; Kirstetter, Pierre-Emmanuel; Hong, Yang; Kong, Fanyou; Flamig, Zachary L.

    2016-10-01

    Flash flooding is one of the most costly and deadly natural hazards in the United States and across the globe. This study advances the use of high-resolution quantitative precipitation forecasts (QPFs) for flash flood forecasting. The QPFs are derived from a stormscale ensemble prediction system, and used within a distributed hydrological model framework to yield basin-specific, probabilistic flash flood forecasts (PFFFs). Before creating the PFFFs, it is important to characterize QPF uncertainty, particularly in terms of location which is the most problematic for hydrological use of QPFs. The SAL methodology (Wernli et al., 2008), which stands for structure, amplitude, and location, is used for this error quantification, with a focus on location. Finally, the PFFF methodology is proposed that produces probabilistic hydrological forecasts. The main advantages of this method are: (1) identifying specific basin scales that are forecast to be impacted by flash flooding; (2) yielding probabilistic information about the forecast hydrologic response that accounts for the locational uncertainties of the QPFs; (3) improving lead time by using stormscale NWP ensemble forecasts; and (4) not requiring multiple simulations, which are computationally demanding.

  17. Seasonal streamflow forecasting with the global hydrological forecasting system FEWS-World

    NASA Astrophysics Data System (ADS)

    Candogan Yossef, N.; Van Beek, L. P.; Winsemius, H.; Bierkens, M. F.

    2011-12-01

    The year-to-year variability of river discharge brings about risks and opportunities in water resources management. Reliable hydrological forecasts and effective communication allow several sectors to make more informed management decisions. In many developing regions of the world, there are no efficient hydrological forecasting systems. For these regions, a global forecasting system which indicates increased probabilities of streamflow excesses or shortages over long lead-times can be of great value. FEWS-World is developed for this purpose. The system incorporates the global hydrological model PCR-GLOBWB and delivers streamflow forecasts on a global scale. This study investigates the skill and value of FEWS-World. Skill is defined as the ability of the system to forecast discharge extremes; and value is its usefulness for possible users and ultimately for affected populations. Skill is assessed in historical simulation mode as well as retroactive forecasting mode. The eventual goal is to transfer FEWS-World to operational forecasting mode, where the system will use operational seasonal forecasts from the European Center for Medium-Range Weather Forecasts (ECMWF). The results will be disseminated on the internet to provide valuable information for users in data and model-poor regions of the world. The preliminary skill assessment of PCR-GLOBWB in reproducing flow extremes is carried out for a selection of 20 large rivers of the world. The model is run for a historical period, with a meteorological forcing data set based on observations from the Climate Research Unit of the University of East Anglia, and the ERA-40 reanalysis of ECMWF. Model skill in reproducing monthly anomalies as well as floods and droughts is assessed by applying verification measures developed for deterministic meteorological forecasts. The results of this preliminary analysis shows that even where the simulated hydrographs are biased, higher skills can be attained in reproducing monthly

  18. Accuracy analysis of TDRSS demand forecasts

    NASA Technical Reports Server (NTRS)

    Stern, Daniel C.; Levine, Allen J.; Pitt, Karl J.

    1994-01-01

    This paper reviews Space Network (SN) demand forecasting experience over the past 16 years and describes methods used in the forecasts. The paper focuses on the Single Access (SA) service, the most sought-after resource in the Space Network. Of the ten years of actual demand data available, only the last five years (1989 to 1993) were considered predictive due to the extensive impact of the Challenger accident of 1986. NASA's Space Network provides tracking and communications services to user spacecraft such as the Shuttle and the Hubble Space Telescope. Forecasting the customer requirements is essential to planning network resources and to establishing service commitments to future customers. The lead time to procure Tracking and Data Relay Satellites (TDRS's) requires demand forecasts ten years in the future a planning horizon beyond the funding commitments for missions to be supported. The long range forecasts are shown to have had a bias toward underestimation in the 1991 -1992 period. The trend of underestimation can be expected to be replaced by overestimation for a number of years starting with 1998. At that time demand from new missions slated for launch will be larger than the demand from ongoing missions, making the potential for delay the dominant factor. If the new missions appear as scheduled, the forecasts are likely to be moderately underestimated. The SN commitment to meet the negotiated customer's requirements calls for conservatism in the forecasting. Modification of the forecasting procedure to account for a delay bias is, therefore, not advised. Fine tuning the mission model to more accurately reflect the current actual demand is recommended as it may marginally improve the first year forecasting.

  19. Tsunami Forecast: Connecting Science with Warning Operations

    NASA Astrophysics Data System (ADS)

    Titov, V. V.

    2014-12-01

    Tsunami modeling capability had been rapidly developing even before the watershed event of the 2004 Sumatra tsunami. During 1990-2000, the International Decade for Natural Disaster Reduction, the tsunami scientific community took on the difficult task of developing the modeling capability that would provide accuracy needed for long-term tsunami forecast — tsunami hazard maps. After exhaustive field, laboratory and modeling efforts by the international scientific community, the modeling capability has been achieved with accuracy deemed sufficient for operational use. Several real-time model forecast tools started to be used at TWCs in the US and Japan. In parallel, the observational component of tsunami warning systems had been improving, including updated existing seismic and coastal sea-level stations array. New early detection and measurement system (DART) has been developed specifically for tsunami forecast applications. The 2004 Sumatra tsunami has triggered the efforts of intensive implementation of science results into operational tsunami warning capabilities. At present, several tsunami forecast systems, based on various modeling and detection capabilities, are operational. Since 2004, over 40 tsunamis, including the 2011 Japanese tsunami, provided real-time tests for the tsunami forecast system capabilities. Preliminary assessment of tsunami forecast performance will be presented based on the analysis of the U.S. operational tsunami inundation forecast. Assessing forecast performance is important to evaluate the needs for improvement and further research. Baseline of the tsunami forecast skills has now been established and will be presented based on the data from the tsunamis during the decade. Future improvements and future challenges will also be discussed.

  20. Seasonal hydrological ensemble forecasts over Europe

    NASA Astrophysics Data System (ADS)

    Arnal, Louise; Wetterhall, Fredrik; Stephens, Elisabeth; Cloke, Hannah; Pappenberger, Florian

    2016-04-01

    This study investigates the limits of predictability in dynamical seasonal discharge forecasting, in both space and time, over Europe. Seasonal forecasts have an important socioeconomic value. Applications are numerous and cover hydropower management, spring flood prediction, low flow prediction for navigation and agricultural water demands. Additionally, the constant increase in NWP skill for longer lead times and the predicted increase in the intensity and frequency of hydro-meteorological extremes, have amplified the incentive to promote and further improve hydrological forecasts on sub-seasonal to seasonal timescales. In this study, seasonal hydrological forecasts (SEA), driven by the ECMWF's System 4 in hindcast mode, were analysed against an Ensemble Streamflow Prediction (ESP) benchmark. The ESP was forced with an ensemble of resampled historical meteorological observations and started with perfect initial conditions. Both forecasts were produced by the LISFLOOD model, run on the pan-European scale with a spatial resolution of 5 by 5 km. The forecasts were issued monthly on a daily time step, from 1990 until the current time, up to a lead time of 7 months. The seasonal discharge forecasts were analysed against the ESP on a catchment scale in terms of their accuracy, skill and sharpness, using a diverse set of verification metrics (e.g. KGE, CRPSS and ROC). Additionally, a reverse-ESP was constructed by forcing the LISFLOOD model with a single perfect meteorological set of observations and initiated from an ensemble of resampled historical initial conditions. The comparison of the ESP with the reverse-ESP approach enabled the identification of the respective contribution of meteorological forcings and hydrologic initial conditions errors to seasonal discharge forecasting uncertainties in Europe. These results could help pinpoint target elements of the forecasting chain which, after being improved, could lead to substantial increase in discharge predictability

  1. How MAG4 Improves Space Weather Forecasting

    NASA Technical Reports Server (NTRS)

    Falconer, David; Khazanov, Igor; Barghouty, Nasser

    2013-01-01

    Dangerous space weather is driven by solar flares and Coronal Mass Ejection (CMEs). Forecasting flares and CMEs is the first step to forecasting either dangerous space weather or All Clear. MAG4 (Magnetogram Forecast), developed originally for NASA/SRAG (Space Radiation Analysis Group), is an automated program that analyzes magnetograms from the HMI (Helioseismic and Magnetic Imager) instrument on NASA SDO (Solar Dynamics Observatory), and automatically converts the rate (or probability) of major flares (M- and X-class), Coronal Mass Ejections (CMEs), and Solar Energetic Particle Events.

  2. Weather forecast needs from the viewpoint of hydrology

    USGS Publications Warehouse

    Thomas, Donald M.; Buchanan, Thomas J.

    1980-01-01

    Hydrologists now depend on directly observed data in their forecasting and only infrequently use meteorological forecasts. Case studies show how reliable meteorological forecasts could be beneficial in flood and drought situations. Hydrologists need meteorological forecasts that recognize spatial variability, that are unbiased, and that have a specified degree of uncertainty. (USGS)

  3. An Econometric Model for Forecasting Income and Employment in Hawaii.

    ERIC Educational Resources Information Center

    Chau, Laurence C.

    This report presents the methodology for short-run forecasting of personal income and employment in Hawaii. The econometric model developed in the study is used to make actual forecasts through 1973 of income and employment, with major components forecasted separately. Several sets of forecasts are made, under different assumptions on external…

  4. Epidemic forecasting is messier than weather forecasting: The role of human behavior and internet data streams in epidemic forecast

    DOE PAGES

    Moran, Kelly Renee; Fairchild, Geoffrey; Generous, Nicholas; ...

    2016-11-14

    Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection andmore » Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. Here, we conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting.« less

  5. Epidemic forecasting is messier than weather forecasting: The role of human behavior and internet data streams in epidemic forecast

    SciTech Connect

    Moran, Kelly Renee; Fairchild, Geoffrey; Generous, Nicholas; Hickmann, Kyle Scott; Osthus, Dave Allen; Priedhorsky, Reid; Hyman, James M.; Del Valle, Sara Yermimah

    2016-11-14

    Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection and Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. Here, we conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting.

  6. 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

  7. Ensemble Forecasts with Useful Skill-Spread Relationships for African meningitis and Asia Streamflow Forecasting

    NASA Astrophysics Data System (ADS)

    Hopson, T. M.

    2014-12-01

    One potential benefit of an ensemble prediction system (EPS) is its capacity to forecast its own forecast error through the ensemble spread-error relationship. In practice, an EPS is often quite limited in its ability to represent the variable expectation of forecast error through the variable dispersion of the ensemble, and perhaps more fundamentally, in its ability to provide enough variability in the ensembles dispersion to make the skill-spread relationship even potentially useful (irrespective of whether the EPS is well-calibrated or not). In this paper we examine the ensemble skill-spread relationship of an ensemble constructed from the TIGGE (THORPEX Interactive Grand Global Ensemble) dataset of global forecasts and a combination of multi-model and post-processing approaches. Both of the multi-model and post-processing techniques are based on quantile regression (QR) under a step-wise forward selection framework leading to ensemble forecasts with both good reliability and sharpness. The methodology utilizes the ensemble's ability to self-diagnose forecast instability to produce calibrated forecasts with informative skill-spread relationships. A context for these concepts is provided by assessing the constructed ensemble in forecasting district-level humidity impacting the incidence of meningitis in the meningitis belt of Africa, and in forecasting flooding events in the Brahmaputra and Ganges basins of South Asia.

  8. From short term power forecasting to nowcasting - Benefiting from meteorological forecasts and measurements

    NASA Astrophysics Data System (ADS)

    Mey, Britta; Braun, Axel; Good, Garrett; Vogt, Stephan; Wessel, Arne; Dobschinski, Jan

    2016-04-01

    Today, wind and solar power forecasts with time horizons from zero to about three hours are essential for the reliable grid and market integration of wind and solar energy. With respect to closure times of German intra-day markets, power forecasts with time horizons of about one to two hours and an update frequency of 15 minutes are required for final trading activities, reducing the uncertainty of the day-ahead forecast of the previous day. Regarding grid security aspects, grid operators utilize such forecasts to create continuous intra-day grid congestion forecasts. In addition to these preventive measures, wind and solar power become more and more important for the provision of ancillary services by wind and solar farm operators. This use case mainly requires power forecasts with time horizons of less than one hour. In general, forecasts with time horizons below three hours are investigated within the nowcasting research area. Nowcasting models are mainly based on current observations and extrapolation methods. With respect to wind and solar power forecasts with horizons of up to three hours, it has been shown in studies that real-time power measurements have the highest information content as compared to other potential model input parameters. We will present results from studies focusing on the benefit of meteorological data (forecasts and/or measurements) in the field of solar and wind power forecasts with time horizons of up to a few hours. Wind farm forecast errors are for example reduced by using numerical weather prediction (NWP) data in the wind power prediction model along with real-time wind farm power measurements. Furthermore, spatially distributed NWP data in combination with German total wind power measurements helped in the reduction of extreme forecast errors. By using global radiation forecasts as an input for wind power forecasts, forecast error during sunrise and sunset could be reduced. In the field of German total solar power, nowcasting

  9. Satellite-advection based solar forecasting: lessons learned and progress towards probabalistic solar forecasting

    NASA Astrophysics Data System (ADS)

    Rogers, M. A.

    2015-12-01

    Using satellite observations from GOES-E and GOES-W platforms in concert with GFS-derived cloud-level winds and a standalone radiative transfer model, an advection-derived forecast for surface GHI over the continental United States, with intercomparison between forecasts for four zones over the CONUS and Central Pacific with SURFRAD results. Primary sources for error in advection-based forecasts, primarily driven by false- or mistimed ramp events are discussed, with identification of error sources quantified along with techniques used to improve advection-based forecasts to approximately 10% MAE for designated surface locations. Development of a blended steering wind product utilizing NWP output combined with satellite-derived winds from AMV techniques to improve 0-1 hour advection forecasts will be discussed. Additionally, the use of two years' of solar forecast observations in the development of a prototype probablistic forecast for ramp events will be shown, with the intent of increasing the use of satellite-derived forecasts for grid operators and optimizing integration of renewable resources into the power grid. Elements of the work were developed under the 'Public-Private-Academic Partnership to Advance Solar Power Forecasting' project spearheaded by the National Center for Atmospheric Research.

  10. Probabilistic regional wind power forecasts based on calibrated Numerical Weather Forecast ensembles

    NASA Astrophysics Data System (ADS)

    Späth, Stephan; von Bremen, Lueder; Junk, Constantin; Heinemann, Detlev

    2014-05-01

    With increasing shares of installed wind power in Germany, accurate forecasts of wind speed and power get increasingly important for the grid integration of Renewable Energies. Applications like grid management and trading also benefit from uncertainty information. This uncertainty information can be provided by ensemble forecasts. These forecasts often exhibit systematic errors such as biases and spread deficiencies. The errors can be reduced by statistical post-processing. We use forecast data from the regional Numerical Weather Prediction model COSMO-DE EPS as input to regional wind power forecasts. In order to enhance the power forecast, we first calibrate the wind speed forecasts against the model analysis, so some of the model's systematic errors can be removed. Wind measurements at every grid point are usually not available and as we want to conduct grid zone forecasts, the model analysis is the best target for calibration. We use forecasts from the COSMO-DE EPS, a high-resolution ensemble prediction system with 20 forecast members. The model covers the region of Germany and surroundings with a vertical resolution of 50 model levels and a horizontal resolution of 0.025 degrees (approximately 2.8 km). The forecast range is 21 hours with model output available on an hourly basis. Thus, we use it for shortest-term wind power forecasts. The COSMO-DE EPS was originally designed with a focus on forecasts of convective precipitation. The COSMO-DE EPS wind speed forecasts at hub height were post-processed by nonhomogenous Gaussian regression (NGR; Thorarinsdottir and Gneiting, 2010), a calibration method that fits a truncated normal distribution to the ensemble wind speed forecasts. As calibration target, the model analysis was used. The calibration is able to remove some deficits of the COSMO-DE EPS. In contrast to the raw ensemble members, the calibrated ensemble members do not show anymore the strong correlations with each other and the spread-skill relationship

  11. Local Air Quality Conditions and Forecasts

    MedlinePlus

    Local Air Quality Conditions Zip Code: State : My Current Location Map Center Forecast AQI Current AQI Current Ozone Current PM ... Ozone Loop PM Loop AQI: Good (0 - 50) Air quality is considered satisfactory, and air pollution poses little ...

  12. Forecasting residential electricity demand in provincial China.

    PubMed

    Liao, Hua; Liu, Yanan; Gao, Yixuan; Hao, Yu; Ma, Xiao-Wei; Wang, Kan

    2017-03-01

    In China, more than 80% electricity comes from coal which dominates the CO2 emissions. Residential electricity demand forecasting plays a significant role in electricity infrastructure planning and energy policy designing, but it is challenging to make an accurate forecast for developing countries. This paper forecasts the provincial residential electricity consumption of China in the 13th Five-Year-Plan (2016-2020) period using panel data. To overcome the limitations of widely used predication models with unreliably prior knowledge on function forms, a robust piecewise linear model in reduced form is utilized to capture the non-deterministic relationship between income and residential electricity consumption. The forecast results suggest that the growth rates of developed provinces will slow down, while the less developed will be still in fast growing. The national residential electricity demand will increase at 6.6% annually during 2016-2020, and populous provinces such as Guangdong will be the main contributors to the increments.

  13. NOAA's Space Weather Prediction Center, Forecast Office

    NASA Video Gallery

    The Forecast Office of NOAA's Space Weather Prediction Center is the nation's official source of alerts, warnings, and watches. The office, staffed 24/7, is always vigilant for solar activity that ...

  14. Flood Forecasting in River System Using ANFIS

    SciTech Connect

    Ullah, Nazrin; Choudhury, P.

    2010-10-26

    The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.

  15. Predictability Assessment and Improving Ensemble Forecasts

    DTIC Science & Technology

    2001-09-30

    system (EFS) output by artificial neural networks . c) Design of optimal EFS’s, with an emphasis on precipitation forecasts. d) Design of stochastic physics parameterizations that improve under-dispersion in EFS s.

  16. AIR QUALITY FORECAST VERIFICATION USING SATELLITE DATA

    EPA Science Inventory

    NOAA 's operational geostationary satellite retrievals of aerosol optical depths (AODs) were used to verify National Weather Service (NWS) experimental (research mode) particulate matter (PM2.5) forecast guidance issued during the summer 2004 International Consortium for Atmosp...

  17. Forecasting in the presence of expectations

    NASA Astrophysics Data System (ADS)

    Allen, R.; Zivin, J. G.; Shrader, J.

    2016-05-01

    Physical processes routinely influence economic outcomes, and actions by economic agents can, in turn, influence physical processes. This feedback creates challenges for forecasting and inference, creating the potential for complementarity between models from different academic disciplines. Using the example of prediction of water availability during a drought, we illustrate the potential biases in forecasts that only take part of a coupled system into account. In particular, we show that forecasts can alter the feedbacks between supply and demand, leading to inaccurate prediction about future states of the system. Although the example is specific to drought, the problem of feedback between expectations and forecast quality is not isolated to the particular model-it is relevant to areas as diverse as population assessments for conservation, balancing the electrical grid, and setting macroeconomic policy.

  18. Flood Forecasting in River System Using ANFIS

    NASA Astrophysics Data System (ADS)

    Ullah, Nazrin; Choudhury, P.

    2010-10-01

    The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.

  19. A global flash flood forecasting system

    NASA Astrophysics Data System (ADS)

    Baugh, Calum; Pappenberger, Florian; Wetterhall, Fredrik; Hewson, Tim; Zsoter, Ervin

    2016-04-01

    The sudden and devastating nature of flash flood events means it is imperative to provide early warnings such as those derived from Numerical Weather Prediction (NWP) forecasts. Currently such systems exist on basin, national and continental scales in Europe, North America and Australia but rely on high resolution NWP forecasts or rainfall-radar nowcasting, neither of which have global coverage. To produce global flash flood forecasts this work investigates the possibility of using forecasts from a global NWP system. In particular we: (i) discuss how global NWP can be used for flash flood forecasting and discuss strengths and weaknesses; (ii) demonstrate how a robust evaluation can be performed given the rarity of the event; (iii) highlight the challenges and opportunities in communicating flash flood uncertainty to decision makers; and (iv) explore future developments which would significantly improve global flash flood forecasting. The proposed forecast system uses ensemble surface runoff forecasts from the ECMWF H-TESSEL land surface scheme. A flash flood index is generated using the ERIC (Enhanced Runoff Index based on Climatology) methodology [Raynaud et al., 2014]. This global methodology is applied to a series of flash floods across southern Europe. Results from the system are compared against warnings produced using the higher resolution COSMO-LEPS limited area model. The global system is evaluated by comparing forecasted warning locations against a flash flood database of media reports created in partnership with floodlist.com. To deal with the lack of objectivity in media reports we carefully assess the suitability of different skill scores and apply spatial uncertainty thresholds to the observations. To communicate the uncertainties of the flash flood system output we experiment with a dynamic region-growing algorithm. This automatically clusters regions of similar return period exceedence probabilities, thus presenting the at-risk areas at a spatial

  20. Operational foreshock forecasting: Fifteen years after

    NASA Astrophysics Data System (ADS)

    Ogata, Y.

    2010-12-01

    We are concerned with operational forecasting of the probability that events are foreshocks of a forthcoming earthquake that is significantly larger (mainshock). Specifically, we define foreshocks as the preshocks substantially smaller than the mainshock by a magnitude gap of 0.5 or larger. The probability gain of foreshock forecast is extremely high compare to long-term forecast by renewal processes or various alarm-based intermediate-term forecasts because of a large event’s low occurrence rate in a short period and a narrow target region. Thus, it is desired to establish operational foreshock probability forecasting as seismologists have done for aftershocks. When a series of earthquakes occurs in a region, we attempt to discriminate foreshocks from a swarm or mainshock-aftershock sequence. Namely, after real time identification of an earthquake cluster using methods such as the single-link algorithm, the probability is calculated by applying statistical features that discriminate foreshocks from other types of clusters, by considering the events' stronger proximity in time and space and tendency towards chronologically increasing magnitudes. These features were modeled for probability forecasting and the coefficients of the model were estimated in Ogata et al. (1996) for the JMA hypocenter data (M≧4, 1926-1993). Currently, fifteen years has passed since the publication of the above-stated work so that we are able to present the performance and validation of the forecasts (1994-2009) by using the same model. Taking isolated events into consideration, the probability of the first events in a potential cluster being a foreshock vary in a range between 0+% and 10+% depending on their locations. This conditional forecasting performs significantly better than the unconditional (average) foreshock probability of 3.7% throughout Japan region. Furthermore, when we have the additional events in a cluster, the forecast probabilities range more widely from nearly 0% to

  1. Why Don't We Learn to Accurately Forecast Feelings? How Misremembering Our Predictions Blinds Us to Past Forecasting Errors

    ERIC Educational Resources Information Center

    Meyvis, Tom; Ratner, Rebecca K.; Levav, Jonathan

    2010-01-01

    Why do affective forecasting errors persist in the face of repeated disconfirming evidence? Five studies demonstrate that people misremember their forecasts as consistent with their experience and thus fail to perceive the extent of their forecasting error. As a result, people do not learn from past forecasting errors and fail to adjust subsequent…

  2. Multi-model seasonal forecast of Arctic sea-ice: forecast uncertainty at pan-Arctic and regional scales

    NASA Astrophysics Data System (ADS)

    Blanchard-Wrigglesworth, E.; Barthélemy, A.; Chevallier, M.; Cullather, R.; Fučkar, N.; Massonnet, F.; Posey, P.; Wang, W.; Zhang, J.; Ardilouze, C.; Bitz, C. M.; Vernieres, G.; Wallcraft, A.; Wang, M.

    2016-10-01

    Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or forecast post-processing (bias correction) techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

  3. Influenza Forecasting with Google Flu Trends

    PubMed Central

    Dugas, Andrea Freyer; Jalalpour, Mehdi; Gel, Yulia; Levin, Scott; Torcaso, Fred; Igusa, Takeru; Rothman, Richard E.

    2013-01-01

    Background We developed a practical influenza forecast model based on real-time, geographically focused, and easy to access data, designed to provide individual medical centers with advanced warning of the expected number of influenza cases, thus allowing for sufficient time to implement interventions. Secondly, we evaluated the effects of incorporating a real-time influenza surveillance system, Google Flu Trends, and meteorological and temporal information on forecast accuracy. Methods Forecast models designed to predict one week in advance were developed from weekly counts of confirmed influenza cases over seven seasons (2004–2011) divided into seven training and out-of-sample verification sets. Forecasting procedures using classical Box-Jenkins, generalized linear models (GLM), and generalized linear autoregressive moving average (GARMA) methods were employed to develop the final model and assess the relative contribution of external variables such as, Google Flu Trends, meteorological data, and temporal information. Results A GARMA(3,0) forecast model with Negative Binomial distribution integrating Google Flu Trends information provided the most accurate influenza case predictions. The model, on the average, predicts weekly influenza cases during 7 out-of-sample outbreaks within 7 cases for 83% of estimates. Google Flu Trend data was the only source of external information to provide statistically significant forecast improvements over the base model in four of the seven out-of-sample verification sets. Overall, the p-value of adding this external information to the model is 0.0005. The other exogenous variables did not yield a statistically significant improvement in any of the verification sets. Conclusions Integer-valued autoregression of influenza cases provides a strong base forecast model, which is enhanced by the addition of Google Flu Trends confirming the predictive capabilities of search query based syndromic surveillance. This accessible and

  4. Maintaining Realistic Uncertainty in Model and Forecast

    DTIC Science & Technology

    2000-09-30

    Maintaining Realistic Uncertainty in Model and Forecast Leonard Smith Pembroke College Oxford University St. Aldates Oxford OX1 1DW United Kingdom...5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Pembroke College, Oxford University ,,St...evaluation: l-shadowing, probabilistic prediction and weather forecasting. D.Phil Thesis, Oxford University . Lorenz, E. (1995) Predictability-a Partially

  5. Forecasting Tools Point to Fishing Hotspots

    NASA Technical Reports Server (NTRS)

    2009-01-01

    Private weather forecaster WorldWinds Inc. of Slidell, Louisiana has employed satellite-gathered oceanic data from Marshall Space Flight Center to create a service that is every fishing enthusiast s dream. The company's FishBytes system uses information about sea surface temperature and chlorophyll levels to forecast favorable conditions for certain fish populations. Transmitting the data to satellite radio subscribers, FishBytes provides maps that guide anglers to the areas they are most likely to make their favorite catch.

  6. Multispectral satellite training for inexperienced Navy forecasters

    NASA Astrophysics Data System (ADS)

    Kuciauskas, Arunas P.; Lee, Thomas F.; Durkee, Philip A.; Ledesma, Roy

    2004-10-01

    Recent advancements of meteorology and oceanography (METOC) satellite products has resulted from a surge in computing resources and expanded communications via the Internet. Greater tactical demands in military operations are placed on Navy and Marine METOC personnel to provide better atmospheric depictions and forecasts in support of helicopter, fighter jet and ground troop operations, as was experienced in Operation Enduring Freedom and Operation Iraqi Freedom. Unfortunately, US military weather forecasters are often limited in their abilities to provide state of the art products and forecasts. One reason for these inefficiencies are that oftentimes, daily forecasting tasks are left to non-commissioned personnel (e.g., AG"s and ET"s) who receive little or no classroom training in this area, nor are there continuing education/training available. METOC forecast centers vary greatly and might not have access to the appropriate information base to answer ongoing questions. Additionally, the typical tour of duty at a particular forecast center is 2 years, resulting in a stressful environment to bring new forecasters up to speed in demanding forecast operations. The result is that the user is often confined to image looping and basic image enhancements to convey the general environmental conditions over the region of interest. To facilitate the learning process, the Naval Research Laboratory and the Naval Postgraduate School have developed a 3 day intensive laboratory and lecture course in satellite remote sensing, focusing on topics vital to military operations such as smoke and fire detection, coastal maritime layer analysis, snow, fog, haze, tropical cyclones, hazardous wind conditions, etc. A wealth of satellite data is provided from MODIS, AVHRR, DMSP and Geostationary satellite data. Background satellite remote sensing topics such as radiative transfer theory is also presented. This report presents a sample of the material used within the training.

  7. CBO’s Revenue Forecasting Record

    DTIC Science & Technology

    2015-11-01

    Forecasts 10 Efficient Use of New Information 12 Some Sources of Forecast Error 12 Errors Related to the Size of the Economy 13 Errors Attributable to...Other Factors 14 Errors Attributable to Misestimates of the Size of the Economy Versus Other Factors 14 Interactions Between Misestimates of GDP and...is a small sample size given the variability of economic per- formance and the many different factors in the economy that interact with one another to

  8. Solar Energy Forecast System Development and Implementation

    NASA Astrophysics Data System (ADS)

    Jascourt, S. D.; Kirk-Davidoff, D. B.; Cassidy, C.

    2012-12-01

    Forecast systems for predicting real-time solar energy generation are being developed along similar lines to those of more established wind forecast systems, but the challenges and constraints are different. Clouds and aerosols play a large role, and for tilted photovoltaic panels and solar concentrating plants, the direct beam irradiance, which typically has much larger forecast errors than global horizontal irradiance, must be utilized. At MDA Information Systems, we are developing a forecast system based on first principles, with the well-validated REST2 clear sky model (Gueymard, 2008) at its backbone. In tuning the model and addressing aerosol scattering and surface albedo, etc., we relied upon the wealth of public data sources including AERONET (aerosol optical depth at different wavelengths), Suominet (GPS integrated water vapor), NREL MIDC solar monitoring stations, SURFRAD (includes upwelling shortwave), and MODIS (albedo in different wavelength bands), among others. The forecast itself utilizes a blend of NWP model output, which must be brought down to finer time resolution based on the diurnal cycle rather than simple interpolation. Many models currently do not output the direct beam irradiance, and one that does appears to have a bias relative to its global horizontal irradiance, with equally good performance attained by utilizing REST2 and the model global radiation to estimate the direct component. We will present a detailed assessment of various NWP solar energy products, evaluating forecast skill at a range of photovoltaic installations.

  9. Nonlinear forecasting of intertidal shoreface evolution

    NASA Astrophysics Data System (ADS)

    Grimes, D. J.; Cortale, N.; Baker, K.; McNamara, D. E.

    2015-10-01

    Natural systems dominated by sediment transport are notoriously difficult to forecast. This is particularly true along the ocean coastline, a region that draws considerable human attention as economic investment and infrastructure are threatened by both persistent, long-term and acute, event driven processes (i.e., sea level rise and storm damage, respectively). Forecasting the coastline's evolution over intermediate time (daily) and space (tens of meters) scales is hindered by the complexity of sediment transport and hydrodynamics, and limited access to the detailed local forcing that drives fast scale processes. Modern remote sensing systems provide an efficient, economical means to collect data within these regions. A solar-powered digital camera installation is used to capture the coast's evolution, and machine learning algorithms are implemented to extract the shoreline and estimate the daily mean intertidal coastal profile. Methods in nonlinear time series forecasting and genetic programming applied to these data corroborate that coastal morphology at these scales is predominately driven by nonlinear internal dynamics, which partially mask external forcing signatures. Results indicate that these forecasting techniques achieve nontrivial predictive skill for spatiotemporal forecast of the upper coastline profile (as much as 43% of variance in data explained for one day predictions). This analysis provides evidence that societally relevant coastline forecasts can be achieved without knowing the forcing environment or the underlying dynamical equations that govern coastline evolution.

  10. Weather Forecaster Understanding of Climate Models

    NASA Astrophysics Data System (ADS)

    Bol, A.; Kiehl, J. T.; Abshire, W. E.

    2013-12-01

    Weather forecasters, particularly those in broadcasting, are the primary conduit to the public for information on climate and climate change. However, many weather forecasters remain skeptical of model-based climate projections. To address this issue, The COMET Program developed an hour-long online lesson of how climate models work, targeting an audience of weather forecasters. The module draws on forecasters' pre-existing knowledge of weather, climate, and numerical weather prediction (NWP) models. In order to measure learning outcomes, quizzes were given before and after the lesson. Preliminary results show large learning gains. For all people that took both pre and post-tests (n=238), scores improved from 48% to 80%. Similar pre/post improvement occurred for National Weather Service employees (51% to 87%, n=22 ) and college faculty (50% to 90%, n=7). We believe these results indicate a fundamental misunderstanding among many weather forecasters of (1) the difference between weather and climate models, (2) how researchers use climate models, and (3) how they interpret model results. The quiz results indicate that efforts to educate the public about climate change need to include weather forecasters, a vital link between the research community and the general public.

  11. Analogue Downscaling of Seasonal Rainfall Forecasts

    NASA Astrophysics Data System (ADS)

    Charles, A. N.; Timbal, B.; Hendon, H.

    2010-12-01

    We have taken an existing statistical downscaling model (SDM), based on meteorological analogues that was developed for downscaling climate change projections (Timbal et al 2009), and applied it in the seasonal forecasting context to produce downscaled rainfall hindcasts from a coupled model seasonal forecast system (POAMA). Downscaling of POAMA forecasts is required to provide seasonal climate information at local scales of interest. Analogue downscaling is a simple technique to generate rainfall forecasts appropriate to the local scale by conditioning on the large scale predicted GCM circulation and the local topography and climate. Analogue methods are flexible and have been shown to produce good results when downscaling 20th century South Eastern Australian rainfall output from climate models. A set of re-forecasts for three month rainfall at 170 observing stations in the South Murray Darling region of Australia were generated using predictors from the POAMA re-forecasts as input for the analogue SDM. The predictors were optimised over a number of different GCMS in previous climate change downscaling studies. Downscaling with the analogue SDM results in predicted rainfall with realistic variance while maintaining the modest predictive skill of the dynamical model. Evaluation of the consistency between the large scale mean of downscaled and direct GCM output precipitation is encouraging.

  12. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect

    Brainard, James Robert

    2009-10-01

    This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

  13. Radar Based Precipitation Forecasting for Flood Warning

    NASA Astrophysics Data System (ADS)

    Chen, Y.

    2007-12-01

    Precipitation is one of the most important inputs for flood warning. The accuracy of the measured precipitation controls the effectiveness of flood warning, while the forecasted precipitation increases the lead time of flood warning, this is vital for catastrophically flood warning as it provides time for flood management, such as the emergency evacuation of the people and properties within the flood prone area, so to avoid flood damages. This paper presents an algorithm for forecasting precipitation based on Chinese next generation weather radar- CINRAD for catastrophically flood warning. This algorithm includes radar data quality control, precipitation estimation and forecasting, result correction. The radar data, received at every 5-6 minutes, is quality controlled first to delete the data noises, the pre-processed radar data then is used to estimate the precipitation, which will be employed to calibrate the radar equation parameters, then the pre-processed radar data and calibrated radar equation parameters will be input to the precipitation procedure to forecast precipitation. A software based on the above algorithm is developed that can be used to forecast precipitation on real ¡§Ctime. The radar in Guangzhou city, the biggest city in southern China is studied and the precipitation in 2005 and 2006 in Liuxihe River Basin in southern China were forecasted to validate the effectiveness, the results show this algorithm is encouraging and will be put into real-time operation in the flood warning of Liuxihe River in 2007.

  14. Nonlinear forecasting of intertidal shoreface evolution.

    PubMed

    Grimes, D J; Cortale, N; Baker, K; McNamara, D E

    2015-10-01

    Natural systems dominated by sediment transport are notoriously difficult to forecast. This is particularly true along the ocean coastline, a region that draws considerable human attention as economic investment and infrastructure are threatened by both persistent, long-term and acute, event driven processes (i.e., sea level rise and storm damage, respectively). Forecasting the coastline's evolution over intermediate time (daily) and space (tens of meters) scales is hindered by the complexity of sediment transport and hydrodynamics, and limited access to the detailed local forcing that drives fast scale processes. Modern remote sensing systems provide an efficient, economical means to collect data within these regions. A solar-powered digital camera installation is used to capture the coast's evolution, and machine learning algorithms are implemented to extract the shoreline and estimate the daily mean intertidal coastal profile. Methods in nonlinear time series forecasting and genetic programming applied to these data corroborate that coastal morphology at these scales is predominately driven by nonlinear internal dynamics, which partially mask external forcing signatures. Results indicate that these forecasting techniques achieve nontrivial predictive skill for spatiotemporal forecast of the upper coastline profile (as much as 43% of variance in data explained for one day predictions). This analysis provides evidence that societally relevant coastline forecasts can be achieved without knowing the forcing environment or the underlying dynamical equations that govern coastline evolution.

  15. Seismic Forecasting of Solar Activity

    NASA Technical Reports Server (NTRS)

    Braun, Douglas; Lindsey, Charles

    2001-01-01

    We have developed and improved helioseismic imaging techniques of the far-side of the Sun as part of a synoptic monitor of solar activity. In collaboration with the MIDI team at Stanford University we are routinely applying our analysis to images within 24 hours of their acquisition by SOHO. For the first time, real-time seismic maps of large active regions on the Sun's far surface are publicly available. The synoptic images show examples of active regions persisting for one or more solar rotations, as well as those initially detected forming on the solar far side. Until recently, imaging the far surface of the Sun has been essentially blind to active regions more than about 50 degrees from the antipode of disk center. In a paper recently accepted for publication, we have demonstrated how acoustic travel-time perturbations may be mapped over the entire hemisphere of the Sun facing away from the Earth, including the polar regions. In addition to offering significant improvements to ongoing space weather forecasting efforts, the procedure offers the possibility of local seismic monitoring of both the temporal and spatial variations in the acoustic properties of the Sun over the entire far surface.

  16. Scintillation Forecasting Using NPOESS Data

    NASA Astrophysics Data System (ADS)

    Basu, B.; Retterer, J.; Demajistre, R.; de La Beaujardiere, O.; Scro, K.

    2005-12-01

    We have conducted a theoretical study of the use of NPOESS data for the forecasting of equatorial radio scintillation using knowledge of the equatorial Appleton anomaly, e.g., the peak-to-valley ratio of TEC (Total Electron Content) between the anomaly crests and the magnetic equator. The peak-to-valley ratio can be obtained from the UV (ultraviolet) imagery of the anomaly region that will be provided by the NPOESS sensors. The post-sunset enhancement of the upward drift velocity of the equatorial plasma has been shown, both theoretically and observationally, to be an important determinant of both the onset of scintillation and the strength of the anomaly. The technical approach is to run PBMOD, the AFRL low-latitude ionosphere model, with a range of post-sunset vertical drift velocities to determine the quantitative relationship between the peak-to-valley ratio and the maximum value of the pot-sunset upward drift velocity of equatorial plasma. Once the relationship is validated, it will be used to estimate the maximum value of the drift velocity from the peak-to-valley ratio, which is derived from the UV imagery data provided by NPOESS-like sensor, such as GUVI on TIMED satellite. The drift velocity will then be used in PBMOD to simulate the formation and evolution of equatorial plasma `bubbles' and calculate the distribution of the amplitude scintillation index S4. Results of the study will be discussed.

  17. Monitoring and seasonal forecasting of meteorological droughts

    NASA Astrophysics Data System (ADS)

    Dutra, Emanuel; Pozzi, Will; Wetterhall, Fredrik; Di Giuseppe, Francesca; Magnusson, Linus; Naumann, Gustavo; Barbosa, Paulo; Vogt, Jurgen; Pappenberger, Florian

    2015-04-01

    Near-real time drought monitoring can provide decision makers valuable information for use in several areas, such as water resources management, or international aid. Unfortunately, a major constraint in current drought outlooks is the lack of reliable monitoring capability for observed precipitation globally in near-real time. Furthermore, drought monitoring systems requires a long record of past observations to provide mean climatological conditions. We address these constraints by developing a novel drought monitoring approach in which monthly mean precipitation is derived from short-range using ECMWF probabilistic forecasts and then merged with the long term precipitation climatology of the Global Precipitation Climatology Centre (GPCC) dataset. Merging the two makes available a real-time global precipitation product out of which the Standardized Precipitation Index (SPI) can be estimated and used for global or regional drought monitoring work. This approach provides stability in that by-passes problems of latency (lags) in having local rain-gauge measurements available in real time or lags in satellite precipitation products. Seasonal drought forecasts can also be prepared using the common methodology and based upon two data sources used to provide initial conditions (GPCC and the ECMWF ERA-Interim reanalysis (ERAI) combined with either the current ECMWF seasonal forecast or a climatology based upon ensemble forecasts. Verification of the forecasts as a function of lead time revealed a reduced impact on skill for: (i) long lead times using different initial conditions, and (ii) short lead times using different precipitation forecasts. The memory effect of initial conditions was found to be 1 month lead time for the SPI-3, 3 to 4 months for the SPI-6 and 5 months for the SPI-12. Results show that dynamical forecasts of precipitation provide added value, a skill similar to or better than climatological forecasts. In some cases, particularly for long SPI time

  18. Total probabilities of ensemble runoff forecasts

    NASA Astrophysics Data System (ADS)

    Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

    2016-04-01

    Ensemble forecasting has for a long time been used as a method in meteorological modelling to indicate the uncertainty of the forecasts. However, as the ensembles often exhibit both bias and dispersion errors, it is necessary to calibrate and post-process them. Two of the most common methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). Engeland and Steinsland Engeland and Steinsland (2014) developed a framework which can estimate post-processing parameters which are different in space and time, but still can give a spatially and temporally consistent output. However, their method is computationally complex for our larger number of stations, and cannot directly be regionalized in the way we would like, so we suggest a different path below. The target of our work is to create a mean forecast with uncertainty bounds for a large number of locations in the framework of the European Flood Awareness System (EFAS - http://www.efas.eu) We are therefore more interested in improving the forecast skill for high-flows rather than the forecast skill of lower runoff levels. EFAS uses a combination of ensemble forecasts and deterministic forecasts from different forecasters to force a distributed hydrologic model and to compute runoff ensembles for each river pixel within the model domain. Instead of showing the mean and the variability of each forecast ensemble individually, we will now post-process all model outputs to find a total probability, the post-processed mean and uncertainty of all ensembles. The post-processing parameters are first calibrated for each calibration location, but assuring that they have some spatial correlation, by adding a spatial penalty in the calibration process. This can in some cases have a slight negative

  19. More intense experiences, less intense forecasts: why people overweight probability specifications in affective forecasts.

    PubMed

    Buechel, Eva C; Zhang, Jiao; Morewedge, Carey K; Vosgerau, Joachim

    2014-01-01

    We propose that affective forecasters overestimate the extent to which experienced hedonic responses to an outcome are influenced by the probability of its occurrence. The experience of an outcome (e.g., winning a gamble) is typically more affectively intense than the simulation of that outcome (e.g., imagining winning a gamble) upon which the affective forecast for it is based. We suggest that, as a result, experiencers allocate a larger share of their attention toward the outcome (e.g., winning the gamble) and less to its probability specifications than do affective forecasters. Consequently, hedonic responses to an outcome are less sensitive to its probability specifications than are affective forecasts for that outcome. The results of 6 experiments provide support for our theory. Affective forecasters overestimated how sensitive experiencers would be to the probability of positive and negative outcomes (Experiments 1 and 2). Consistent with our attentional account, differences in sensitivity to probability specifications disappeared when the attention of forecasters was diverted from probability specifications (Experiment 3) or when the attention of experiencers was drawn toward probability specifications (Experiment 4). Finally, differences in sensitivity to probability specifications between forecasters and experiencers were diminished when the forecasted outcome was more affectively intense (Experiments 5 and 6).

  20. Uncertainty Forecasts Improve Weather-Related Decisions and Attenuate the Effects of Forecast Error

    ERIC Educational Resources Information Center

    Joslyn, Susan L.; LeClerc, Jared E.

    2012-01-01

    Although uncertainty is inherent in weather forecasts, explicit numeric uncertainty estimates are rarely included in public forecasts for fear that they will be misunderstood. Of particular concern are situations in which precautionary action is required at low probabilities, often the case with severe events. At present, a categorical weather…

  1. Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting: Preprint

    SciTech Connect

    Zhang, J.; Florita, A.; Hodge, B. M.; Freedman, J.

    2014-05-01

    The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.

  2. More Intense Experiences, Less Intense Forecasts: Why People Overweight Probability Specifications in Affective Forecasts

    PubMed Central

    Buechel, Eva C.; Zhang, Jiao; Morewedge, Carey K.; Vosgerau, Joachim

    2014-01-01

    We propose that affective forecasters overestimate the extent to which experienced hedonic responses to an outcome are influenced by the probability of its occurrence. The experience of an outcome (e.g., winning a gamble) is typically more affectively intense than the simulation of that outcome (e.g., imagining winning a gamble) upon which the affective forecast for it is based. We suggest that, as a result, experiencers allocate a larger share of their attention toward the outcome (e.g., winning the gamble) and less to its probability specifications than do affective forecasters. Consequently, hedonic responses to an outcome are less sensitive to its probability specifications than are affective forecasts for that outcome. The results of 6 experiments provide support for our theory. Affective forecasters overestimated how sensitive experiencers would be to the probability of positive and negative outcomes (Experiments 1 and 2). Consistent with our attentional account, differences in sensitivity to probability specifications disappeared when the attention of forecasters was diverted from probability specifications (Experiment 3) or when the attention of experiencers was drawn toward probability specifications (Experiment 4). Finally, differences in sensitivity to probability specifications between forecasters and experiencers were diminished when the forecasted outcome was more affectively intense (Experiments 5 and 6). PMID:24128184

  3. Pollen Forecast and Dispersion Modelling

    NASA Astrophysics Data System (ADS)

    Costantini, Monica; Di Giuseppe, Fabio; Medaglia, Carlo Maria; Travaglini, Alessandro; Tocci, Raffaella; Brighetti, M. Antonia; Petitta, Marcello

    2014-05-01

    The aim of this study is monitoring, mapping and forecast of pollen distribution for the city of Rome using in-situ measurements of 10 species of common allergenic pollens and measurements of PM10. The production of daily concentration maps, associated to a mobile phone app, are innovative compared to existing dedicated services to people who suffer from respiratory allergies. The dispersal pollen is one of the most well-known causes of allergic disease that is manifested by disorders of the respiratory functions. Allergies are the third leading cause of chronic disease and it is estimated that tens millions of people in Italy suffer from it. Recent works reveal that during the last few years there was a progressive increase of affected subjects, especially in urban areas. This situation may depend: on the ability to transport of pollutants, on the ability to react between pollutants and pollen and from a combination of other irritants, existing in densely populated and polluted urban areas. The methodology used to produce maps is based on in-situ measurements time series relative to 2012, obtained from networks of air quality and pollen stations in the metropolitan area of Rome. The monitoring station aerobiological of University of Rome "Tor Vergata" is located at the Department of Biology. The instrument used to pollen monitoring is a volumetric sampler type Hirst (Hirst 1952), Model 2000 VPPS Lanzoni; the data acquisition is carried out as reported in Standard UNI 11008:2004 - "Qualità dell'aria - Metodo di campionamento e conteggio dei granuli pollinici e delle spore fungine aerodisperse" - the protocol that describes the procedure for measuring of the concentration of pollen grains and fungal spores dispersed into the atmosphere, and reported in the "Manuale di gestione e qualità della R.I.M.A" (Travaglini et. al. 2009). All 10 allergenic pollen are monitored since 1996. At Tor Vergata university is also operating a meteorological station (SP2000, CAE

  4. The Invasive Species Forecasting System

    NASA Technical Reports Server (NTRS)

    Schnase, John; Most, Neal; Gill, Roger; Ma, Peter

    2011-01-01

    The Invasive Species Forecasting System (ISFS) provides computational support for the generic work processes found in many regional-scale ecosystem modeling applications. Decision support tools built using ISFS allow a user to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of management concern, such as a national park, monument, forest, or refuge. This type of decision product helps resource managers plan invasive species protection, monitoring, and control strategies for the lands they manage. Until now, scientists and resource managers have lacked the data-assembly and computing capabilities to produce these maps quickly and cost efficiently. ISFS focuses on regional-scale habitat suitability modeling for invasive terrestrial plants. ISFS s component architecture emphasizes simplicity and adaptability. Its core services can be easily adapted to produce model-based decision support tools tailored to particular parks, monuments, forests, refuges, and related management units. ISFS can be used to build standalone run-time tools that require no connection to the Internet, as well as fully Internet-based decision support applications. ISFS provides the core data structures, operating system interfaces, network interfaces, and inter-component constraints comprising the canonical workflow for habitat suitability modeling. The predictors, analysis methods, and geographic extents involved in any particular model run are elements of the user space and arbitrarily configurable by the user. ISFS provides small, lightweight, readily hardened core components of general utility. These components can be adapted to unanticipated uses, are tailorable, and require at most a loosely coupled, nonproprietary connection to the Web. Users can invoke capabilities from a command line; programmers can integrate ISFS's core components into more complex systems and services. Taken together, these

  5. 1994 Solid waste forecast container volume summary

    SciTech Connect

    Templeton, K.J.; Clary, J.L.

    1994-09-01

    This report describes a 30-year forecast of the solid waste volumes by container type. The volumes described are low-level mixed waste (LLMW) and transuranic/transuranic mixed (TRU/TRUM) waste. These volumes and their associated container types will be generated or received at the US Department of Energy Hanford Site for storage, treatment, and disposal at Westinghouse Hanford Company`s Solid Waste Operations Complex (SWOC) during a 30-year period from FY 1994 through FY 2023. The forecast data for the 30-year period indicates that approximately 307,150 m{sup 3} of LLMW and TRU/TRUM waste will be managed by the SWOC. The main container type for this waste is 55-gallon drums, which will be used to ship 36% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of 55-gallon drums is Past Practice Remediation. This waste will be generated by the Environmental Restoration Program during remediation of Hanford`s past practice sites. Although Past Practice Remediation is the primary generator of 55-gallon drums, most waste generators are planning to ship some percentage of their waste in 55-gallon drums. Long-length equipment containers (LECs) are forecasted to contain 32% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of LECs is the Long-Length Equipment waste generator, which is responsible for retrieving contaminated long-length equipment from the tank farms. Boxes are forecasted to contain 21% of the waste. These containers are primarily forecasted for use by the Environmental Restoration Operations--D&D of Surplus Facilities waste generator. This waste generator is responsible for the solid waste generated during decontamination and decommissioning (D&D) of the facilities currently on the Surplus Facilities Program Plan. The remaining LLMW and TRU/TRUM waste volume is planned to be shipped in casks and other miscellaneous containers.

  6. Automated time series forecasting for biosurveillance.

    PubMed

    Burkom, Howard S; Murphy, Sean Patrick; Shmueli, Galit

    2007-09-30

    For robust detection performance, traditional control chart monitoring for biosurveillance is based on input data free of trends, day-of-week effects, and other systematic behaviour. Time series forecasting methods may be used to remove this behaviour by subtracting forecasts from observations to form residuals for algorithmic input. We describe three forecast methods and compare their predictive accuracy on each of 16 authentic syndromic data streams. The methods are (1) a non-adaptive regression model using a long historical baseline, (2) an adaptive regression model with a shorter, sliding baseline, and (3) the Holt-Winters method for generalized exponential smoothing. Criteria for comparing the forecasts were the root-mean-square error, the median absolute per cent error (MedAPE), and the median absolute deviation. The median-based criteria showed best overall performance for the Holt-Winters method. The MedAPE measures over the 16 test series averaged 16.5, 11.6, and 9.7 for the non-adaptive regression, adaptive regression, and Holt-Winters methods, respectively. The non-adaptive regression forecasts were degraded by changes in the data behaviour in the fixed baseline period used to compute model coefficients. The mean-based criterion was less conclusive because of the effects of poor forecasts on a small number of calendar holidays. The Holt-Winters method was also most effective at removing serial autocorrelation, with most 1-day-lag autocorrelation coefficients below 0.15. The forecast methods were compared without tuning them to the behaviour of individual series. We achieved improved predictions with such tuning of the Holt-Winters method, but practical use of such improvements for routine surveillance will require reliable data classification methods.

  7. Air Quality Forecast Verification using Satellite Data

    NASA Astrophysics Data System (ADS)

    Kondragunta, S.; Lee, P.; McQueen, J.; Kittaka, C.; Prados, A.; Ciren, P.; Laszlo, I.; Pierce, R. B.; Hoff, R.; Szykman, J. J.

    2006-05-01

    NOAA's operational geostationary satellite retrievals of aerosol optical depths (AODs) were used to verify National Weather Service (NWS) developmental (research mode) particulate matter (PM2.5) predictions tested during the summer 2004 International Consortium for Atmospheric Research on Transport and Transformation/New England Air Quality Study (ICARTT/NEAQS) field campaign. The forecast period was encompassed by long range transport of smoke from fires burning in Canada and Alaska and a regional-scale sulfate event over the Gulf of Mexico and the eastern United States (U.S). Over the 30-day time period for which daytime hourly forecasts were compared to observations, the categorical (event defined as AOD greater than 0.65) forecast accuracy was between 60% and 99% with a mean of ~80%. Hourly normalized mean bias (forecasts -" observations) ranged between -50% and +50% with forecasts being biased high when observed AODs were small and biased low when observed AODs were high. Normalized Mean Errors are between 50% and 100% with the errors on the lower end during July 18-22, 2004 time period when a regional scale sulfate event occurred. Spatially, the errors are small over the regions where sulfate plumes were present. The correlation coefficient (r) also showed similar features (spatially and temporally) with a peak value of ~0.6 during July 18-22, 2004 time period. The dominance of long-range transport of smoke into the US during the summer of 2004, neglected in the model predictions, skewed the model forecast performance. Enhanced accuracy and reduced normalized mean errors during the time period when a sulfate event prevailed shows that the forecast system is capable of skill in predicting PM2.5 associated with urban/industrial pollution events.

  8. On the assessment of reliability in probabilistic hydrometeorological event forecasting

    NASA Astrophysics Data System (ADS)

    DeChant, Caleb M.; Moradkhani, Hamid

    2015-06-01

    Probabilistic forecasts are commonly used to communicate uncertainty in the occurrence of hydrometeorological events. Although probabilistic forecasting is common, conventional methods for assessing the reliability of these forecasts are approximate. Among the most common methods for assessing reliability, the decomposed Brier Score and Reliability Diagram treat an observed string of events as samples from multiple Binomial distributions, but this is an approximation of the forecast reliability, leading to unnecessary loss of information. This article suggests testing the hypothesis of reliability via the Poisson-Binomial distribution, which is a generalized solution to the Binomial distribution, providing a more accurate model of the probabilistic event forecast verification setting. Further, a two-stage approach to reliability assessment is suggested to identify errors in the forecast related to both bias and overly/insufficiently sharp forecasts. Such a methodology is shown to more effectively distinguish between reliable and unreliable forecasts, leading to more robust probabilistic forecast verification.

  9. An alternate approach to ensemble ENSO forecast spread: Application to the 2014 forecast

    NASA Astrophysics Data System (ADS)

    Larson, Sarah M.; Kirtman, Ben P.

    2015-11-01

    Evaluating the 2014 El Niño forecast as a "bust" may be tapping into a bigger issue, namely that forecast "overconfidence" from single-model ensembles could affect the retrospective assessment of El Niño-Southern Oscillation (ENSO) predictions. The present study proposes a new approach to quantifying an "expected" spread and uncertainty from noise-driven processes and supplementing these measures with actual ENSO forecasts. Expanding on a previously developed coupled model framework that isolates noise-driven ENSO-like errors, an experimental design is implemented to generate an expected December Niño-3.4 spread from March initial condition sea surface temperature errors that have similar structure to the 2014 and 2015 observed. Results reveal that the 2014 ENSO forecast falls within the expected uncertainty generated by ENSO-independent, forecast-independent, noise-driven errors.

  10. Seasonal Water Balance Forecasts for Drought Early Warning in Ethiopia

    NASA Astrophysics Data System (ADS)

    Spirig, Christoph; Bhend, Jonas; Liniger, Mark

    2016-04-01

    Droughts severely impact Ethiopian agricultural production. Successful early warning for drought conditions in the upcoming harvest season therefore contributes to better managing food shortages arising from adverse climatic conditions. So far, however, meteorological seasonal forecasts have not been used in Ethiopia's national food security early warning system (i.e. the LEAP platform). Here we analyse the forecast quality of seasonal forecasts of total rainfall and of the meteorological water balance as a proxy for plant available water. We analyse forecast skill of June to September rainfall and water balance from dynamical seasonal forecast systems, the ECMWF System4 and EC-EARTH global forecasting systems. Rainfall forecasts outperform forecasts assuming a stationary climate mainly in north-eastern Ethiopia - an area that is particularly vulnerable to droughts. Forecasts of the water balance index seem to be even more skilful and thus more useful than pure rainfall forecasts. The results vary though for different lead times and skill measures employed. We further explore the potential added value of dynamically downscaling the forecasts through several dynamical regional climate models made available through the EU FP7 project EUPORIAS. Preliminary results suggest that dynamically downscaled seasonal forecasts are not significantly better compared with seasonal forecasts from the global models. We conclude that seasonal forecasts of a simple climate index such as the water balance have the potential to benefit drought early warning in Ethiopia, both due to its positive predictive skill and higher usefulness than seasonal mean quantities.

  11. Flood forecasting in Niger-Benue basin using satellite and quantitative precipitation forecast data

    NASA Astrophysics Data System (ADS)

    Haile, Alemseged Tamiru; Tefera, Fekadu Teshome; Rientjes, Tom

    2016-10-01

    Availability of reliable, timely and accurate rainfall data is constraining the establishment of flood forecasting and early warning systems in many parts of Africa. We evaluated the potential of satellite and weather forecast data as input to a parsimonious flood forecasting model to provide information for flood early warning in the central part of Nigeria. We calibrated the HEC-HMS rainfall-runoff model using rainfall data from post real time Tropical Rainfall Measuring Mission (TRMM) Multi satellite Precipitation Analysis product (TMPA). Real time TMPA satellite rainfall estimates and European Centre for Medium-Range Weather Forecasts (ECMWF) rainfall products were tested for flood forecasting. The implication of removing the systematic errors of the satellite rainfall estimates (SREs) was explored. Performance of the rainfall-runoff model was assessed using visual inspection of simulated and observed hydrographs and a set of performance indicators. The forecast skill was assessed for 1-6 days lead time using categorical verification statistics such as Probability Of Detection (POD), Frequency Of Hit (FOH) and Frequency Of Miss (FOM). The model performance satisfactorily reproduced the pattern and volume of the observed stream flow hydrograph of Benue River. Overall, our results show that SREs and rainfall forecasts from weather models have great potential to serve as model inputs for real-time flood forecasting in data scarce areas. For these data to receive application in African transboundary basins, we suggest (i) removing their systematic error to further improve flood forecast skill; (ii) improving rainfall forecasts; and (iii) improving data sharing between riparian countries.

  12. Verification of Space Weather Forecasts using Terrestrial Weather Approaches

    NASA Astrophysics Data System (ADS)

    Henley, E.; Murray, S.; Pope, E.; Stephenson, D.; Sharpe, M.; Bingham, S.; Jackson, D.

    2015-12-01

    The Met Office Space Weather Operations Centre (MOSWOC) provides a range of 24/7 operational space weather forecasts, alerts, and warnings, which provide valuable information on space weather that can degrade electricity grids, radio communications, and satellite electronics. Forecasts issued include arrival times of coronal mass ejections (CMEs), and probabilistic forecasts for flares, geomagnetic storm indices, and energetic particle fluxes and fluences. These forecasts are produced twice daily using a combination of output from models such as Enlil, near-real-time observations, and forecaster experience. Verification of forecasts is crucial for users, researchers, and forecasters to understand the strengths and limitations of forecasters, and to assess forecaster added value. To this end, the Met Office (in collaboration with Exeter University) has been adapting verification techniques from terrestrial weather, and has been working closely with the International Space Environment Service (ISES) to standardise verification procedures. We will present the results of part of this work, analysing forecast and observed CME arrival times, assessing skill using 2x2 contingency tables. These MOSWOC forecasts can be objectively compared to those produced by the NASA Community Coordinated Modelling Center - a useful benchmark. This approach cannot be taken for the other forecasts, as they are probabilistic and categorical (e.g., geomagnetic storm forecasts give probabilities of exceeding levels from minor to extreme). We will present appropriate verification techniques being developed to address these forecasts, such as rank probability skill score, and comparing forecasts against climatology and persistence benchmarks. As part of this, we will outline the use of discrete time Markov chains to assess and improve the performance of our geomagnetic storm forecasts. We will also discuss work to adapt a terrestrial verification visualisation system to space weather, to help

  13. Timetable of an operational flood forecasting system

    NASA Astrophysics Data System (ADS)

    Liechti, Katharina; Jaun, Simon; Zappa, Massimiliano

    2010-05-01

    At present a new underground part of Zurich main station is under construction. For this purpose the runoff capacity of river Sihl, which is passing beneath the main station, is reduced by 40%. If a flood is to occur the construction site is evacuated and gates can be opened for full runoff capacity to prevent bigger damages. However, flooding the construction site, even if it is controlled, is coupled with costs and retardation. The evacuation of the construction site at Zurich main station takes about 2 to 4 hours and opening the gates takes another 1 to 2 hours each. In the upper part of the 336 km2 Sihl catchment the Sihl lake, a reservoir lake, is situated. It belongs and is used by the Swiss Railway Company for hydropower production. This lake can act as a retention basin for about 46% of the Sihl catchment. Lowering the lake level to gain retention capacity, and therewith safety, is coupled with direct loss for the Railway Company. To calculate the needed retention volume and the water to be released facing unfavourable weather conditions, forecasts with a minimum lead time of 2 to 3 days are needed. Since the catchment is rather small, this can only be realised by the use of meteorological forecast data. Thus the management of the construction site depends on accurate forecasts to base their decisions on. Therefore an operational hydrological ensemble prediction system (HEPS) was introduced in September 2008 by the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). It delivers daily discharge forecasts with a time horizon of 5 days. The meteorological forecasts are provided by MeteoSwiss and stem from the operational limited-area COSMO-LEPS which downscales the ECMWF ensemble prediction system to a spatial resolution of 7 km. Additional meteorological data for model calibration and initialisation (air temperature, precipitation, water vapour pressure, global radiation, wind speed and sunshine duration) and radar data are also provided by

  14. Tsunami Forecasting in the Atlantic Basin

    NASA Astrophysics Data System (ADS)

    Knight, W. R.; Whitmore, P.; Sterling, K.; Hale, D. A.; Bahng, B.

    2012-12-01

    The mission of the West Coast and Alaska Tsunami Warning Center (WCATWC) is to provide advance tsunami warning and guidance to coastal communities within its Area-of-Responsibility (AOR). Predictive tsunami models, based on the shallow water wave equations, are an important part of the Center's guidance support. An Atlantic-based counterpart to the long-standing forecasting ability in the Pacific known as the Alaska Tsunami Forecast Model (ATFM) is now developed. The Atlantic forecasting method is based on ATFM version 2 which contains advanced capabilities over the original model; including better handling of the dynamic interactions between grids, inundation over dry land, new forecast model products, an optional non-hydrostatic approach, and the ability to pre-compute larger and more finely gridded regions using parallel computational techniques. The wide and nearly continuous Atlantic shelf region presents a challenge for forecast models. Our solution to this problem has been to develop a single unbroken high resolution sub-mesh (currently 30 arc-seconds), trimmed to the shelf break. This allows for edge wave propagation and for kilometer scale bathymetric feature resolution. Terminating the fine mesh at the 2000m isobath keeps the number of grid points manageable while allowing for a coarse (4 minute) mesh to adequately resolve deep water tsunami dynamics. Higher resolution sub-meshes are then included around coastal forecast points of interest. The WCATWC Atlantic AOR includes eastern U.S. and Canada, the U.S. Gulf of Mexico, Puerto Rico, and the Virgin Islands. Puerto Rico and the Virgin Islands are in very close proximity to well-known tsunami sources. Because travel times are under an hour and response must be immediate, our focus is on pre-computing many tsunami source "scenarios" and compiling those results into a database accessible and calibrated with observations during an event. Seismic source evaluation determines the order of model pre

  15. Forecasts of solar and geomagnetic activity

    NASA Technical Reports Server (NTRS)

    Joselyn, Joann

    1987-01-01

    Forecasts of solar and geomagnetic activity are critical since these quantities are such important inputs to the thermospheric density models. At this time in the history of solar science there is no way to make such a forecast from first principles. Physical theory applied to the Sun is developing rapidly, but is still primitive. Techniques used for forecasting depend upon the observations over about 130 years, which is only twelve solar cycles. It has been noted that even-numbered cycles systematically tend to be smaller than the odd-numbered ones by about 20 percent. Another observation is that for the last 12 cycle pairs, an even-numbered sunspot cycle looks rather like the next odd-numbered cycle, but with the top cut off. These observations are examples of approximate periodicities that forecasters try to use to achieve some insight into the nature of an upcoming cycle. Another new and useful forecasting aid is a correlation that has been noted between geomagnetic indices and the size of the next solar cycle. Some best estimates are given concerning both activities.

  16. Layered Ensemble Architecture for Time Series Forecasting.

    PubMed

    Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin

    2016-01-01

    Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.

  17. Coastal ocean forecasting systems in Europe

    NASA Astrophysics Data System (ADS)

    Dugan, John

    During my tour as the liaison oceanographer at the Office of Naval Research's European branch, I conducted a focused study of coastal ocean forecasting systems. This study is of direct interest to ONR because of an increased interest in the coastal zone and to the civilian U.S. oceanographic community because of numerous problems in the coastal zone that could be alleviated with an operational forecasting system. The Europeans have a long history of excellent research and developmental work in this area. The Europeans' distinguished history in coastal ocean forecasting is due in part to their strong dependence on the sea. However, the original motivation for these systems was the recognition early in this century that weather conditions were responsible for damaging storm surges around the periphery of the North Sea and that science could predict these catastrophic floods. Forecasting systems called tide-surge prediction systems, which provide warnings of impending flood conditions, were designed and constructed and are operational in the various meteorological centers of the nations surrounding the North Sea. Over time, the services have been extended to provide forecasts of ocean waves, water depth for navigation, and currents for a large customer base. These systems now are being extended further into the three-dimensional domain that is required for management of problems associated with water quality, pollution, and aquaculture and fisheries interests.

  18. Operational aerosol and dust storm forecasting

    NASA Astrophysics Data System (ADS)

    Westphal, D. L.; Curtis, C. A.; Liu, M.; Walker, A. L.

    2009-03-01

    The U. S. Navy now conducts operational forecasting of aerosols and dust storms on global and regional scales. The Navy Aerosol Analysis and Prediction System (NAAPS) is run four times per day and produces 6-day forecasts of sulfate, smoke, dust and sea salt aerosol concentrations and visibility for the entire globe. The Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS®) is run twice daily for Southwest Asia and produces 3-day forecasts of dust, smoke, and visibility. The graphical output from these models is available on the Internet (www.nrlmry.navy.mil/aerosol/). The aerosol optical properties are calculated for each specie for each forecast output time and used for sea surface temperature (SST) retrieval corrections, regional electro-optical (EO) propagation assessments, and the development of satellite algorithms. NAAPS daily aerosol optical depth (AOD) values are compared with the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) AOD values. Visibility forecasts are compared quantitatively with surface synoptic reports.

  19. Operational seasonal forecasting of crop performance

    PubMed Central

    Stone, Roger C; Meinke, Holger

    2005-01-01

    Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production. PMID:16433097

  20. 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.

  1. Operational seasonal forecasting of crop performance.

    PubMed

    Stone, Roger C; Meinke, Holger

    2005-11-29

    Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production.

  2. Peak Wind Tool for General Forecasting

    NASA Technical Reports Server (NTRS)

    Barrett, Joe H., III

    2010-01-01

    The expected peak wind speed of the day is an important forecast element in the 45th Weather Squadron's (45 WS) daily 24-Hour and Weekly Planning Forecasts. The forecasts are used for ground and space launch operations at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45 WS also issues wind advisories for KSC/CCAFS when they expect wind gusts to meet or exceed 25 kt, 35 kt and 50 kt thresholds at any level from the surface to 300 ft. The 45 WS forecasters have indicated peak wind speeds are challenging to forecast, particularly in the cool season months of October - April. In Phase I of this task, the Applied Meteorology Unit (AMU) developed a tool to help the 45 WS forecast non-convective winds at KSC/CCAFS for the 24-hour period of 0800 to 0800 local time. The tool was delivered as a Microsoft Excel graphical user interface (GUI). The GUI displayed the forecast of peak wind speed, 5-minute average wind speed at the time of the peak wind, timing of the peak wind and probability the peak speed would meet or exceed 25 kt, 35 kt and 50 kt. For the current task (Phase II ), the 45 WS requested additional observations be used for the creation of the forecast equations by expanding the period of record (POR). Additional parameters were evaluated as predictors, including wind speeds between 500 ft and 3000 ft, static stability classification, Bulk Richardson Number, mixing depth, vertical wind shear, temperature inversion strength and depth and wind direction. Using a verification data set, the AMU compared the performance of the Phase I and II prediction methods. Just as in Phase I, the tool was delivered as a Microsoft Excel GUI. The 45 WS requested the tool also be available in the Meteorological Interactive Data Display System (MIDDS). The AMU first expanded the POR by two years by adding tower observations, surface observations and CCAFS (XMR) soundings for the cool season months of March 2007 to April 2009. The POR was expanded

  3. Heterogeneity: The key to failure forecasting

    PubMed Central

    Vasseur, Jérémie; Wadsworth, Fabian B.; Lavallée, Yan; Bell, Andrew F.; Main, Ian G.; Dingwell, Donald B.

    2015-01-01

    Elastic waves are generated when brittle materials are subjected to increasing strain. Their number and energy increase non-linearly, ending in a system-sized catastrophic failure event. Accelerating rates of geophysical signals (e.g., seismicity and deformation) preceding large-scale dynamic failure can serve as proxies for damage accumulation in the Failure Forecast Method (FFM). Here we test the hypothesis that the style and mechanisms of deformation, and the accuracy of the FFM, are both tightly controlled by the degree of microstructural heterogeneity of the material under stress. We generate a suite of synthetic samples with variable heterogeneity, controlled by the gas volume fraction. We experimentally demonstrate that the accuracy of failure prediction increases drastically with the degree of material heterogeneity. These results have significant implications in a broad range of material-based disciplines for which failure forecasting is of central importance. In particular, the FFM has been used with only variable success to forecast failure scenarios both in the field (volcanic eruptions and landslides) and in the laboratory (rock and magma failure). Our results show that this variability may be explained, and the reliability and accuracy of forecast quantified significantly improved, by accounting for material heterogeneity as a first-order control on forecasting power. PMID:26307196

  4. Forecast Mekong 2012: Building scientific capacity

    USGS Publications Warehouse

    Stefanov, James E.

    2012-01-01

    In 2009, U.S. Secretary of State Hillary R. Clinton joined the Foreign Ministers of Cambodia, Laos, Thailand, and Vietnam in launching the Lower Mekong Initiative to enhance U.S. engagement with the countries of the Lower Mekong River Basin in the areas of environment, health, education, and infrastructure. The U.S. Geological Survey Forecast Mekong supports the Lower Mekong Initiative through a variety of activities. The principal objectives of Forecast Mekong include the following: * Build scientific capacity in the Lower Mekong Basin and promote cooperation and collaboration among scientists working in the region. * Provide data, information, and scientific models to help resource managers there make informed decisions. * Produce forecasting and visualization tools to support basin planning, including climate change adaptation. The focus of this product is Forecast Mekong accomplishments and current activities related to the development of scientific capacity at organizations and institutions in the region. Building on accomplishments in 2010 and 2011, Forecast Mekong continues to enhance scientific capacity in the Lower Mekong Basin with a suite of activities in 2012.

  5. Emergency Response Transport Forecasting Using Historical Wind Field Pattern Matching.

    NASA Astrophysics Data System (ADS)

    Carter, Roger G.; Keislar, Robert E.

    2000-03-01

    Historical pattern matching, or analog forecasting, is used to generate short-term mesoscale transport forecasts for emergency response at the Idaho National Engineering and Environmental Laboratory. A simple historical pattern-matching algorithm operating on a database from the spatially and temporally dense Eastern Idaho Mesonet is used to generate a wind field forecast, which then is input to an existing puff diffusion model. The forecasts are rated both by a team of meteorologists and by a computer scoring method. Over 60% of the forecasts are rated as acceptable. The forecasts also are compared with a persistence method, using both a subjective human evaluation and root-mean-square error calculations.

  6. Convective Weather Forecast Accuracy Analysis at Center and Sector Levels

    NASA Technical Reports Server (NTRS)

    Wang, Yao; Sridhar, Banavar

    2010-01-01

    This paper presents a detailed convective forecast accuracy analysis at center and sector levels. The study is aimed to provide more meaningful forecast verification measures to aviation community, as well as to obtain useful information leading to the improvements in the weather translation capacity models. In general, the vast majority of forecast verification efforts over past decades have been on the calculation of traditional standard verification measure scores over forecast and observation data analyses onto grids. These verification measures based on the binary classification have been applied in quality assurance of weather forecast products at the national level for many years. Our research focuses on the forecast at the center and sector levels. We calculate the standard forecast verification measure scores for en-route air traffic centers and sectors first, followed by conducting the forecast validation analysis and related verification measures for weather intensities and locations at centers and sectors levels. An approach to improve the prediction of sector weather coverage by multiple sector forecasts is then developed. The weather severe intensity assessment was carried out by using the correlations between forecast and actual weather observation airspace coverage. The weather forecast accuracy on horizontal location was assessed by examining the forecast errors. The improvement in prediction of weather coverage was determined by the correlation between actual sector weather coverage and prediction. observed and forecasted Convective Weather Avoidance Model (CWAM) data collected from June to September in 2007. CWAM zero-minute forecast data with aircraft avoidance probability of 60% and 80% are used as the actual weather observation. All forecast measurements are based on 30-minute, 60- minute, 90-minute, and 120-minute forecasts with the same avoidance probabilities. The forecast accuracy analysis for times under one-hour showed that the errors in

  7. Real-time forecasts of dengue epidemics

    NASA Astrophysics Data System (ADS)

    Yamana, T. K.; Shaman, J. L.

    2015-12-01

    Dengue is a mosquito-borne viral disease prevalent in the tropics and subtropics, with an estimated 2.5 billion people at risk of transmission. In many areas with endemic dengue, disease transmission is seasonal but prone to high inter-annual variability with occasional severe epidemics. Predicting and preparing for periods of higher than average transmission is a significant public health challenge. Here we present a model of dengue transmission and a framework for optimizing model simulations with real-time observational data of dengue cases and environmental variables in order to generate ensemble-based forecasts of the timing and severity of disease outbreaks. The model-inference system is validated using synthetic data and dengue outbreak records. Retrospective forecasts are generated for a number of locations and the accuracy of these forecasts is quantified.

  8. The NASA GEOS-5 Aerosol Forecasting System

    NASA Technical Reports Server (NTRS)

    Colarco, Peter; daSilva, Arlindo; Darmenov, Anton

    2011-01-01

    The NASA Goddard Earth Observing System modeling and data assimilation environment (GEOS-5) is maintained by the Global Modeling and Assimilation Office (GMAO) at the NASA Goddard Space Flight Center. Near-realtime meteorological forecasts are produced to support NASA satellite and field missions. We have implemented in this environment an aerosol module based on the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) model. This modeling system has previously been evaluated in the context of hindcasts based on assimilated meteorology. Here we focus on the development and evaluation of the near-realtime forecasting system. We present a description of recent efforts to implement near-realtime biomass burning emissions derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power products. We as well present a developing capability for improvement of aerosol forecasts by assimilation of aerosol information from MODIS.

  9. Computer technology forecasting at the National Laboratories

    SciTech Connect

    Peskin, A M

    1980-01-01

    The DOE Office of ADP Management organized a group of scientists and computer professionals, mostly from their own national laboratories, to prepare an annually updated technology forecast to accompany the Department's five-year ADP Plan. The activities of the task force were originally reported in an informal presentation made at the ACM Conference in 1978. This presentation represents an update of that report. It also deals with the process of applying the results obtained at a particular computing center, Brookhaven National Laboratory. Computer technology forecasting is a difficult and hazardous endeavor, but it can reap considerable advantage. The forecast performed on an industry-wide basis can be applied to the particular needs of a given installation, and thus give installation managers considerable guidance in planning. A beneficial side effect of this process is that it forces installation managers, who might otherwise tend to preoccupy themselves with immediate problems, to focus on longer term goals and means to their ends. (RWR)

  10. The promise and peril of healthcare forecasting.

    PubMed

    Wharam, J Frank; Weiner, Jonathan P

    2012-03-01

    Health plans and physician groups increasingly use sophisticated tools to predict individual patient outcomes. Such analytics will accelerate as US medicine enters the digital age. Promising applications of forecasting include better targeting of disease management as well as innovative patient care approaches such as personalized health insurance and clinical decision support systems. In addition, stakeholders will use predictions to advance their organizational agendas, and unintended consequences could arise. Forecasting-based interventions might have uncertain effectiveness, focus on cost savings rather than long-term health, or specifically exclude disadvantaged populations. Policy makers, health plans, and method developers should adopt strategies that address these concerns in order to maximize the benefit of healthcare forecasting on the long-term health of patients.

  11. Simulation forecasts complex flow streams from Ekofisk

    SciTech Connect

    Arnes, F.C.; Lillejord, H.

    1996-10-28

    A commercial steady-state process flowsheet simulation program serves as the basis for a rigorous calculation model for predicting produced flow rates from the Ekofisk complex in the Norwegian sector of the North Sea. The complex is the center of an extensive gathering system that collects oil and gas streams from several producing fields. Prior to running a production forecast, the simulation model is initiated by matching several years of production. Once the simulation model matches historical production data within acceptable limits, it then is driven by production forecasts from reservoir simulations to develop long-term forecasts of gas, NGL, and oil production. The paper describes the Ekofisk field, the process simulation, implementation of the model, and problems encountered.

  12. Forecast Validation and Verification for Earthquakes, Weather and Finance

    NASA Astrophysics Data System (ADS)

    Rundle, J. B.; Holliday, J. R.; Turcotte, D. L.; Donnellan, A.; Tiampo, K.

    2009-04-01

    Techniques for earthquake forecasting are in development using both seismicity data mining methods, as well as numerical simulations. Testing such forecasts is necessary not only to determine forecast quality, but also to carry out forecast improvement. A large number of techniques to validate and verify forecasts have been developed for weather and financial applications. Many of these have been elaborated in public locations, including http://www.bom.gov.au/bmrc/wefor/staff/eee/verif/verif_web_page.html. Typically, the goal is to test for forecast resolution, reliability and sharpness. A good forecast is characterized by consistency, quality and value. Most, if not all of these forecast verification procedures can be readily applied to earthquake forecasts as well. In this talk, we discuss a number of these methods, and show how they might be useful for both fault-based forecasting, a group that includes the WGCEP and simulator-based renewal models, and grid-based forecasting, which includes the Relative Intensity, Pattern Informatics, and smoothed seismicity methods. We find that applying these standard methods of forecast verification is straightforward, and we conclude that judgments about the quality of a given forecast method can often depend on the test applied.

  13. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

    SciTech Connect

    Zhang, Jie; Hodge, Bri -Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat; Black, Jon; Tedesco, John

    2015-11-10

    Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.

  14. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

    DOE PAGES

    Zhang, Jie; Hodge, Bri -Mathias; Lu, Siyuan; ...

    2015-11-10

    Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based onmore » state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.« less

  15. The Forecast Interpretation Tool—a Monte Carlo technique for blending climatic distributions with probabilistic forecasts

    USGS Publications Warehouse

    Husak, G.J.; Michaelsen, J.; Kyriakidis, P.; Verdin, J.P.; Funk, C.; Galu, G.

    2011-01-01

    Probabilistic forecasts are produced from a variety of outlets to help predict rainfall, and other meteorological events, for periods of 1 month or more. Such forecasts are expressed as probabilities of a rainfall event, e.g. being in the upper, middle, or lower third of the relevant distribution of rainfall in the region. The impact of these forecasts on the expectation for the event is not always clear or easily conveyed. This article proposes a technique based on Monte Carlo simulation for adjusting existing climatologic statistical parameters to match forecast information, resulting in new parameters defining the probability of events for the forecast interval. The resulting parameters are shown to approximate the forecasts with reasonable accuracy. To show the value of the technique as an application for seasonal rainfall, it is used with consensus forecast developed for the Greater Horn of Africa for the 2009 March-April-May season. An alternative, analytical approach is also proposed, and discussed in comparison to the first simulation-based technique.

  16. Real-time eruption forecasting using the material Failure Forecast Method with a Bayesian approach

    NASA Astrophysics Data System (ADS)

    Boué, A.; Lesage, P.; Cortés, G.; Valette, B.; Reyes-Dávila, G.

    2015-04-01

    Many attempts for deterministic forecasting of eruptions and landslides have been performed using the material Failure Forecast Method (FFM). This method consists in adjusting an empirical power law on precursory patterns of seismicity or deformation. Until now, most of the studies have presented hindsight forecasts based on complete time series of precursors and do not evaluate the ability of the method for carrying out real-time forecasting with partial precursory sequences. In this study, we present a rigorous approach of the FFM designed for real-time applications on volcano-seismic precursors. We use a Bayesian approach based on the FFM theory and an automatic classification of seismic events. The probability distributions of the data deduced from the performance of this classification are used as input. As output, it provides the probability of the forecast time at each observation time before the eruption. The spread of the a posteriori probability density function of the prediction time and its stability with respect to the observation time are used as criteria to evaluate the reliability of the forecast. We test the method on precursory accelerations of long-period seismicity prior to vulcanian explosions at Volcán de Colima (Mexico). For explosions preceded by a single phase of seismic acceleration, we obtain accurate and reliable forecasts using approximately 80% of the whole precursory sequence. It is, however, more difficult to apply the method to multiple acceleration patterns.

  17. Probabilistic forecasts for Decision Support at the North Central River Forecast Center

    NASA Astrophysics Data System (ADS)

    Restrepo, Pedro; Buan, Steven; Connelly, Brian; DeWeese, Michael; Diamond, Laura; Ellis, Larry; Goering, Dustin; Holz, Andrea; Husaby, James; Merrigan, Douglas; Palmer, Justin; Pokorny, Daniel; Reckel, Holly; Sites, William; Stockhaus, Scott; Thornburg, Jonathon; Wavrin, Robert.; Ziemer, Mark

    2013-04-01

    The North Central River Forecast Center (NCRFC) of the US National Weather Service has the responsibility for issuing river forecasts at 426 points over an area of nearly 890,000 km2, covering the Upper Mississippi river basin, the US watersheds flowing to lakes Superior, Huron and Michigan, and rivers flowing from the US to the Hudson Bay in Canada. The NCRFC issues probabilistic outlook forecasts at all its forecast points starting on December. While focused primarily on the risks associated with flooding during the spring snow melt down, the RFC frequently issues probabilistic forecasts to deal with water resources operations during drought times. This presentation will focus on probabilistic forecasts issued to assess flooding risk at Red River of the North , to support navigation operations on the Mississippi river during drought conditions, and on support of reservoir operations for hydropower generation and recreation. The presentation will discuss the improvements over the current practice that will be possible to achieve once the NWS Hydrologic Ensemble Forecasting System is put into operations later this year.

  18. Forecasting cyanobacteria dominance in Canadian temperate lakes.

    PubMed

    Persaud, Anurani D; Paterson, Andrew M; Dillon, Peter J; Winter, Jennifer G; Palmer, Michelle; Somers, Keith M

    2015-03-15

    Predictive models based on broad scale, spatial surveys typically identify nutrients and climate as the most important predictors of cyanobacteria abundance; however these models generally have low predictive power because at smaller geographic scales numerous other factors may be equally or more important. At the lake level, for example, the ability to forecast cyanobacteria dominance is of tremendous value to lake managers as they can use such models to communicate exposure risks associated with recreational and drinking water use, and possible exposure to algal toxins, in advance of bloom occurrence. We used detailed algal, limnological and meteorological data from two temperate lakes in south-central Ontario, Canada to determine the factors that are closely linked to cyanobacteria dominance, and to develop easy to use models to forecast cyanobacteria biovolume. For Brandy Lake (BL), the strongest and most parsimonious model for forecasting % cyanobacteria biovolume (% CB) included water column stability, hypolimnetic TP, and % cyanobacteria biovolume two weeks prior. For Three Mile Lake (TML), the best model for forecasting % CB included water column stability, hypolimnetic TP concentration, and 7-d mean wind speed. The models for forecasting % CB in BL and TML are fundamentally different in their lag periods (BL = lag 1 model and TML = lag 2 model) and in some predictor variables despite the close proximity of the study lakes. We speculate that three main factors (nutrient concentrations, water transparency and lake morphometry) may have contributed to differences in the models developed, and may account for variation observed in models derived from large spatial surveys. Our results illustrate that while forecast models can be developed to determine when cyanobacteria will dominate within two temperate lakes, the models require detailed, lake-specific calibration to be effective as risk-management tools.

  19. Including Tidal Effects in Tsunami Forecasting

    NASA Astrophysics Data System (ADS)

    Arcas, D.

    2015-12-01

    Recently a new tsunami forecast system SIFT (Short-term Inundation and Forecasting of Tsunamis) has been declared operational by the National Weather Service (NWS) Tsunami Warning Centers. The SIFT system assimilates real-time information from a network of observing systems deployed in the open ocean, to produce on-the-fly estimates of tsunami impact at specific coastal communities. These estimates are computed via the tsunami simulation code MOST (Method of Splitting Tsunami) and include forecast products such as tsunami arrival time, duration of the event, predicted tsunami currents, maximum sea surface elevation and expected inundation areas. These computations are performed under the assumption that the mean sea level remains constant at Mean High Water (MHW) during the entire tsunami event. This assumption produces conservative tsunami forecasts that tend to err on the side of caution with the possibility of substantial overestimates of the inundation areas. To avoid this problem and produce more accurate, operational tsunami forecasts, we investigate the effects of tsunami interaction with tides. The nonlinear dynamic interaction is simulated by first, simulating tidal elevations and currents with Oregon State University tidal model, to obtain boundary and initial conditions to force the MOST tsunami model. Tsunami boundary and initial conditions can be added to those for the tide to study the combined effect. Our results show that even at locations with strong tidal forcing, the tsunami/tide interaction effect has a weakly non-linear effect on the tsunami elevation waveform. This interaction, however, will have a significant effect on the extent of the inundation area. Based on these findings we propose a simple, linear correction to the standard MHW forecast for tsunami time series and inundation area, that can be performed on-the-fly by the SIFT system without the need for complex tidal models.

  20. Forecast bias analysis using object-based verification of regional WRF summertime convective forecasts

    NASA Astrophysics Data System (ADS)

    Starzec, Mariusz

    Forecast verification remains a crucial component of improving model forecasts, but still remains a challenge to perform. An objective method is developed to verify simulated reflectivity against radar reflectivity at a 1 km altitude utilizing the Method for Object-based Diagnostic Evaluation (MODE) Tool. Comparing the reflectivity field allows for an instantaneous view of what is occurring in simulations without any averaging that may occur when analyzing fields such as accumulated precipitation. The objective method is applied to high resolution 3 km and 1 km local convective WRF summertime forecasts in the Northern Plains region. The bulk verification statistics reveal that forecasts generate too many objects, over-forecast the areal coverage of convection, and over-intensify convection. No noteworthy increases in skill are found when increasing to 1 km resolution and instead lead to a significant over-forecasting of small cells. A sensitivity study is performed to investigate the forecast biases found by varying the cloud droplet concentration, microphysical scheme, and horizontal resolution on a case day containing weakly forced convection mostly below the freezing level. Changing the cloud droplet concentration has a strong impact on the number of object and area biases. Increasing droplet counts to observed values generates a forecast that more closely resembles the observations in terms of area and object counts, but leads not enough rain generation. Changing the microphysical scheme produces the most pronounced effects on object counts and intensity, which is attributed to differences in autoconversion formulations. Coarsening the resolution from 3 km to 9 km leads to a decrease in skill, showing that 3 km simulations are more effective at convective forecasts. Increasing the resolution to 1 km results in amplifying the object count bias, and is found to not be worth the additional computational expense.

  1. 2014 Gulf of Mexico Hypoxia Forecast

    USGS Publications Warehouse

    Scavia, Donald; Evans, Mary Anne; Obenour, Dan

    2014-01-01

    The Gulf of Mexico annual summer hypoxia forecasts are based on average May total nitrogen loads from the Mississippi River basin for that year. The load estimate, recently released by USGS, is 4,761 metric tons per day. Based on that estimate, we predict the area of this summer’s hypoxic zone to be 14,000 square kilometers (95% credible interval, 8,000 to 20,000) – an “average year”. Our forecast hypoxic volume is 50 km3 (95% credible interval, 20 to 77).

  2. Medium range flood forecasts at global scale

    NASA Astrophysics Data System (ADS)

    Voisin, N.; Wood, A. W.; Lettenmaier, D. P.; Wood, E. F.

    2006-12-01

    While weather and climate forecast methods have advanced greatly over the last two decades, this capability has yet to be evidenced in mitigation of water-related natural hazards (primarily floods and droughts), especially in the developing world. Examples abound of extreme property damage and loss of life due to floods in the underdeveloped world. For instance, more than 4.5 million people were affected by the July 2000 flooding of the Mekong River and its tributaries in Cambodia, Vietnam, Laos and Thailand. The February- March 2000 floods in the Limpopo River of Mozambique caused extreme disruption to that country's fledgling economy. Mitigation of these events through advance warning has typically been modest at best. Despite the above noted improvement in weather and climate forecasts, there is at present no system for forecasting of floods globally, notwithstanding that the potential clearly exists. We describe a methodology that is eventually intended to generate global flood predictions routinely. It draws heavily from the experimental North American Land Data Assimilation System (NLDAS) and the companion Global Land Data Assimilation System (GLDAS) for development of nowcasts, and the University of Washington Experimental Hydrologic Prediction System to develop ensemble hydrologic forecasts based on Numerical Weather Prediction (NWP) models which serve both as nowcasts (and hence reduce the need for in situ precipitation and other observations in parts of the world where surface networks are critically deficient) and provide forecasts for lead times as long as fifteen days. The heart of the hydrologic modeling system is the University of Washington/Princeton University Variable Infiltration Capacity (VIC) macroscale hydrology model. In the prototype (tested using retrospective data), VIC is driven globally up to the time of forecast with daily ERA40 precipitation (rescaled on a monthly basis to a station-based global climatology), ERA40 wind, and ERA40

  3. An Improved Forecasting Method of Sunspot Maximum

    NASA Astrophysics Data System (ADS)

    Yin, Z.; Tian, L.; Han, Y.; Wang, B.; Han, Y.

    2015-12-01

    It has been paid more and more attention for forecasting sunspot maximum of future solar cycle in recent decades, and a variety of forecasting methods have been studied. However, to make an accurate prediction is still very difficult due to the complexities of the characteristics of solar activity. Some authors summerized a variety of methods for the maximum predictions of 22nd, 23rd, 24th solar cycles, the incomplete statistics are 63, 54 and 75 cases respectively, results of the methods, which the difference between forecasting and observed values within the range of ±15%, are 27.0%, 25.9% and 24.3% respectively. Using the 13 points smoothed value of monthly sunspot numbers, we studied correlation between sunspot number rising rate of the first 24 months of the solar cycle and the coming cycle maximum, published forecasting result that the maximum value was 139.2 ± 18.8 for 23rd solar cycle (Han et al., 2000), and the observed value is 120.8, the error is about 15.2%. The present paper describes our improved forecasting methods. First, Vondrak smoothing method is used to deal with the monthly sunspot numbers. It is studied that the relationship between the rise rate of earlier months of sunspot numbers of this smoothed sequence and the coming maximum value in each solar cycles. The results show that the first 22, 23, 24 months rise rate of sunspot numbers are highly related with the coming maximum values, and simulated prediction of maximum for 22~24 cycles show that using the 22-month rise rate of three solar cycles, the maximum forecasting error is about 13.2%, using 23-month rise rate, the maximum error is about 11.2%, while using 24-month rise rate, the maximum error is only about 9.3%. The new method not only improves the forecasting accuracy but also can make the forecasting time in advance at least half a year than the common method using 13 points monthly smoothed value.

  4. San Francisco Bay Area Cargo Forecast.

    DTIC Science & Technology

    1981-06-01

    CHAlES IN SAY AREA AND PACIFIC COAST SHARES FOREIGN CONTAINER CAKRO Pacftic Coast Bay Area bil Total .1 Share of Total as Share of Ypar lted States...patterns and recent trends, and on evaluation of the key factors and events likely to affect future trade. Thus, it was both "past and forward looking...Bay Area Forecast The baseline, high, and low forecasts of Bay Area Trade Route 29 containerized cargo shown in Table 28 are based on evaluation of

  5. 2013 Gulf of Mexico Hypoxia Forecast

    USGS Publications Warehouse

    Scavia, Donald; Evans, Mary Anne; Obenour, Dan

    2013-01-01

    The Gulf of Mexico annual summer hypoxia forecasts are based on average May total nitrogen loads from the Mississippi River basin for that year. The load estimate, recently released by USGS, is 7,316 metric tons per day. Based on that estimate, we predict the area of this summer’s hypoxic zone to be 18,900 square kilometers (95% credible interval, 13,400 to 24,200), the 7th largest reported and about the size of New Jersey. Our forecast hypoxic volume is 74.5 km3 (95% credible interval, 51.5 to 97.0), also the 7th largest on record.

  6. Seasonal forecast quality of the West African monsoon rainfall regimes by multiple forecast systems

    NASA Astrophysics Data System (ADS)

    Rodrigues, Luis Ricardo Lage; García-Serrano, Javier; Doblas-Reyes, Francisco

    2014-07-01

    A targeted methodology to study the West African monsoon (WAM) rainfall variability is considered where monthly rainfall is averaged over 10°W-10°E to take into account the latitudinal migration and temporal distribution of the WAM summer rainfall. Two observational rainfall data sets and a large number of quasi-operational forecast systems, among them two systems from the European Seasonal to Interannual Prediction initiative and six systems from the North American Multi-model Ensemble project, are used in this research. The two leading modes of the WAM rainfall variability, namely, the Guinean and Sahelian regimes, are estimated by applying principal component analysis (PCA) on the longitudinally averaged precipitation. The PCA is performed upon the observations and each forecast system and lead time separately. A statistical model based on simple linear regression using sea surface temperature indices as predictors is considered both as a benchmark and an additional forecast system. The combination of the dynamical forecast systems and the statistical model is performed using different methods of combination. It is shown that most forecast systems capture the main features associated with the Guinean regime, that is, rainfall located mainly south of 10°N and the northward migration of rainfall over the season. On the other hand, only a fraction of the forecast systems capture the characteristics of the rainfall signal north of 10°N associated with the Sahelian regime. A simple statistical model proves to be of great value and outperforms most state-of-the-art dynamical forecast systems when predicting the principal components associated with the Guinean and Sahelian regimes. Combining all forecast systems do not lead to improved forecasts when compared to the best single forecast system, the European Centre for Medium-Range Weather Forecasts System 4 (S4). In fact, S4 is far better than any forecast system when predicting the variability of the WAM rainfall

  7. Resolution of Probabilistic Weather Forecasts with Application in Disease Management.

    PubMed

    Hughes, G; McRoberts, N; Burnett, F J

    2017-02-01

    Predictive systems in disease management often incorporate weather data among the disease risk factors, and sometimes this comes in the form of forecast weather data rather than observed weather data. In such cases, it is useful to have an evaluation of the operational weather forecast, in addition to the evaluation of the disease forecasts provided by the predictive system. Typically, weather forecasts and disease forecasts are evaluated using different methodologies. However, the information theoretic quantity expected mutual information provides a basis for evaluating both kinds of forecast. Expected mutual information is an appropriate metric for the average performance of a predictive system over a set of forecasts. Both relative entropy (a divergence, measuring information gain) and specific information (an entropy difference, measuring change in uncertainty) provide a basis for the assessment of individual forecasts.

  8. Research Spotlight: New method could improve hurricane surge forecasting

    NASA Astrophysics Data System (ADS)

    Tretkoff, Ernie

    2011-03-01

    In recent years, hurricanes in the Gulf of Mexico, including Katrina and Ike, caused some of the highest surges on record and significant flooding, highlighting the need for good surge forecasts that can be used for early warning and evacuation. However, current approaches for surge forecasting use models that take too much computational time or have spatial resolution too low to provide adequate forecast accuracy. Irish et al. propose a new method for determining probabilistic maximum hurricane surge forecasts. Their approach is based on calculations of surge response functions, which are derived from numerical simulations, along with analysis of meteorological forecasts. They applied the method to data from Hurricane Ike and found that they could accurately compute surge forecast probabilities within seconds, given publicly available meteorological forecast data. The method can provide a forecast of how surge would vary along the coast and identify areas most vulnerable to high surges. (Geophysical Research Letters, doi:10.1029/2010GL046347, 2011)

  9. Seasonal forecast of St. Louis encephalitis virus transmission, Florida.

    PubMed

    Shaman, Jeffrey; Day, Jonathan F; Stieglitz, Marc; Zebiak, Stephen; Cane, Mark

    2004-05-01

    Disease transmission forecasts can help minimize human and domestic animal health risks by indicating where disease control and prevention efforts should be focused. For disease systems in which weather-related variables affect pathogen proliferation, dispersal, or transmission, the potential for disease forecasting exists. We present a seasonal forecast of St. Louis encephalitis virus transmission in Indian River County, Florida. We derive an empiric relationship between modeled land surface wetness and levels of SLEV transmission in humans. We then use these data to forecast SLEV transmission with a seasonal lead. Forecast skill is demonstrated, and a real-time seasonal forecast of epidemic SLEV transmission is presented. This study demonstrates how weather and climate forecast skill-verification analyses may be applied to test the predictability of an empiric disease forecast model.

  10. Development of an oil spill forecast system for offshore China

    NASA Astrophysics Data System (ADS)

    Wang, Yonggang; Wei, Zexun; An, Wei

    2016-07-01

    An oil spill forecast system for offshore China was developed based on Visual C++. The oil spill forecast system includes an ocean environmental forecast model and an oil spill model. The ocean environmental forecast model was designed to include timesaving methods, and comprised a parametrical wind wave forecast model and a sea surface current forecast model. The oil spill model was based on the "particle method" and fulfills the prediction of oil particle behavior by considering the drifting, evaporation and emulsification processes. A specific database was embedded into the oil spill forecast system, which contained fundamental information, such as the properties of oil, reserve of emergency equipment and distribution of marine petroleum platform. The oil spill forecast system was successfully applied as part of an oil spill emergency exercise, and provides an operational service in the Research and Development Center for Offshore Oil Safety and Environmental Technology.

  11. Evolutionary Forecast Engines for Solar Meteorology

    NASA Astrophysics Data System (ADS)

    Coimbra, C. F.

    2012-12-01

    A detailed comparison of non-stationary regression and stochastic learning methods based on k-Nearest Neighbor (kNN), Artificial Neural Networks (ANN) and Genetic Algorithm (GA) approaches is carried out in order to develop high-fidelity solar forecast engines for several time horizons of interest. A hybrid GA/ANN method emerges as the most robust stochastic learning candidate. The GA/ANN approach In general the following decisions need to be made when creating an ANN-based solar forecast model: the ANN architecture: number of layers, numbers of neurons per layer; the preprocessing scheme; the fraction and distribution between training and testing data, and the meteorological and radiometric inputs. ANNs are very well suited to handle multivariate forecasting models due to their overall flexibility and nonlinear pattern recognition abilities. However, the forecasting skill of ANNs depends on a new set of parameters to be optimized within the context of the forecast model, which is the selection of input variables that most directly impact the fidelity of the forecasts. In a data rich scenario where irradiation, meteorological, and cloud cover data are available, it is not always evident which variables to include in the model a priori. New variables can also arise from data preprocessing such as smoothing or spectral decomposition. One way to avoid time-consuming trial-and-error approaches that have limited chance to result in optimal ANN topology and input selection is to couple the ANN with some optimization algorithm that scans the solution space and "evolves" the ANN structure. Genetic Algorithms (GAs) are well suited for this task. Results and Discussion The models built upon the historical data of 2009 and 2010 are applied to the 2011 data without modifications or retraining. We consider 3 solar variability seasons or periods, which are subsets of the total error evaluation data set. The 3 periods are defined based on the solar variability study as: - a high

  12. Risky Business: Development, Communication and Use of Hydroclimatic Forecasts

    NASA Astrophysics Data System (ADS)

    Lall, U.

    2012-12-01

    Inter-seasonal and longer hydroclimatic forecasts have been made increasingly in the last two decades following the increase in ENSO activity since the early 1980s and the success in seasonal ENSO forecasting. Yet, the number of examples of systematic use of these forecasts and their incorporation into water systems operation continue to be few. This may be due in part to the limited skill in such forecasts over much of the world, but is also likely due to the limited evolution of methods and opportunities to "safely" use uncertain forecasts. There has been a trend to rely more on "physically based" rather than "physically informed" empirical forecasts, and this may in part explain the limited success in developing usable products in more locations. Given the limited skill, forecasters have tended to "dumb" down their forecasts - either formally or subjectively shrinking the forecasts towards climatology, or reducing them to tercile forecasts that serve to obscure the potential information in the forecast. Consequently, the potential utility of such forecasts for decision making is compromised. Water system operating rules are often designed to be robust in the face of historical climate variability, and consequently are adapted to the potential conditions that a forecast seeks to inform. In such situations, there is understandable reluctance by managers to use the forecasts as presented, except in special cases where an alternate course of action is pragmatically appealing in any case. In this talk, I review opportunities to present targeted forecasts for use with decision systems that directly address climate risk and the risk induced by unbiased yet uncertain forecasts, focusing especially on extreme events and water allocation in a competitive environment. Examples from Brazil and India covering surface and ground water conjunctive use strategies that could potentially be insured and lead to improvements over the traditional system operation and resource

  13. Modeling and forecasting U.S. sex differentials in mortality.

    PubMed

    Carter, L R; Lee, R D

    1992-11-01

    "This paper examines differentials in observed and forecasted sex-specific life expectancies and longevity in the United States from 1900 to 2065. Mortality models are developed and used to generate long-run forecasts, with confidence intervals that extend recent work by Lee and Carter (1992). These results are compared for forecast accuracy with univariate naive forecasts of life expectancies and those prepared by the Actuary of the Social Security Administration."

  14. 7 CFR 1710.301 - Financial forecasts-distribution borrowers.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 11 2010-01-01 2010-01-01 false Financial forecasts-distribution borrowers. 1710.301... AND GUARANTEES Long-Range Financial Forecasts § 1710.301 Financial forecasts—distribution borrowers. (a) Financial forecasts prepared by distribution borrowers shall cover at least a ten-year...

  15. Method for Water Management Considering Long-term Probabilistic Forecasts

    NASA Astrophysics Data System (ADS)

    Hwang, J.; Kang, J.; Suh, A. S.

    2015-12-01

    This research is aimed at predicting the monthly inflow of the Andong-dam basin in South Korea using long-term probabilistic forecasts to apply long-term forecasts to water management. Forecasted Cumulative Distribution Functions (CDFs) of monthly precipitation are plotted by combining the range of monthly precipitation based on proper Probability Density Function (PDF) in past data with probabilistic forecasts in each category. Ensembles of inflow are estimated by entering generated ensembles of precipitation based on the CDFs into the 'abcd' water budget model. The bias and RMSE between averages in past data and observed inflow are compared to them in forecasted ensembles. In our results, the bias and RMSE of average precipitation in the forecasted ensemble are bigger than in past data, whereas the average inflow in the forecasted ensemble is smaller than in past data. This result could be used for reference data to apply long-term forecasts to water management, because of the limit in the number of forecasted data for verification and differences between the Andong-dam basin and the forecasted regions. This research has significance by suggesting a method of applying probabilistic information in climate variables from long-term forecasts to water management in Korea. Original data of a climate model, which produces long-term probabilistic forecasts should be verified directly as input data of a water budget model in the future, so that a more scientific response in water management against uncertainty of climate change could be reached.

  16. 17 CFR 210.11-03 - Presentation of financial forecast.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 17 Commodity and Securities Exchanges 2 2010-04-01 2010-04-01 false Presentation of financial forecast. 210.11-03 Section 210.11-03 Commodity and Securities Exchanges SECURITIES AND EXCHANGE COMMISSION... Information § 210.11-03 Presentation of financial forecast. (a) A financial forecast may be filed in lieu...

  17. Naive vs. Sophisticated Methods of Forecasting Public Library Circulations.

    ERIC Educational Resources Information Center

    Brooks, Terrence A.

    1984-01-01

    Two sophisticated--autoregressive integrated moving average (ARIMA), straight-line regression--and two naive--simple average, monthly average--forecasting techniques were used to forecast monthly circulation totals of 34 public libraries. Comparisons of forecasts and actual totals revealed that ARIMA and monthly average methods had smallest mean…

  18. An Optimization of Inventory Demand Forecasting in University Healthcare Centre

    NASA Astrophysics Data System (ADS)

    Bon, A. T.; Ng, T. K.

    2017-01-01

    Healthcare industry becomes an important field for human beings nowadays as it concerns about one’s health. With that, forecasting demand for health services is an important step in managerial decision making for all healthcare organizations. Hence, a case study was conducted in University Health Centre to collect historical demand data of Panadol 650mg for 68 months from January 2009 until August 2014. The aim of the research is to optimize the overall inventory demand through forecasting techniques. Quantitative forecasting or time series forecasting model was used in the case study to forecast future data as a function of past data. Furthermore, the data pattern needs to be identified first before applying the forecasting techniques. Trend is the data pattern and then ten forecasting techniques are applied using Risk Simulator Software. Lastly, the best forecasting techniques will be find out with the least forecasting error. Among the ten forecasting techniques include single moving average, single exponential smoothing, double moving average, double exponential smoothing, regression, Holt-Winter’s additive, Seasonal additive, Holt-Winter’s multiplicative, seasonal multiplicative and Autoregressive Integrated Moving Average (ARIMA). According to the forecasting accuracy measurement, the best forecasting technique is regression analysis.

  19. New Employment Forecasts. Hotel and Catering Industry 1988-1993.

    ERIC Educational Resources Information Center

    Measurement for Management Decision, Ltd., London (England).

    Econometric forecasting models were used to forecast employment levels in the hotel and catering industry in Great Britain through 1993 under several different forecasting scenarios. The growth in employment in the hotel and catering industry over the next 5 years is likely to be broadly based, both across income levels of domestic consumers,…

  20. Communicating Environmental Uncertainty: The Nature of Weather Forecasts.

    ERIC Educational Resources Information Center

    Travis, Richard W.; Riebsame, William E.

    1979-01-01

    Traces the path of weather forecasts from the time they are made by the National Oceanic and Atmospheric Administration until the time they are received by the public through the mass media. The purpose of the article is to provide geography teachers with basic information on weather forecasts, interpretation of forecast terms, and indications…

  1. 7 CFR 1710.203 - Requirement to prepare a load forecast-distribution borrowers.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... participation in and inclusion of its load forecasting information in the approved load forecast of its power... inclusion of its load forecasting information in the approved load forecast of its power supply borrower... participation in and inclusion of its load forecasting information in the approved load forecast of its...

  2. 7 CFR 1710.203 - Requirement to prepare a load forecast-distribution borrowers.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... participation in and inclusion of its load forecasting information in the approved load forecast of its power... inclusion of its load forecasting information in the approved load forecast of its power supply borrower... participation in and inclusion of its load forecasting information in the approved load forecast of its...

  3. 7 CFR 1710.203 - Requirement to prepare a load forecast-distribution borrowers.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... participation in and inclusion of its load forecasting information in the approved load forecast of its power... inclusion of its load forecasting information in the approved load forecast of its power supply borrower... participation in and inclusion of its load forecasting information in the approved load forecast of its...

  4. 7 CFR 1710.203 - Requirement to prepare a load forecast-distribution borrowers.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... forecasting information in the approved load forecast of its power supply borrower. The distribution borrower... forecasting information in the approved load forecast of its power supply borrower. The distribution borrower... inclusion of its load forecasting information in the approved load forecast of its power supply...

  5. 7 CFR 1710.203 - Requirement to prepare a load forecast-distribution borrowers.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... participation in and inclusion of its load forecasting information in the approved load forecast of its power... inclusion of its load forecasting information in the approved load forecast of its power supply borrower... participation in and inclusion of its load forecasting information in the approved load forecast of its...

  6. Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting

    SciTech Connect

    Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat

    2015-10-05

    Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.

  7. Chesapeake Bay Hypoxic Volume Forecasts and Results

    USGS Publications Warehouse

    Evans, Mary Anne; Scavia, Donald

    2013-01-01

    Given the average Jan-May 2013 total nitrogen load of 162,028 kg/day, this summer's hypoxia volume forecast is 6.1 km3, slightly smaller than average size for the period of record and almost the same as 2012. The late July 2013 measured volume was 6.92 km3.

  8. Increased Accuracy in Statistical Seasonal Hurricane Forecasting

    NASA Astrophysics Data System (ADS)

    Nateghi, R.; Quiring, S. M.; Guikema, S. D.

    2012-12-01

    Hurricanes are among the costliest and most destructive natural hazards in the U.S. Accurate hurricane forecasts are crucial to optimal preparedness and mitigation decisions in the U.S. where 50 percent of the population lives within 50 miles of the coast. We developed a flexible statistical approach to forecast annual number of hurricanes in the Atlantic region during the hurricane season. Our model is based on the method of Random Forest and captures the complex relationship between hurricane activity and climatic conditions through careful variable selection, model testing and validation. We used the National Hurricane Center's Best Track hurricane data from 1949-2011 and sixty-one candidate climate descriptors to develop our model. The model includes information prior to the hurricane season, i.e., from the last three months of the previous year (Oct. through Dec.) and the first five months of the current year (January through May). Our forecast errors are substantially lower than other leading forecasts such as that of the National Oceanic and Atmospheric Administration (NOAA).

  9. Enrollment Forecasting. Educational Facilities Digest 1.

    ERIC Educational Resources Information Center

    Piele, Philip; Wright, Darrell

    Enrollment forecasting is a subject for scholars of varied interests and concerns. The literature reflects several perspectives, including those of school administrators, facilities planners, mathematicians, statisticians, demographers, and computer programmers. This pamphlet contains an analysis and annotated bibliographies of 29 publications on…

  10. Forecasting Spacecraft Telemetry Using Modified Physical Predictions

    DTIC Science & Technology

    2010-10-01

    spacecraft and its environment are difficult to simulate and may change dramatically in a short period of time. This is particularly true of...Ryan Mackey 1 and Igor Kulikov 1 1 Reasoning, Modeling, and Simulation Group, Jet Propulsion Laboratory, California Institute of Technology...operational limits. Forecasting can be attempted statistically, or can be based on rigorous physical simulation . However, combining these

  11. Using Satellite Data in Weather Forecasting: I

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary J.; Suggs, Ronnie J.; Lecue, Juan M.

    2006-01-01

    The GOES Product Generation System (GPGS) is a set of computer codes and scripts that enable the assimilation of real-time Geostationary Operational Environmental Satellite (GOES) data into regional-weather-forecasting mathematical models. The GPGS can be used to derive such geophysical parameters as land surface temperature, the amount of precipitable water, the degree of cloud cover, the surface albedo, and the amount of insolation from satellite measurements of radiant energy emitted by the Earth and its atmosphere. GPGS incorporates a priori information (initial guesses of thermodynamic parameters of the atmosphere) and radiometric measurements from the geostationary operational environmental satellites along with mathematical models of physical principles that govern the transfer of energy in the atmosphere. GPGS solves the radiative-transfer equation and provides the resulting data products in formats suitable for use by weather-forecasting computer programs. The data-assimilation capability afforded by GPGS offers the potential to improve local weather forecasts ranging from 3 hours to 2 days - especially with respect to temperature, humidity, cloud cover, and the probability of precipitation. The improvements afforded by GPGS could be of interest to news media, utility companies, and other organizations that utilize regional weather forecasts.

  12. The Quest for the Perfect Weather Forecaster

    ERIC Educational Resources Information Center

    Kahl, Jonathan; Horwitz, Kevin; Berg, Craig; Gruhl, Mary

    2004-01-01

    It is said that meteorology is the only profession where a person can be wrong half the time and still keep his or her job. The truth is not quite so bleak, but one can still ask, "Just how accurate are weather forecasters, anyway?" This article presents two projects for middle level students to investigate this issue in a hands-on,…

  13. Forecasting sudden changes in environmental pollution patterns

    PubMed Central

    Olascoaga, María J.; Haller, George

    2012-01-01

    The lack of reliable forecasts for the spread of oceanic and atmospheric contamination hinders the effective protection of the ecosystem, society, and the economy from the fallouts of environmental disasters. The consequences can be dire, as evidenced by the Deepwater Horizon oil spill in the Gulf of Mexico in 2010. We present a methodology to predict major short-term changes in environmental contamination patterns, such as oil spills in the ocean and ash clouds in the atmosphere. Our approach is based on new mathematical results on the objective (frame-independent) identification of key material surfaces that drive tracer mixing in unsteady, finite-time flow data. Some of these material surfaces, known as Lagrangian coherent structures (LCSs), turn out to admit highly attracting cores that lead to inevitable material instabilities even under future uncertainties or unexpected perturbations to the observed flow. These LCS cores have the potential to forecast imminent shape changes in the contamination pattern, even before the instability builds up and brings large masses of water or air into motion. Exploiting this potential, the LCS-core analysis developed here provides a model-independent forecasting scheme that relies only on already observed or validated flow velocities at the time the prediction is made. We use this methodology to obtain high-precision forecasts of two major instabilities that occurred in the shape of the Deepwater Horizon oil spill. This is achieved using simulated surface currents preceding the prediction times and assuming that the oil behaves as a passive tracer. PMID:22411824

  14. FORECASTING AIR QUALITY OVER THE UNITED STATES

    EPA Science Inventory

    Increased awareness of national air quality issues on the part of the media and the general public have recently led to more demand for short-term (1-2 day) air quality forecasts for use in assessing potential health impacts (e.g., on children, the elderly, and asthmatics) and po...

  15. Applications products of aviation forecast models

    NASA Technical Reports Server (NTRS)

    Garthner, John P.

    1988-01-01

    A service called the Optimum Path Aircraft Routing System (OPARS) supplies products based on output data from the Naval Oceanographic Global Atmospheric Prediction System (NOGAPS), a model run on a Cyber-205 computer. Temperatures and winds are extracted from the surface to 100 mb, approximately 55,000 ft. Forecast winds are available in six-hour time steps.

  16. Forecasting Demand for Weapon System Items

    DTIC Science & Technology

    1994-07-01

    level at quarter n. SL(n) was set using the Presutti- Trepp model that DLA currently uses. Forecast error is required by the model to set the safety level...of inventory investment versus response time, we varied the safety level by changing the "lambda factor" or backorder cost used in the Presutti- Trepp

  17. Short time ahead wind power production forecast

    NASA Astrophysics Data System (ADS)

    Sapronova, Alla; Meissner, Catherine; Mana, Matteo

    2016-09-01

    An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast.

  18. Landslide forecasting and factors influencing predictability

    NASA Astrophysics Data System (ADS)

    Intrieri, Emanuele; Gigli, Giovanni

    2016-11-01

    Forecasting a catastrophic collapse is a key element in landslide risk reduction, but it is also a very difficult task owing to the scientific difficulties in predicting a complex natural event and also to the severe social repercussions caused by a false or missed alarm. A prediction is always affected by a certain error; however, when this error can imply evacuations or other severe consequences a high reliability in the forecast is, at least, desirable. In order to increase the confidence of predictions, a new methodology is presented here. In contrast to traditional approaches, this methodology iteratively applies several forecasting methods based on displacement data and, thanks to an innovative data representation, gives a valuation of the reliability of the prediction. This approach has been employed to back-analyse 15 landslide collapses. By introducing a predictability index, this study also contributes to the understanding of how geology and other factors influence the possibility of forecasting a slope failure. The results showed how kinematics, and all the factors influencing it, such as geomechanics, rainfall and other external agents, are key concerning landslide predictability.

  19. Issues in midterm analysis and forecasting 1998

    SciTech Connect

    1998-07-01

    Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.

  20. How Accurate Can Enrollment Forecasting Be?

    ERIC Educational Resources Information Center

    Shaw, Robert C.

    1980-01-01

    After briefly describing several methods of projecting enrollments, cites research indicating that the cohort survival method is best used as a relatively short-range forecast where in-migration and out-migration ratios are expected to remain fairly stable or to change at the same rate as they have in the recent past. (Author/IRT)

  1. Issues in midterm analysis and forecasting, 1996

    SciTech Connect

    1996-08-01

    This document consists of papers which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1996. Topics include: The Potential Impact of Technological Progress on U.S. Energy Markets; The Outlook for U.S. Import Dependence; Fuel Economy, Vehicle Choice, and Changing Demographics, and Annual Energy Outlook Forecast Evaluation.

  2. Principles of major geomagnetic storms forecasting

    NASA Astrophysics Data System (ADS)

    Zagnetko, Alexander; Applbaum, David; Dorman, Lev; Pustil'Nik, Lev; Sternlieb, Abraham; Zukerman, Igor

    According to NOAA Space Weather Scales, geomagnetic storms of scales G5 (3-hour index of geomagnetic activity Kp=9), G4 (Kp=8) and G3 (Kp=7) are dangerous for people technology and health (influence on power systems, on spacecraft operations, on HF radio-communications and others). To prevent these serious damages will be very important to forecast dangerous geomagnetic storms. In many papers it was shown that in principle for this forecasting can be used data on CR intensity and CR anisotropy changing before SC of major geomagnetic storms accompanied by sufficient Forbush-decreases (e.g., Dorman et al., 1995, 1999). In this paper we consider all types of observed precursor effects in CR what can be used for forecasting of great geomagnetic storms and possible mechanisms of these precursor effects origin. REFERENCES: Dorman L.I., et al. "Cosmic-ray forecasting features for big Forbush-decreases". Nuclear Physics B, 49A, 136-144 (1995). L.I.Dorman, et al, "Cosmic ray Forbush-decrease as indicators of space dangerous phenomenon and possible use of cosmic ray data for their pre-diction", Proc. of 26-th Intern. Cosmic Ray Conference, Salt Lake City, 6, 476-479 (1999).

  3. Forecasting and management of hop downy mildew

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Downy mildew of hop, caused by Pseudoperonospora humuli, is managed in the Pacific Northwestern U.S. by regular application of fungicides. A degree-day model that forecasts the first emergence of shoots systemically infection with P. humuli (termed basal spikes) and a risk index for secondary sprea...

  4. PROPHET: An applicaton of propagation forecasting principles

    NASA Technical Reports Server (NTRS)

    Argo, P. E.; Rothmuller, I. J.

    1979-01-01

    A propagation assessment and forecasting terminal, PROPHET, is described. The terminal is a key element of the environmental prediction and assessment system which uses real time solar/geophysical data to provide real time knowledge of propagation conditions. The terminal uses models to translate data from satellite and ground based sources into performance predictions for specific systems.

  5. Weather forecasting with open source software

    NASA Astrophysics Data System (ADS)

    Rautenhaus, Marc; Dörnbrack, Andreas

    2013-04-01

    To forecast the weather situation during aircraft-based atmospheric field campaigns, we employ a tool chain of existing and self-developed open source software tools and open standards. Of particular value are the Python programming language with its extension libraries NumPy, SciPy, PyQt4, Matplotlib and the basemap toolkit, the NetCDF standard with the Climate and Forecast (CF) Metadata conventions, and the Open Geospatial Consortium Web Map Service standard. These open source libraries and open standards helped to implement the "Mission Support System", a Web Map Service based tool to support weather forecasting and flight planning during field campaigns. The tool has been implemented in Python and has also been released as open source (Rautenhaus et al., Geosci. Model Dev., 5, 55-71, 2012). In this presentation we discuss the usage of free and open source software for weather forecasting in the context of research flight planning, and highlight how the field campaign work benefits from using open source tools and open standards.

  6. Visually Comparing Weather Features in Forecasts.

    PubMed

    Quinan, P Samuel; Meyer, Miriah

    2016-01-01

    Meteorologists process and analyze weather forecasts using visualization in order to examine the behaviors of and relationships among weather features. In this design study conducted with meteorologists in decision support roles, we identified and attempted to address two significant common challenges in weather visualization: the employment of inconsistent and often ineffective visual encoding practices across a wide range of visualizations, and a lack of support for directly visualizing how different weather features relate across an ensemble of possible forecast outcomes. In this work, we present a characterization of the problems and data associated with meteorological forecasting, we propose a set of informed default encoding choices that integrate existing meteorological conventions with effective visualization practice, and we extend a set of techniques as an initial step toward directly visualizing the interactions of multiple features over an ensemble forecast. We discuss the integration of these contributions into a functional prototype tool, and also reflect on the many practical challenges that arise when working with weather data.

  7. Flood Warning and Forecasting System in Slovakia

    NASA Astrophysics Data System (ADS)

    Leskova, Danica

    2016-04-01

    In 2015, it finished project Flood Warning and Forecasting System (POVAPSYS) as part of the flood protection in Slovakia till 2010. The aim was to build POVAPSYS integrated computerized flood forecasting and warning system. It took a qualitatively higher level of output meteorological and hydrological services in case of floods affecting large territorial units, as well as local flood events. It is further unfolding demands on performance and coordination of meteorological and hydrological services, troubleshooting observation, evaluation of data, fast communication, modeling and forecasting of meteorological and hydrological processes. Integration of all information entering and exiting to and from the project POVAPSYS provides Hydrological Flood Forecasting System (HYPOS). The system provides information on the current hydrometeorological situation and its evolution with the generation of alerts and notifications in case of exceeding predefined thresholds. HYPOS's functioning of the system requires flawless operability in critical situations while minimizing the loss of its key parts. HYPOS is a core part of the project POVAPSYS, it is a comprehensive software solutions based on a modular principle, providing data and processed information including alarms, in real time. In order to achieve full functionality of the system, in proposal, we have put emphasis on reliability, robustness, availability and security.

  8. Data Analysis, Modeling, and Ensemble Forecasting to Support NOWCAST and Forecast Activities at the Fallon Naval Air Station

    DTIC Science & Technology

    2008-09-30

    Weather and Research Forecasting model (WRF); 3) To include at a later stage the Coastal Oceanic and Atmospheric Modeling Prediction System ( COAMPS ...charts and animations, Other useful links, Ensemble forecasting (in construction), Forecast of transport and dispersion of dust and pollutants, Model...regional­ mesoscale multi-model ( COAMPS , WRF, and MM5) ensemble forecasting (Lewis 2005). In this initial phase of the development of the multi-model

  9. 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

  10. Ensemble postprocessing for probabilistic quantitative precipitation forecasts

    NASA Astrophysics Data System (ADS)

    Bentzien, S.; Friederichs, P.

    2012-12-01

    Precipitation is one of the most difficult weather variables to predict in hydrometeorological applications. In order to assess the uncertainty inherent in deterministic numerical weather prediction (NWP), meteorological services around the globe develop ensemble prediction systems (EPS) based on high-resolution NWP systems. With non-hydrostatic model dynamics and without parameterization of deep moist convection, high-resolution NWP models are able to describe convective processes in more detail and provide more realistic mesoscale structures. However, precipitation forecasts are still affected by displacement errors, systematic biases and fast error growth on small scales. Probabilistic guidance can be achieved from an ensemble setup which accounts for model error and uncertainty of initial and boundary conditions. The German Meteorological Service (Deutscher Wetterdienst, DWD) provides such an ensemble system based on the German-focused limited-area model COSMO-DE. With a horizontal grid-spacing of 2.8 km, COSMO-DE is the convection-permitting high-resolution part of the operational model chain at DWD. The COSMO-DE-EPS consists of 20 realizations of COSMO-DE, driven by initial and boundary conditions derived from 4 global models and 5 perturbations of model physics. Ensemble systems like COSMO-DE-EPS are often limited with respect to ensemble size due to the immense computational costs. As a consequence, they can be biased and exhibit insufficient ensemble spread, and probabilistic forecasts may be not well calibrated. In this study, probabilistic quantitative precipitation forecasts are derived from COSMO-DE-EPS and evaluated at more than 1000 rain gauges located all over Germany. COSMO-DE-EPS is a frequently updated ensemble system, initialized 8 times a day. We use the time-lagged approach to inexpensively increase ensemble spread, which results in more reliable forecasts especially for extreme precipitation events. Moreover, we will show that statistical

  11. Diagnostic studies of ensemble forecast "jumps"

    NASA Astrophysics Data System (ADS)

    Magnusson, Linus; Hewson, Tim; Ferranti, Laura; Rodwell, Mark

    2016-04-01

    During 2015 we saw exceptional consistency in successive seasonal forecasts produced at ECMWF, for the winter period 2015/16, right across the globe. This winter was characterised by a well-predicted and unusually strong El Nino, and some have ascribed the consistency to that. For most of December this consistency was mirrored in the (separate) ECMWF monthly forecast system, which correctly predicted anomalously strong (mild) zonal flow, over the North Atlantic and western Eurasia, even in forecasts for weeks 3 and 4. In monthly forecasts in general these weeks are often devoid of strong signals. However in late December and early January strong signals, even in week 2, proved to be incorrect, most notably over the North Atlantic and Eurasian sectors. Indeed on at least two occasions the outcome was beyond the ensemble forecast range over Scandinavia. In one of these conditions flipped from extreme mild to extreme cold as a high latitude block developed. Temperature prediction is very important to many customers, notably those dealing with renewable energy, because cold weather causes increased demand but also tends to coincide with reduced wind power production. So understandably jumps can cause consternation amongst some customer groups, and are very difficult to handle operationally. This presentation will discuss the results of initial diagnostic investigations into what caused the "ensemble jumps", particularly at the week two lead, though reference will also be made to a related shorter range (day 3) jump that was important for flooding over the UK. Initial results suggest that an inability of the ECMWF model to correctly represent convective outbreaks over North America (that for winter-time were quite extreme) played an important role. Significantly, during this period, an unusually large amount of upper air data over North America was rejected or ascribed low weight. These results bear similarities to previous diagnostic studies at ECMWF, wherein major

  12. Modeling, Simulation, and Forecasting of Subseasonal Variability

    NASA Technical Reports Server (NTRS)

    Waliser, Duane; Schubert, Siegfried; Kumar, Arun; Weickmann, Klaus; Dole, Randall

    2003-01-01

    A planning workshop on "Modeling, Simulation and Forecasting of Subseasonal Variability" was held in June 2003. This workshop was the first of a number of meetings planned to follow the NASA-sponsored workshop entitled "Prospects For Improved Forecasts Of Weather And Short-Term Climate Variability On Sub-Seasonal Time Scales" that was held April 2002. The 2002 workshop highlighted a number of key sources of unrealized predictability on subseasonal time scales including tropical heating, soil wetness, the Madden Julian Oscillation (MJO) [a.k.a Intraseasonal Oscillation (ISO)], the Arctic Oscillation (AO) and the Pacific/North American (PNA) pattern. The overarching objective of the 2003 follow-up workshop was to proceed with a number of recommendations made from the 2002 workshop, as well as to set an agenda and collate efforts in the areas of modeling, simulation and forecasting intraseasonal and short-term climate variability. More specifically, the aims of the 2003 workshop were to: 1) develop a baseline of the "state of the art" in subseasonal prediction capabilities, 2) implement a program to carry out experimental subseasonal forecasts, and 3) develop strategies for tapping the above sources of predictability by focusing research, model development, and the development/acquisition of new observations on the subseasonal problem. The workshop was held over two days and was attended by over 80 scientists, modelers, forecasters and agency personnel. The agenda of the workshop focused on issues related to the MJO and tropicalextratropical interactions as they relate to the subseasonal simulation and prediction problem. This included the development of plans for a coordinated set of GCM hindcast experiments to assess current model subseasonal prediction capabilities and shortcomings, an emphasis on developing a strategy to rectify shortcomings associated with tropical intraseasonal variability, namely diabatic processes, and continuing the implementation of an

  13. Forecasting production in Liquid Rich Shale plays

    NASA Astrophysics Data System (ADS)

    Nikfarman, Hanieh

    Production from Liquid Rich Shale (LRS) reservoirs is taking center stage in the exploration and production of unconventional reservoirs. Production from the low and ultra-low permeability LRS plays is possible only through multi-fractured horizontal wells (MFHW's). There is no existing workflow that is applicable to forecasting multi-phase production from MFHW's in LRS plays. This project presents a practical and rigorous workflow for forecasting multiphase production from MFHW's in LRS reservoirs. There has been much effort in developing workflows and methodology for forecasting in tight/shale plays in recent years. The existing workflows, however, are applicable only to single phase flow, and are primarily used in shale gas plays. These methodologies do not apply to the multi-phase flow that is inevitable in LRS plays. To account for complexities of multiphase flow in MFHW's the only available technique is dynamic modeling in compositional numerical simulators. These are time consuming and not practical when it comes to forecasting production and estimating reserves for a large number of producers. A workflow was developed, and validated by compositional numerical simulation. The workflow honors physics of flow, and is sufficiently accurate while practical so that an analyst can readily apply it to forecast production and estimate reserves in a large number of producers in a short period of time. To simplify the complex multiphase flow in MFHW, the workflow divides production periods into an initial period where large production and pressure declines are expected, and the subsequent period where production decline may converge into a common trend for a number of producers across an area of interest in the field. Initial period assumes the production is dominated by single-phase flow of oil and uses the tri-linear flow model of Erdal Ozkan to estimate the production history. Commercial software readily available can simulate flow and forecast production in this

  14. The Wind Forecast Improvement Project (WFIP). A Public-Private Partnership Addressing Wind Energy Forecast Needs

    SciTech Connect

    Wilczak, James M.; Finley, Cathy; Freedman, Jeff; Cline, Joel; Bianco, L.; Olson, J.; Djalaova, I.; Sheridan, L.; Ahlstrom, M.; Manobianco, J.; Zack, J.; Carley, J.; Benjamin, S.; Coulter, R. L.; Berg, Larry K.; Mirocha, Jeff D.; Clawson, K.; Natenberg, E.; Marquis, M.

    2015-10-30

    The Wind Forecast Improvement Project (WFIP) is a public-private research program, the goals of which are to improve the accuracy of short-term (0-6 hr) wind power forecasts for the wind energy industry and then to quantify the economic savings that accrue from more efficient integration of wind energy into the electrical grid. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that include the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models to improve model initial conditions; and second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the U.S. (the upper Great Plains, and Texas), and included 12 wind profiling radars, 12 sodars, 184 instrumented tall towers and over 400 nacelle anemometers (provided by private industry), lidar, and several surface flux stations. Results demonstrate that a substantial improvement of up to 14% relative reduction in power root mean square error (RMSE) was achieved from the combination of improved NOAA numerical weather prediction (NWP) models and assimilation of the new observations. Data denial experiments run over select periods of time demonstrate that up to a 6% relative improvement came from the new observations. The use of ensemble forecasts produced even larger forecast improvements. Based on the success of WFIP, DOE is planning follow-on field programs.

  15. Seasonal UK Drought Forecasting using Statistical Methods

    NASA Astrophysics Data System (ADS)

    Richardson, Doug; Fowler, Hayley; Kilsby, Chris; Serinaldi, Francesco

    2016-04-01

    In the UK drought is a recurrent feature of climate with potentially large impacts on public water supply. Water companies' ability to mitigate the impacts of drought by managing diminishing availability depends on forward planning and it would be extremely valuable to improve forecasts of drought on monthly to seasonal time scales. By focusing on statistical forecasting methods, this research aims to provide techniques that are simpler, faster and computationally cheaper than physically based models. In general, statistical forecasting is done by relating the variable of interest (some hydro-meteorological variable such as rainfall or streamflow, or a drought index) to one or more predictors via some formal dependence. These predictors are generally antecedent values of the response variable or external factors such as teleconnections. A candidate model is Generalised Additive Models for Location, Scale and Shape parameters (GAMLSS). GAMLSS is a very flexible class allowing for more general distribution functions (e.g. highly skewed and/or kurtotic distributions) and the modelling of not just the location parameter but also the scale and shape parameters. Additionally GAMLSS permits the forecasting of an entire distribution, allowing the output to be assessed in probabilistic terms rather than simply the mean and confidence intervals. Exploratory analysis of the relationship between long-memory processes (e.g. large-scale atmospheric circulation patterns, sea surface temperatures and soil moisture content) and drought should result in the identification of suitable predictors to be included in the forecasting model, and further our understanding of the drivers of UK drought.

  16. 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

  17. Review of techniques for magnetic storm forecasting

    NASA Astrophysics Data System (ADS)

    Detman, Thomas R.; Vassiliadis, Dimitris

    Today a wide variety of techniques are available for nowcasting and forecasting magnetic storm activity. A brief review of linear time series prediction techniques, with examples, is used to lay a foundation for the description of newer non-linear techniques based on state-space reconstruction. We illustrate the state-space prediction technique in application to predict Dst from ISEE-3 solar wind data. Upstream solar wind data, such as from ISEE-3 or WTND close to the L1 libration point, provide a prediction lead time of 0.5-1.5 hours. To go beyond the L1 prediction lead time some information about the solar wind between the Li point and the Sun is required. Remote sensing is the measurement of something from a distance, like solar magnetograms or X-ray images. Both empirical and physically based models, driven by remote sensing data, promise a way to make forecasts a few days into the future. A combination of the statistical time series prediction techniques operating on the output of physically based models, driven by remote sensing data, may offer the first capability of predicting magnetic storms a few days in advance. We illustrate this combination of techniques using the output of a potential field model [Wang and Sheeley, 1988] as input to a linear prediction filter to forecast the planetary geomagnetic index. Finally, practical forecasting requires verification. We describe some of the standard measures of forecast performance: skill score, prediction efficiency, and correlation coefficient. The value of cross validation testing is emphasized.

  18. UNCERTAINTY IN THE GLOBAL FORECAST SYSTEM

    SciTech Connect

    Werth, D.; Garrett, A.

    2009-04-15

    We validated one year of Global Forecast System (GFS) predictions of surface meteorological variables (wind speed, air temperature, dewpoint temperature, air pressure) over the entire planet for forecasts extending from zero hours into the future (an analysis) to 36 hours. Approximately 12,000 surface stations world-wide were included in this analysis. Root-Mean-Square- Errors (RMSE) increased as the forecast period increased from zero to 36 hours, but the initial RMSE were almost as large as the 36 hour forecast RMSE for all variables. Typical RMSE were 3 C for air temperature, 2-3mb for sea-level pressure, 3.5 C for dewpoint temperature and 2.5 m/s for wind speed. Approximately 20-40% of the GFS errors can be attributed to a lack of resolution of local features. We attribute the large initial RMSE for the zero hour forecasts to the inability of the GFS to resolve local terrain features that often dominate local weather conditions, e.g., mountain- valley circulations and sea and land breezes. Since the horizontal resolution of the GFS (about 1{sup o} of latitude and longitude) prevents it from simulating these locally-driven circulations, its performance will not improve until model resolution increases by a factor of 10 or more (from about 100 km to less than 10 km). Since this will not happen in the near future, an alternative for the near term to improve surface weather analyses and predictions for specific points in space and time would be implementation of a high-resolution, limited-area mesoscale atmospheric prediction model in regions of interest.

  19. Operational forecasting based on a modified Weather Research and Forecasting model

    SciTech Connect

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

    Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

  20. Real-time Social Internet Data to Guide Forecasting Models

    SciTech Connect

    Del Valle, Sara Y.

    2016-09-20

    Our goal is to improve decision support by monitoring and forecasting events using social media, mathematical models, and quantifying model uncertainty. Our approach is real-time, data-driven forecasts with quantified uncertainty: Not just for weather anymore. Information flow from human observations of events through an Internet system and classification algorithms is used to produce quantitatively uncertain forecast. In summary, we want to develop new tools to extract useful information from Internet data streams, develop new approaches to assimilate real-time information into predictive models, validate approaches by forecasting events, and our ultimate goal is to develop an event forecasting system using mathematical approaches and heterogeneous data streams.

  1. Official forecasts pushed out to a year ahead

    SciTech Connect

    Kerr, R.A.

    1994-12-23

    The National Weather Service is about to unveil 15 month forecasting. NWS will not be predicting individual storms in these long-range forecasts, but rather large regions of above, below, or near normal temperature and precipitation. NWS meterologists are adopting three standard techniques for long-range forecasting, two based on objective methods for forecasting El Nino, and one, canonical correlation analysis, an effort to systematize what forecasters already do, looking for its of impending El Nino and other signs of imminent climatic change. 2 figs.

  2. A neural network short-term forecast of significant thunderstorms

    SciTech Connect

    Mccann, D.W. )

    1992-09-01

    Neural networks, an artificial-intelligence tools that excels in pattern recognition, are reviewed, and a 3-7-h significant thunderstorm forecast developed with this technique is discussed. Two neural networks learned to forecast significant thunderstorms from fields of surface-based lifted index and surface moisture convergence. These networks are sensitive to the patterns that skilled forecasters recognize as occurring prior to strong thunderstorms. The two neural networks are combined operationally at the National Severe Storm Forecast Center into a single hourly product that enhances pattern-recognition skills. Examples of neural network products are shown, and their potential impact on significant thunderstorm forecasting is demonstrated. 22 refs.

  3. International Cooperative for Aerosol Prediction Workshop on Aerosol Forecast Verification

    NASA Technical Reports Server (NTRS)

    Benedetti, Angela; Reid, Jeffrey S.; Colarco, Peter R.

    2011-01-01

    The purpose of this workshop was to reinforce the working partnership between centers who are actively involved in global aerosol forecasting, and to discuss issues related to forecast verification. Participants included representatives from operational centers with global aerosol forecasting requirements, a panel of experts on Numerical Weather Prediction and Air Quality forecast verification, data providers, and several observers from the research community. The presentations centered on a review of current NWP and AQ practices with subsequent discussion focused on the challenges in defining appropriate verification measures for the next generation of aerosol forecast systems.

  4. Forecastability as a Design Criterion in Wind Resource Assessment: Preprint

    SciTech Connect

    Zhang, J.; Hodge, B. M.

    2014-04-01

    This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

  5. NASA Products to Enhance Energy Utility Load Forecasting

    NASA Technical Reports Server (NTRS)

    Lough, G.; Zell, E.; Engel-Cox, J.; Fungard, Y.; Jedlovec, G.; Stackhouse, P.; Homer, R.; Biley, S.

    2012-01-01

    Existing energy load forecasting tools rely upon historical load and forecasted weather to predict load within energy company service areas. The shortcomings of load forecasts are often the result of weather forecasts that are not at a fine enough spatial or temporal resolution to capture local-scale weather events. This project aims to improve the performance of load forecasting tools through the integration of high-resolution, weather-related NASA Earth Science Data, such as temperature, relative humidity, and wind speed. Three companies are participating in operational testing one natural gas company, and two electric providers. Operational results comparing load forecasts with and without NASA weather forecasts have been generated since March 2010. We have worked with end users at the three companies to refine selection of weather forecast information and optimize load forecast model performance. The project will conclude in 2012 with transitioning documented improvements from the inclusion of NASA forecasts for sustained use by energy utilities nationwide in a variety of load forecasting tools. In addition, Battelle has consulted with energy companies nationwide to document their information needs for long-term planning, in light of climate change and regulatory impacts.

  6. Wind power forecasting: IEA Wind Task 36 & future research issues

    SciTech Connect

    Giebel, G.; Cline, J.; Frank, H.; Shaw, W.; Pinson, P.; Hodge, B-M; Kariniotakis, G.; Madsen, J.; Möhrlen, C.

    2016-10-03

    Here, this paper presents the new International Energy Agency Wind Task 36 on Forecasting, and invites to collaborate within the group. Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, MetOffice, met.no, DMI,...), operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. As first results, an overview of current issues for research in short-term forecasting of wind power is presented.

  7. Wind power forecasting: IEA Wind Task 36 & future research issues

    DOE PAGES

    Giebel, G.; Cline, J.; Frank, H.; ...

    2016-10-03

    Here, this paper presents the new International Energy Agency Wind Task 36 on Forecasting, and invites to collaborate within the group. Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, MetOffice, met.no, DMI,...), operational forecaster and forecast users. The Taskmore » is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. As first results, an overview of current issues for research in short-term forecasting of wind power is presented.« less

  8. Wind power forecasting: IEA Wind Task 36 & future research issues

    NASA Astrophysics Data System (ADS)

    Giebel, G.; Cline, J.; Frank, H.; Shaw, W.; Pinson, P.; Hodge, B.-M.; Kariniotakis, G.; Madsen, J.; Möhrlen, C.

    2016-09-01

    This paper presents the new International Energy Agency Wind Task 36 on Forecasting, and invites to collaborate within the group. Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, MetOffice, met.no, DMI,...), operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. As first results, an overview of current issues for research in short-term forecasting of wind power is presented.

  9. Forecast skill impact of drifting buoys in the Southern Hemisphere

    NASA Technical Reports Server (NTRS)

    Kalnay, E.; Atlas, R.; Baker, W.; Halem, M.

    1984-01-01

    Two analyses are performed to evaluate the effect of drift buoys and the FGGE's special observing system (SOS) on forecasting. The FGGE analysis utilizes all level II-b conventional and special data, and the Nosat analysis employs only surface and conventional upper air data. Twelve five-day forecasts are produced from these data. An additional experiment utilizing the FGGE data base minus buoys data, and the Nosat data base including buoys data is being conducted. The forecasts are compared and synoptic evaluation of the effect of buoys data is described. The results reveal that the FGGE data base with the SOS significantly improves forecasting in the Southern Hemisphere and the loss of buoys data does not have a great effect on forecasting. The Nosat data has less impact on forecasting; however, the addition of buoys data provides an improvement in forecast skills.

  10. Multivariate postprocessing techniques for probabilistic hydrological forecasting

    NASA Astrophysics Data System (ADS)

    Hemri, Stephan; Lisniak, Dmytro; Klein, Bastian

    2016-04-01

    Hydrologic ensemble forecasts driven by atmospheric ensemble prediction systems need statistical postprocessing in order to account for systematic errors in terms of both mean and spread. Runoff is an inherently multivariate process with typical events lasting from hours in case of floods to weeks or even months in case of droughts. This calls for multivariate postprocessing techniques that yield well calibrated forecasts in univariate terms and ensure a realistic temporal dependence structure at the same time. To this end, the univariate ensemble model output statistics (EMOS; Gneiting et al., 2005) postprocessing method is combined with two different copula approaches that ensure multivariate calibration throughout the entire forecast horizon. These approaches comprise ensemble copula coupling (ECC; Schefzik et al., 2013), which preserves the dependence structure of the raw ensemble, and a Gaussian copula approach (GCA; Pinson and Girard, 2012), which estimates the temporal correlations from training observations. Both methods are tested in a case study covering three subcatchments of the river Rhine that represent different sizes and hydrological regimes: the Upper Rhine up to the gauge Maxau, the river Moselle up to the gauge Trier, and the river Lahn up to the gauge Kalkofen. The results indicate that both ECC and GCA are suitable for modelling the temporal dependences of probabilistic hydrologic forecasts (Hemri et al., 2015). References Gneiting, T., A. E. Raftery, A. H. Westveld, and T. Goldman (2005), Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation, Monthly Weather Review, 133(5), 1098-1118, DOI: 10.1175/MWR2904.1. Hemri, S., D. Lisniak, and B. Klein, Multivariate postprocessing techniques for probabilistic hydrological forecasting, Water Resources Research, 51(9), 7436-7451, DOI: 10.1002/2014WR016473. Pinson, P., and R. Girard (2012), Evaluating the quality of scenarios of short-term wind power

  11. Seasonal streamflow forecasting by conditioning climatology with precipitation indices

    NASA Astrophysics Data System (ADS)

    Crochemore, Louise; Ramos, Maria-Helena; Pappenberger, Florian; Perrin, Charles

    2017-03-01

    Many fields, such as drought-risk assessment or reservoir management, can benefit from long-range streamflow forecasts. Climatology has long been used in long-range streamflow forecasting. Conditioning methods have been proposed to select or weight relevant historical time series from climatology. They are often based on general circulation model (GCM) outputs that are specific to the forecast date due to the initialisation of GCMs on current conditions. This study investigates the impact of conditioning methods on the performance of seasonal streamflow forecasts. Four conditioning statistics based on seasonal forecasts of cumulative precipitation and the standardised precipitation index were used to select relevant traces within historical streamflows and precipitation respectively. This resulted in eight conditioned streamflow forecast scenarios. These scenarios were compared to the climatology of historical streamflows, the ensemble streamflow prediction approach and the streamflow forecasts obtained from ECMWF System 4 precipitation forecasts. The impact of conditioning was assessed in terms of forecast sharpness (spread), reliability, overall performance and low-flow event detection. Results showed that conditioning past observations on seasonal precipitation indices generally improves forecast sharpness, but may reduce reliability, with respect to climatology. Conversely, conditioned ensembles were more reliable but less sharp than streamflow forecasts derived from System 4 precipitation. Forecast attributes from conditioned and unconditioned ensembles are illustrated for a case of drought-risk forecasting: the 2003 drought in France. In the case of low-flow forecasting, conditioning results in ensembles that can better assess weekly deficit volumes and durations over a wider range of lead times.

  12. ECMWF Extreme Forecast Index for water vapor transport: A forecast tool for atmospheric rivers and extreme precipitation

    NASA Astrophysics Data System (ADS)

    Lavers, David A.; Pappenberger, Florian; Richardson, David S.; Zsoter, Ervin

    2016-11-01

    In winter, heavy precipitation and floods along the west coasts of midlatitude continents are largely caused by intense water vapor transport (integrated vapor transport (IVT)) within the atmospheric river of extratropical cyclones. This study builds on previous findings that showed that forecasts of IVT have higher predictability than precipitation, by applying and evaluating the European Centre for Medium-Range Weather Forecasts Extreme Forecast Index (EFI) for IVT in ensemble forecasts during three winters across Europe. We show that the IVT EFI is more able (than the precipitation EFI) to capture extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase; conversely, the precipitation EFI is better during the negative NAO phase and at shorter leads. An IVT EFI example for storm Desmond in December 2015 highlights its potential to identify upcoming hydrometeorological extremes, which may prove useful to the user and forecasting communities.

  13. Forecasting urban highway travel for year 2005

    SciTech Connect

    Miaou, Shaw-Pin . Transportation Center); Rathi, A.K.; Southworth, F.; Greene, D.L. )

    1990-08-01

    As part of a study aimed at estimating suburban highway needs for year 2005, models were developed for forecasting daily vehicle miles of travel (DVMT) for urban areas and its distribution by highway functional class, urban location, and urban area size. A regression model combining both time series and cross-sectional data is used to establish the relationship between the per capita DVMT of 339 urban areas in the United States and a set of explanatory variables including real income, employment, number of persons per household, number of driver licenses per 1000 persons, a variable representing highway supply deficiency, and a time variable. The dynamic shift over time in share of travel between urban locations and highway functional classes as urban areas grow in size is represented by conditional logit models. This paper presents the major findings from the forecasting and distribution models for urban highway travel in year 2005. 30 refs., 3 figs., 9 tabs.

  14. Weather forecasting support for AASE-2

    NASA Technical Reports Server (NTRS)

    Forbes, Gregory S.

    1992-01-01

    The AFEAS Contract and NASA Grant were awarded to Penn State in order to obtain real-time weather forecasting support for the NASA AASE-II Project, which was conducted between October 1991 and March 1992. Because of the special weather sensitivities of the NASA ER-2 aircraft, AASE-II planners felt that public weather forecasts issued by the National Weather Service would not be adequate for mission planning purposes. A likely consequence of resorting to that medium would have been that scientists would have had to be at work by 4 AM day after day in the hope that the aircraft could fly, only to be frustrated by a great number of 'scrubbed' missions. Thus, the Pennsylvania State University was contracted to provide real-time weather support to the AASE-II mission.

  15. Forecasting residual herbicide concentrations in soil

    NASA Astrophysics Data System (ADS)

    McGrath, Gavan; Scanlan, Craig; van Zwieten, Lukas; Rose, Mick; Rose, Terry

    2016-04-01

    High concentrations of herbicides remaining in soil at the time of planting can adversely impact agricultural production and lead to off-site impacts in streams and groundwater. Being able to forecast the likelihood of residual concentrations at specific times in the future offers the potential to improve environmental and economic outcomes. Here we develop a solution for the full transient probability density function for herbicide concentrations in soil as a function of rainfall variability. Quasi-analytical solutions that account for rainfall seasonality are also demonstrated. In addition, new rapid and relatively cost-effective bioassays to quantify herbicide concentrations in near real-time, offers opportunities for data assimilation approaches to improve forecast risks.

  16. Probabilistic forecasts based on radar rainfall uncertainty

    NASA Astrophysics Data System (ADS)

    Liguori, S.; Rico-Ramirez, M. A.

    2012-04-01

    The potential advantages resulting from integrating weather radar rainfall estimates in hydro-meteorological forecasting systems is limited by the inherent uncertainty affecting radar rainfall measurements, which is due to various sources of error [1-3]. The improvement of quality control and correction techniques is recognized to play a role for the future improvement of radar-based flow predictions. However, the knowledge of the uncertainty affecting radar rainfall data can also be effectively used to build a hydro-meteorological forecasting system in a probabilistic framework. This work discusses the results of the implementation of a novel probabilistic forecasting system developed to improve ensemble predictions over a small urban area located in the North of England. An ensemble of radar rainfall fields can be determined as the sum of a deterministic component and a perturbation field, the latter being informed by the knowledge of the spatial-temporal characteristics of the radar error assessed with reference to rain-gauges measurements. This approach is similar to the REAL system [4] developed for use in the Southern-Alps. The radar uncertainty estimate can then be propagated with a nowcasting model, used to extrapolate an ensemble of radar rainfall forecasts, which can ultimately drive hydrological ensemble predictions. A radar ensemble generator has been calibrated using radar rainfall data made available from the UK Met Office after applying post-processing and corrections algorithms [5-6]. One hour rainfall accumulations from 235 rain gauges recorded for the year 2007 have provided the reference to determine the radar error. Statistics describing the spatial characteristics of the error (i.e. mean and covariance) have been computed off-line at gauges location, along with the parameters describing the error temporal correlation. A system has then been set up to impose the space-time error properties to stochastic perturbations, generated in real-time at

  17. Operational earthquake forecasting can enhance earthquake preparedness

    USGS Publications Warehouse

    Jordan, T.H.; Marzocchi, W.; Michael, A.J.; Gerstenberger, M.C.

    2014-01-01

    We cannot yet predict large earthquakes in the short term with much reliability and skill, but the strong clustering exhibited in seismic sequences tells us that earthquake probabilities are not constant in time; they generally rise and fall over periods of days to years in correlation with nearby seismic activity. Operational earthquake forecasting (OEF) is the dissemination of authoritative information about these time‐dependent probabilities to help communities prepare for potentially destructive earthquakes. The goal of OEF is to inform the decisions that people and organizations must continually make to mitigate seismic risk and prepare for potentially destructive earthquakes on time scales from days to decades. To fulfill this role, OEF must provide a complete description of the seismic hazard—ground‐motion exceedance probabilities as well as short‐term rupture probabilities—in concert with the long‐term forecasts of probabilistic seismic‐hazard analysis (PSHA).

  18. Hurricane track forecast cones from fluctuations.

    PubMed

    Meuel, T; Prado, G; Seychelles, F; Bessafi, M; Kellay, H

    2012-01-01

    Trajectories of tropical cyclones may show large deviations from predicted tracks leading to uncertainty as to their landfall location for example. Prediction schemes usually render this uncertainty by showing track forecast cones representing the most probable region for the location of a cyclone during a period of time. By using the statistical properties of these deviations, we propose a simple method to predict possible corridors for the future trajectory of a cyclone. Examples of this scheme are implemented for hurricane Ike and hurricane Jimena. The corridors include the future trajectory up to at least 50 h before landfall. The cones proposed here shed new light on known track forecast cones as they link them directly to the statistics of these deviations.

  19. Forecasting droughts in West Africa: Operational practice and refined seasonal precipitation forecasts

    NASA Astrophysics Data System (ADS)

    Bliefernicht, Jan; Siegmund, Jonatan; Seidel, Jochen; Arnold, Hanna; Waongo, Moussa; Laux, Patrick; Kunstmann, Harald

    2016-04-01

    Precipitation forecasts for the upcoming rainy seasons are one of the most important sources of information for an early warning of droughts and water scarcity in West Africa. The meteorological services in West Africa perform seasonal precipitation forecasts within the framework of PRESAO (the West African climate outlook forum) since the end of the 1990s. Various sources of information and statistical techniques are used by the individual services to provide a harmonized seasonal precipitation forecasts for decision makers in West Africa. In this study, we present a detailed overview of the operational practice in West Africa including a first statistical assessment of the performance of the precipitation forecasts for drought situations for the past 18 years (1998 to 2015). In addition, a long-term hindcasts (1982 to 2009) and a semi-operational experiment for the rainy season 2013 using statistical and/or dynamical downscaling are performed to refine the precipitation forecasts from the Climate Forecast System Version 2 (CFSv2), a global ensemble prediction system. This information is post-processed to provide user-oriented precipitation indices such as the onset of the rainy season for supporting water and land use management for rain-fed agriculture. The evaluation of the individual techniques is performed focusing on water-scarce regions of the Volta basin in Burkina Faso and Ghana. The forecasts of the individual techniques are compared to state-of-the-art global observed precipitation products and a novel precipitation database based on long-term daily rain-gage measurements provided by the national meteorological services. The statistical assessment of the PRESAO forecasts indicates skillful seasonal precipitation forecasts for many locations in the Volta basin, particularly for years with water deficits. The operational experiment for the rainy season 2013 illustrates the high potential of a physically-based downscaling for this region but still shows

  20. Global uncertainty assessment in hydrological forecasting by means of statistical analysis of forecast errors

    NASA Astrophysics Data System (ADS)

    Montanari, A.; Grossi, G.

    2007-12-01

    It is well known that uncertainty assessment in hydrological forecasting is a topical issue. Already in 1905 W.E. Cooke, who was issuing daily weather forecasts in Australia, stated: "It seems to me that the condition of confidence or otherwise form a very important part of the prediction, and ought to find expression". Uncertainty assessment in hydrology involves the analysis of multiple sources of error. The contribution of these latter to the formation of the global uncertainty cannot be quantified independently, unless (a) one is willing to introduce subjective assumptions about the nature of the individual error components or (2) independent observations are available for estimating input error, model error, parameter error and state error. An alternative approach, that is applied in this study and still requires the introduction of some assumptions, is to quantify the global hydrological uncertainty in an integrated way, without attempting to quantify each independent contribution. This methodology can be applied in situations characterized by limited data availability and therefore is gaining increasing attention by end users. This work aims to propose a statistically based approach for assessing the global uncertainty in hydrological forecasting, by building a statistical model for the forecast error xt,d, where t is the forecast time and d is the lead time. Accordingly, the probability distribution of xt,d is inferred through a non linear multiple regression, depending on an arbitrary number of selected conditioning variables. These include the current forecast issued by the hydrological model, the past forecast error and internal state variables of the model. The final goal is to indirectly relate the forecast error to the sources of uncertainty, through a probabilistic link with the conditioning variables. Any statistical model is based on assumptions whose fulfilment is to be checked in order to assure the validity of the underlying theory. Statistical

  1. Forecasting hotspots using predictive visual analytics approach

    SciTech Connect

    Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David

    2014-12-30

    A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

  2. Advanced Climate Analysis and Long Range Forecasting

    DTIC Science & Technology

    2014-09-30

    1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Advanced Climate Analysis and Long Range Forecasting...project is to improve the long range and climate support provided by the U.S. Naval Oceanography Enterprise (NOe) for planning, conducting, and...months, several seasons, several years). The primary transition focus is on improving the long range and climate support capabilities of the Fleet

  3. Value of Forecaster in the Loop

    DTIC Science & Technology

    2014-09-01

    forecast system IFR instrument flight rules IMC instrument meteorological conditions LAMP Localized Aviation Model Output Statistics Program METOC...but less than 3000 ft and/or visibility is greater than or equal to 3 miles but less than 5 miles. The terms Instrument Flight Rules ( IFR ) and Visual...dictated by the meteorological conditions. IMC puts IFR into effect while VMC and MVMC put VFR into effect. Outside of lightening, IMC conditions

  4. Maintaining Realistic Uncertainty in Model and Forecast

    DTIC Science & Technology

    1999-09-30

    Maintaining Realistic Uncertainty in Model and Forecast Leonard Smith Pembroke College Oxford University St Aldates Oxford OX1 3LB England phone... Oxford University ,Pembroke College,St Aldates,Oxford OX1 3LB England, 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S...in my group. REFERENCES Clarke, L. (1999) Rogue Thermocouple Detection. MSc Thesis, Mathematical Institute, Oxford University . Hansen J. and L. A

  5. Ensemble forecasting for a hydrological testbed

    NASA Astrophysics Data System (ADS)

    Jankov, Isidora; Albers, Steve; Wharton, Linda; Tollerud, Ed; Yuan, Huiling; Toth, Zoltan

    2010-05-01

    Significant precipitation events in California during the winter season are often caused by land-falling "atmospheric rivers" associated with extratropical cyclones from the Pacific Ocean. Atmospheric rivers are narrow, elongated plumes of enhanced water vapor transport over the Pacific and Atlantic oceans that can extend from the tropics and subtropics into the extratropics. Large values of integrated water vapor are advected within the warm sector of extratropical cyclones immediately ahead of polar cold fronts, although the source of these vapor plumes can originate in the tropics beyond the cyclone warm sector. When an atmospheric river makes a landfall on the coast of California, the northwest to southeast orientation of the Sierra Mountain chain exerts orographic forcing on the southwesterly low-level flow in the warm sector of approaching extratropical cyclones. As a result, sustained precipitation is typically enhanced and modified by the complex terrain. This has major hydrological consequences. The National Oceanic Atmospheric Administration (NOAA) has established the Hydrometeorological Testbed (HMT) to design and support a series of field and numerical modeling experiments to better understand and forecast precipitation in the Central Valley. The main role of the Forecast Application Branch (NOAA/ESRL/GSD) in HMT has been in supporting the real time numerical forecasts as well as research activities targeting better understanding and improvement of Quantitative Precipitation Forecasts (QPF). For this purpose ensemble modeling system has been developed. The ensemble system consists of mixed dynamic cores, mixed physics and mixed lateral boundary conditions. Performance evaluation results for this system will be presented at the conference.

  6. The Discriminant Analysis Flare Forecasting System (DAFFS)

    NASA Astrophysics Data System (ADS)

    Leka, K. D.; Barnes, Graham; Wagner, Eric; Hill, Frank; Marble, Andrew R.

    2016-05-01

    The Discriminant Analysis Flare Forecasting System (DAFFS) has been developed under NOAA/Small Business Innovative Research funds to quantitatively improve upon the NOAA/SWPC flare prediction. In the Phase-I of this project, it was demonstrated that DAFFS could indeed improve by the requested 25% most of the standard flare prediction data products from NOAA/SWPC. In the Phase-II of this project, a prototype has been developed and is presently running autonomously at NWRA.DAFFS uses near-real-time data from NOAA/GOES, SDO/HMI, and the NSO/GONG network to issue both region- and full-disk forecasts of solar flares, based on multi-variable non-parametric Discriminant Analysis. Presently, DAFFS provides forecasts which match those provided by NOAA/SWPC in terms of thresholds and validity periods (including 1-, 2-, and 3- day forecasts), although issued twice daily. Of particular note regarding DAFFS capabilities are the redundant system design, automatically-generated validation statistics and the large range of customizable options available. As part of this poster, a description of the data used, algorithm, performance and customizable options will be presented, as well as a demonstration of the DAFFS prototype.DAFFS development at NWRA is supported by NOAA/SBIR contracts WC-133R-13-CN-0079 and WC-133R-14-CN-0103, with additional support from NASA contract NNH12CG10C, plus acknowledgment to the SDO/HMI and NSO/GONG facilities and NOAA/SWPC personnel for data products, support, and feedback. DAFFS is presently ready for Phase-III development.

  7. Mesoscale Modeling, Forecasting and Remote Sensing Research.

    DTIC Science & Technology

    remote sensing , cyclonic scale diagnostic studies and mesoscale numerical modeling and forecasting are summarized. Mechanisms involved in the release of potential instability are discussed and simulated quantitatively, giving particular attention to the convective formulation. The basic mesoscale model is documented including the equations, boundary condition, finite differences and initialization through an idealized frontal zone. Results of tests including a three dimensional test with real data, tests of convective/mesoscale interaction and tests with a detailed

  8. Forecasting Attrition Volume: A Methodological Development

    DTIC Science & Technology

    2009-12-01

    de ressources humaines, comme le recrutement, la promotion, la planification et la préparation des budgets, ce rapport aura des répercussions...ressources humaines, comme le recrutement, la promotion, la planification et la préparation des budgets, ce rapport aura des répercussions positives...beginning of the next year ( fiscal or calendar). Missing from this original paper was a specific method to forecast the number of releases of individuals

  9. Forecasting USAF JP-8 Fuel Needs

    DTIC Science & Technology

    2009-03-01

    Homogeneous Charge Compression Ignition, or HCCI , which combines the best features of gasoline- and diesel-powered engines . The results could be up...FORECASTING USAF JP-8 FUEL NEEDS THESIS Presented to the Faculty Department of Logistics Management Graduate School of Engineering and Management...2008). Jet fuel is: ‘Kerosene-type; high-quality kerosene product used primarily as fuel for commercial turbojet and turboprop aircraft engines ’ (New

  10. Reservoir studies with geostatistics to forecast performance

    SciTech Connect

    Tang, R.W.; Behrens, R.A.; Emanuel, A.S. )

    1991-05-01

    In this paper example geostatistics and streamtube applications are presented for waterflood and CO{sub 2} flood in two low-permeability sandstone reservoirs. Thy hybrid approach of combining fine vertical resolution in cross-sectional models with streamtubes resulted in models that showed water channeling and provided realistic performance estimates. Results indicate that the combination of detailed geostatistical cross sections and fine-grid streamtube models offers a systematic approach for realistic performance forecasts.

  11. Wind Forecast Accuracy and PADS Performance Assessment

    DTIC Science & Technology

    2007-05-01

    Therefore a class of models was developed in ASTRAL software that simulates accurately generic navigation logic with simplified guidance and control...on the systems (1st order dynamics with 3 DoF, as opposed to the 2nd order 6 DoF dynamics model also available in ASTRAL ), and are highly...Assuming the system guidance is effective, the ASTRAL models allow simulating a mission plan with an “expected” wind forecast, then simulating an airdrop

  12. The potential uses of operational earthquake forecasting

    USGS Publications Warehouse

    Field, Ned; Jordan, Thomas; Jones, Lucille; Michael, Andrew; Blanpied, Michael L.

    2016-01-01

    This article reports on a workshop held to explore the potential uses of operational earthquake forecasting (OEF). We discuss the current status of OEF in the United States and elsewhere, the types of products that could be generated, the various potential users and uses of OEF, and the need for carefully crafted communication protocols. Although operationalization challenges remain, there was clear consensus among the stakeholders at the workshop that OEF could be useful.

  13. Forecast Variance Estimates Using Dart Inversion

    NASA Astrophysics Data System (ADS)

    Gica, E.

    2014-12-01

    The tsunami forecast tool developed by the NOAA Center for Tsunami Research (NCTR) provides real-time tsunami forecast and is composed of the following major components: a pre-computed tsunami propagation database, an inversion algorithm that utilizes real-time tsunami data recorded at DART stations to define the tsunami source, and inundation models that predict tsunami wave characteristics at specific coastal locations. The propagation database is a collection of basin-wide tsunami model runs generated from 50x100 km "unit sources" with a slip of 1 meter. Linear combination and scaling of unit sources is possible since the nonlinearity in the deep ocean is negligible. To define the tsunami source using the unit sources, real-time DART data is ingested into an inversion algorithm. Based on the selected DART and length of tsunami time series, the inversion algorithm will select the best combination of unit sources and scaling factors that best fit the observed data at the selected locations. This combined source then serves as boundary condition for the inundation models. Different combinations of DARTs and length of tsunami time series used in the inversion algorithm will result in different selection of unit sources and scaling factors. Since the combined unit sources are used as boundary condition for inundation modeling, different sources will produce variations in the tsunami wave characteristics. As part of the testing procedures for the tsunami forecast tool, staff at NCTR and both National and Pacific Tsunami Warning Centers, performed post-event forecasts for several historical tsunamis. The extent of variation due to different source definitions obtained from the testing is analyzed by comparing the simulated maximum tsunami wave amplitude with recorded data at tide gauge locations. Results of the analysis will provide an error estimate defining the possible range of the simulated maximum tsunami wave amplitude for each specific inundation model.

  14. Forecasting Zakat collection using artificial neural network

    NASA Astrophysics Data System (ADS)

    Sy Ahmad Ubaidillah, Sh. Hafizah; Sallehuddin, Roselina

    2013-04-01

    'Zakat', "that which purifies" or "alms", is the giving of a fixed portion of one's wealth to charity, generally to the poor and needy. It is one of the five pillars of Islam, and must be paid by all practicing Muslims who have the financial means (nisab). 'Nisab' is the minimum level to determine whether there is a 'zakat' to be paid on the assets. Today, in most Muslim countries, 'zakat' is collected through a decentralized and voluntary system. Under this voluntary system, 'zakat' committees are established, which are tasked with the collection and distribution of 'zakat' funds. 'Zakat' promotes a more equitable redistribution of wealth, and fosters a sense of solidarity amongst members of the 'Ummah'. The Malaysian government has established a 'zakat' center at every state to facilitate the management of 'zakat'. The center has to have a good 'zakat' management system to effectively execute its functions especially in the collection and distribution of 'zakat'. Therefore, a good forecasting model is needed. The purpose of this study is to develop a forecasting model for Pusat Zakat Pahang (PZP) to predict the total amount of collection from 'zakat' of assets more precisely. In this study, two different Artificial Neural Network (ANN) models using two different learning algorithms are developed; Back Propagation (BP) and Levenberg-Marquardt (LM). Both models are developed and compared in terms of their accuracy performance. The best model is determined based on the lowest mean square error and the highest correlations values. Based on the results obtained from the study, BP neural network is recommended as the forecasting model to forecast the collection from 'zakat' of assets for PZP.

  15. Prediction, Diagnosis, and Casual Thinking in Forecasting.

    DTIC Science & Technology

    1981-09-03

    consider the difficulties of evaluating forecast accuracy without a causal model of what generates DD 1473 O.TO.oi Nov 6s Is OBSOLETE UncDO, ,i S /k...details of the principles of deductive logic, prob- ability theory, access to computational equipment, etc. However, your level of substantive knowledge...interest is large (i.e., is of substantial duration and/or strength), we expect that the suspected cause( s ) are judged to be of compar- able size

  16. 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.

  17. Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting: Preprint

    SciTech Connect

    Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat

    2015-08-05

    Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output. forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.

  18. Towards reliable seasonal ensemble streamflow forecasts for ephemeral rivers

    NASA Astrophysics Data System (ADS)

    Bennett, James; Wang, Qj; Li, Ming; Robertson, David

    2016-04-01

    Despite their inherently variable nature, ephemeral rivers are an important water resource in many dry regions. Water managers are likely benefit considerably from even mildly skilful ensemble forecasts of streamflow in ephemeral rivers. As with any ensemble forecast, forecast uncertainty - i.e., the spread of the ensemble - must be reliably quantified to allow users of the forecasts to make well-founded decisions. Correctly quantifying uncertainty in ephemeral rivers is particularly challenging because of the high incidence of zero flows, which are difficult to handle with conventional statistical techniques. Here we apply a seasonal streamflow forecasting system, the model for generating Forecast Guided Stochastic Scenarios (FoGSS), to 26 Australian ephemeral rivers. FoGSS uses post-processed ensemble rainfall forecasts from a coupled ocean-atmosphere prediction system to force an initialised monthly rainfall runoff model, and then applies a staged hydrological error model to describe and propagate hydrological uncertainty in the forecast. FoGSS produces 12-month streamflow forecasts; as forecast skill declines with lead time, the forecasts are designed to transit seamlessly to stochastic scenarios. The ensemble rainfall forecasts used in FoGSS are known to be unbiased and reliable, and we concentrate here on the hydrological error model. The FoGSS error model has several features that make it well suited to forecasting ephemeral rivers. First, FoGSS models the error after data is transformed with a log-sinh transformation. The log-sinh transformation is able to normalise even highly skewed data and homogenise its variance, allowing us to assume that errors are Gaussian. Second, FoGSS handles zero values using data censoring. Data censoring allows streamflow in ephemeral rivers to be treated as a continuous variable, rather than having to model the occurrence of non-zero values and the distribution of non-zero values separately. This greatly simplifies parameter

  19. The forecasting Ocean assimilation model (FOAM) system

    NASA Astrophysics Data System (ADS)

    Bell, M. J.; Acreman, D.; Barciela, R.; Hines, A.; Martin, M. J.; Sellar, A.; Stark, J.; Storkey, D.

    The FOAM system is built around the ocean and sea-ice components of the Met Office's Unified Model (UM), developed by the Hadley Centre for coupled ocean-ice-atmosphere climate prediction. It is forced by 6-hourly surface fluxes from the Met Office's Numerical Weather Prediction (NWP) system, and assimilates temperature and salinity profiles from in situ instruments, surface temperature, sea-ice concentration and sea surface height data. A coarse resolution global configuration of FOAM on a 1 ° latitude-longitude grid with 20 vertical levels was implemented in the Met Office's operational suite in 1997. Nested models with grid spacings ranging from 30 km to 6 km are used to provide detailed forecasts for selected regions. The models are run each morning and typically produce 5-day forecasts. Real-time daily and archived analyses for the North Atlantic are freely available at http://nerc-essc.reading.ac.uk/las for research and developmentpurposes. We will present results from studies of the accuracy of the forecasts and how it depends on the data types assimilated and the assimilation scheme used. We will also briefly describe the developments being made to assimilate sea-ice concentration and velocity data and incorporate the HadOCC NPZD (nutrient-phytoplankton-zooplankton-detritus) model and assimilation of ocean colour data.

  20. Global disease monitoring and forecasting with Wikipedia.

    PubMed

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y; Priedhorsky, Reid

    2014-11-01

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: access logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with r2 up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.

  1. [Forecasting medical technologies--a global overview].

    PubMed

    Tal, Orna

    2011-02-01

    Forecasting new medical technologies is a crucial stage in the process of decision-making in health care systems on national, organizational, professional and personal levels. Knowing what is on the horizon is essential. It is a tool facilitating preparedness and planning for updating health care in the western world. The challenge is to identify new promising technologies at an early stage. This is due to the uncertainty in estimating developing trends and consequences (clinical, financial, political, legal, social and ethical). A balance must be found between the desire to adopt new emerging technologies and the necessity for accountability n basing decisions on efficient evidence. Scarce resources, pervading health systems everywhere, emphasize the need for this mechanism to justify and improve health system determinations. Planning for the future has expanded into new medical fields, thereby reinforcing the importance of national forecasting bodies. This article presents the basic terminology and principles of medical technology forecasting and reviews the agencies involved in early warning systems including Israel.

  2. Forecasting distribution of numbers of large fires

    USGS Publications Warehouse

    Eidenshink, Jeffery C.; Preisler, Haiganoush K.; Howard, Stephen; Burgan, Robert E.

    2014-01-01

    Systems to estimate forest fire potential commonly utilize one or more indexes that relate to expected fire behavior; however they indicate neither the chance that a large fire will occur, nor the expected number of large fires. That is, they do not quantify the probabilistic nature of fire danger. In this work we use large fire occurrence information from the Monitoring Trends in Burn Severity project, and satellite and surface observations of fuel conditions in the form of the Fire Potential Index, to estimate two aspects of fire danger: 1) the probability that a 1 acre ignition will result in a 100+ acre fire, and 2) the probabilities of having at least 1, 2, 3, or 4 large fires within a Predictive Services Area in the forthcoming week. These statistical processes are the main thrust of the paper and are used to produce two daily national forecasts that are available from the U.S. Geological Survey, Earth Resources Observation and Science Center and via the Wildland Fire Assessment System. A validation study of our forecasts for the 2013 fire season demonstrated good agreement between observed and forecasted values.

  3. A survey on wind power ramp forecasting.

    SciTech Connect

    Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J.

    2011-02-23

    The increasing use of wind power as a source of electricity poses new challenges with regard to both power production and load balance in the electricity grid. This new source of energy is volatile and highly variable. The only way to integrate such power into the grid is to develop reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly variable at several different timescales: sub-hourly, hourly, daily, and seasonally. Wind energy, like other electricity sources, must be scheduled. Although wind power forecasting methods are used, the ability to predict wind plant output remains relatively low for short-term operation. Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, wind power's variability can present substantial challenges when large amounts of wind power are incorporated into a grid system. A critical issue is ramp events, which are sudden and large changes (increases or decreases) in wind power. This report presents an overview of current ramp definitions and state-of-the-art approaches in ramp event forecasting.

  4. Multipurpose simulation systems for regional development forecasting

    SciTech Connect

    Kostina, N.I.

    1995-09-01

    We examine the development of automaton-modeling multipurpose simulation systems as an efficient form of simulation software for MIS. Such systems constitute a single problem-oriented package of applications based on a general simulation model, which is equipped with a task source language, interaction tools, file management tools, and an output document editor. The simulation models are described by the method of probabilistic-automaton modeling, which ensures standard representation of models and standardization of the modeling algorithm. Examples of such systems include the demographic forecasting system DEPROG, the VOKON system for assessing the quality of consumer services in terms of free time, and the SONET system for servicing partially accessible customers. The development of computer-aided systems for production and economic control is now moving to the second state, namely operationalization of optimization and forecasting problems, whose solution may account for the main economic effect of MIS. Computation and information problems, which were the main focus of the first stage of MIS development, are thus acquiring the role of a source of information for optimization and forecasting problems in addition to their direct contribution to preparation and analysis of current production and economic information.

  5. VIIRS in AWIPS: Supporting Operational Forecasters

    NASA Astrophysics Data System (ADS)

    Strabala, K.; Gumley, L.; Huang, H.; Heinrichs, T. A.; Hungershöfer, K.

    2012-12-01

    The Joint Polar Satellite System (JPSS) project has funded the inclusion of Soumi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data in the Advanced Weather Interactive Processing System (AWIPS) in support of operational National Weather Service (NWS) Forecasters. The focus of this effort is to provide VIIRS data to high latitude regions (Alaska), where there are more frequent polar overpasses, and where the geostationary data large view angles make it less effective in monitoring small scale events. Because the Suomi NPP data is available via direct broadcast (DB), it can be acquired by X/L band antennas and processed in near-real time using the free Community Satellite Processing Package (CSPP), which transforms VIIRS raw data into SDRs identical to the IDPS VIIRS SDRs. Working closely with the University of Alaska - Fairbanks Geographic Information Network of Alaska (GINA) team, the CSPP software is running operationally with products remapped and fed to the forecast offices for display in AWIPS. Along with the installation, forecaster training was provided to help operations personnel understand the kinds of events where the high resolution data will be most useful. The high quality of the VIIRS data, the improved spatial resolution and coverage as well as the new day/night band, point to operational use of the data over all AWIPS domains. Examples are provided from different domains using direct broadcast data over Alaska, CONUS (collected and processed at SSEC), as well as Hawaii (antenna installation summer 2012).;

  6. Foreign currency rate forecasting using neural networks

    NASA Astrophysics Data System (ADS)

    Pandya, Abhijit S.; Kondo, Tadashi; Talati, Amit; Jayadevappa, Suryaprasad

    2000-03-01

    Neural networks are increasingly being used as a forecasting tool in many forecasting problems. This paper discusses the application of neural networks in predicting daily foreign exchange rates between the USD, GBP as well as DEM. We approach the problem from a time-series analysis framework - where future exchange rates are forecasted solely using past exchange rates. This relies on the belief that the past prices and future prices are very close related, and interdependent. We present the result of training a neural network with historical USD-GBP data. The methodology used in explained, as well as the training process. We discuss the selection of inputs to the network, and present a comparison of using the actual exchange rates and the exchange rate differences as inputs. Price and rate differences are the preferred way of training neural network in financial applications. Results of both approaches are present together for comparison. We show that the network is able to learn the trends in the exchange rate movements correctly, and present the results of the prediction over several periods of time.

  7. Seasonal forecasting of fire over Kalimantan, Indonesia

    NASA Astrophysics Data System (ADS)

    Spessa, A. C.; Field, R. D.; Pappenberger, F.; Langner, A.; Englhart, S.; Weber, U.; Stockdale, T.; Siegert, F.; Kaiser, J. W.; Moore, J.

    2015-03-01

    Large-scale fires occur frequently across Indonesia, particularly in the southern region of Kalimantan and eastern Sumatra. They have considerable impacts on carbon emissions, haze production, biodiversity, health, and economic activities. In this study, we demonstrate that severe fire and haze events in Indonesia can generally be predicted months in advance using predictions of seasonal rainfall from the ECMWF System 4 coupled ocean-atmosphere model. Based on analyses of long, up-to-date series observations on burnt area, rainfall, and tree cover, we demonstrate that fire activity is negatively correlated with rainfall and is positively associated with deforestation in Indonesia. There is a contrast between the southern region of Kalimantan (high fire activity, high tree cover loss, and strong non-linear correlation between observed rainfall and fire) and the central region of Kalimantan (low fire activity, low tree cover loss, and weak, non-linear correlation between observed rainfall and fire). The ECMWF seasonal forecast provides skilled forecasts of burnt and fire-affected area with several months lead time explaining at least 70% of the variance between rainfall and burnt and fire-affected area. Results are strongly influenced by El Niño years which show a consistent positive bias. Overall, our findings point to a high potential for using a more physical-based method for predicting fires with several months lead time in the tropics rather than one based on indexes only. We argue that seasonal precipitation forecasts should be central to Indonesia's evolving fire management policy.

  8. Solar Data Assimilation Engine for Ionospheric Forecasts

    NASA Astrophysics Data System (ADS)

    Fry, C. D.; Eccles, J. V.

    2007-12-01

    The Space Weather Modeling System (SWMS) is a Battlespace Environments Institute (BEI) project that couples space environment models together under the Earth System Modeling Framework, while ensuring that the component models are scalable and portable. BEI is sponsored by the High Performance Computing Modernization Office and managed by Air Force Weather Agency and Naval Research Laboratory. The Hakamada-Akasofu-Fry version 2 (HAFv2) solar wind model and the Global Assimilation of Ionospheric Measurements (GAIM) model are the first two coupled components in the SWMS. Serving as a data assimilation engine, the HAFv2 model uses solar observations to prepare its initial solar wind conditions. Then, the HAFv2 internal algorithms and the initial conditions determine the present and future states of the solar wind conditions at Earth. The outputs of HAFv2 are provided to GAIM to forecast the time-dependent energy input into the high- latitude ionosphere. This presentation describes how the HAFv2 model is being used as a solar data assimilation engine for producing forecasts of solar wind parameters, that then serve as inputs to drive GAIM and other near-Earth space environment models. The overarching goal is to extend the lead time and skill of forecasts of space weather conditions and their corresponding impacts on operational customers.

  9. Global Disease Monitoring and Forecasting with Wikipedia

    PubMed Central

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid

    2014-01-01

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: access logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art. PMID:25392913

  10. Forecasting the Time Series of Sunspot Numbers

    NASA Astrophysics Data System (ADS)

    Aguirre, L. A.; Letellier, C.; Maquet, J.

    2008-05-01

    Forecasting the solar cycle is of great importance for weather prediction and environmental monitoring, and also constitutes a difficult scientific benchmark in nonlinear dynamical modeling. This paper describes the identification of a model and its use in the forecasting the time series comprised of Wolf’s sunspot numbers. A key feature of this procedure is that the original time series is first transformed into a symmetrical space where the dynamics of the solar dynamo are unfolded in a better way, thus improving the model. The nonlinear model obtained is parsimonious and has both deterministic and stochastic parts. Monte Carlo simulation of the whole model produces very consistent results with the deterministic part of the model but allows for the determination of confidence bands. The obtained model was used to predict cycles 24 and 25, although the forecast of the latter is seen as a crude approximation, given the long prediction horizon required. As for the 24th cycle, two estimates were obtained with peaks of 65±16 and of 87±13 units of sunspot numbers. The simulated results suggest that the 24th cycle will be shorter and less active than the preceding one.

  11. Spatial forecasting of disease risk and uncertainty

    USGS Publications Warehouse

    De Cola, L.

    2002-01-01

    Because maps typically represent the value of a single variable over 2-dimensional space, cartographers must simplify the display of multiscale complexity, temporal dynamics, and underlying uncertainty. A choropleth disease risk map based on data for polygonal regions might depict incidence (cases per 100,000 people) within each polygon for a year but ignore the uncertainty that results from finer-scale variation, generalization, misreporting, small numbers, and future unknowns. In response to such limitations, this paper reports on the bivariate mapping of data "quantity" and "quality" of Lyme disease forecasts for states of the United States. Historical state data for 1990-2000 are used in an autoregressive model to forecast 2001-2010 disease incidence and a probability index of confidence, each of which is then kriged to provide two spatial grids representing continuous values over the nation. A single bivariate map is produced from the combination of the incidence grid (using a blue-to-red hue spectrum), and a probabilistic confidence grid (used to control the saturation of the hue at each grid cell). The resultant maps are easily interpretable, and the approach may be applied to such problems as detecting unusual disease occurences, visualizing past and future incidence, and assembling a consistent regional disease atlas showing patterns of forecasted risks in light of probabilistic confidence.

  12. Forecasting Social Unrest Using Activity Cascades

    PubMed Central

    Cadena, Jose; Korkmaz, Gizem; Kuhlman, Chris J.; Marathe, Achla; Ramakrishnan, Naren; Vullikanti, Anil

    2015-01-01

    Social unrest is endemic in many societies, and recent news has drawn attention to happenings in Latin America, the Middle East, and Eastern Europe. Civilian populations mobilize, sometimes spontaneously and sometimes in an organized manner, to raise awareness of key issues or to demand changes in governing or other organizational structures. It is of key interest to social scientists and policy makers to forecast civil unrest using indicators observed on media such as Twitter, news, and blogs. We present an event forecasting model using a notion of activity cascades in Twitter (proposed by Gonzalez-Bailon et al., 2011) to predict the occurrence of protests in three countries of Latin America: Brazil, Mexico, and Venezuela. The basic assumption is that the emergence of a suitably detected activity cascade is a precursor or a surrogate to a real protest event that will happen “on the ground.” Our model supports the theoretical characterization of large cascades using spectral properties and uses properties of detected cascades to forecast events. Experimental results on many datasets, including the recent June 2013 protests in Brazil, demonstrate the effectiveness of our approach. PMID:26091012

  13. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: access logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.

  14. Global disease monitoring and forecasting with Wikipedia

    DOE PAGES

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; ...

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: accessmore » logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.« less

  15. Regional crop yield forecasting: a probabilistic approach

    NASA Astrophysics Data System (ADS)

    de Wit, A.; van Diepen, K.; Boogaard, H.

    2009-04-01

    Information on the outlook on yield and production of crops over large regions is essential for government services dealing with import and export of food crops, for agencies with a role in food relief, for international organizations with a mandate in monitoring the world food production and trade, and for commodity traders. Process-based mechanistic crop models are an important tool for providing such information, because they can integrate the effect of crop management, weather and soil on crop growth. When properly integrated in a yield forecasting system, the aggregated model output can be used to predict crop yield and production at regional, national and continental scales. Nevertheless, given the scales at which these models operate, the results are subject to large uncertainties due to poorly known weather conditions and crop management. Current yield forecasting systems are generally deterministic in nature and provide no information about the uncertainty bounds on their output. To improve on this situation we present an ensemble-based approach where uncertainty bounds can be derived from the dispersion of results in the ensemble. The probabilistic information provided by this ensemble-based system can be used to quantify uncertainties (risk) on regional crop yield forecasts and can therefore be an important support to quantitative risk analysis in a decision making process.

  16. Action-based flood forecasting for triggering humanitarian action

    NASA Astrophysics Data System (ADS)

    Coughlan de Perez, Erin; van den Hurk, Bart; van Aalst, Maarten K.; Amuron, Irene; Bamanya, Deus; Hauser, Tristan; Jongma, Brenden; Lopez, Ana; Mason, Simon; Mendler de Suarez, Janot; Pappenberger, Florian; Rueth, Alexandra; Stephens, Elisabeth; Suarez, Pablo; Wagemaker, Jurjen; Zsoter, Ervin

    2016-09-01

    Too often, credible scientific early warning information of increased disaster risk does not result in humanitarian action. With financial resources tilted heavily towards response after a disaster, disaster managers have limited incentive and ability to process complex scientific data, including uncertainties. These incentives are beginning to change, with the advent of several new forecast-based financing systems that provide funding based on a forecast of an extreme event. Given the changing landscape, here we demonstrate a method to select and use appropriate forecasts for specific humanitarian disaster prevention actions, even in a data-scarce location. This action-based forecasting methodology takes into account the parameters of each action, such as action lifetime, when verifying a forecast. Forecasts are linked with action based on an understanding of (1) the magnitude of previous flooding events and (2) the willingness to act "in vain" for specific actions. This is applied in the context of the Uganda Red Cross Society forecast-based financing pilot project, with forecasts from the Global Flood Awareness System (GloFAS). Using this method, we define the "danger level" of flooding, and we select the probabilistic forecast triggers that are appropriate for specific actions. Results from this methodology can be applied globally across hazards and fed into a financing system that ensures that automatic, pre-funded early action will be triggered by forecasts.

  17. Verification of National Weather Service spot forecasts using surface observations

    NASA Astrophysics Data System (ADS)

    Lammers, Matthew Robert

    Software has been developed to evaluate National Weather Service spot forecasts issued to support prescribed burns and early-stage wildfires. Fire management officials request spot forecasts from National Weather Service Weather Forecast Offices to provide detailed guidance as to atmospheric conditions in the vicinity of planned prescribed burns as well as wildfires that do not have incident meteorologists on site. This open source software with online display capabilities is used to examine an extensive set of spot forecasts of maximum temperature, minimum relative humidity, and maximum wind speed from April 2009 through November 2013 nationwide. The forecast values are compared to the closest available surface observations at stations installed primarily for fire weather and aviation applications. The accuracy of the spot forecasts is compared to those available from the National Digital Forecast Database (NDFD). Spot forecasts for selected prescribed burns and wildfires are used to illustrate issues associated with the verification procedures. Cumulative statistics for National Weather Service County Warning Areas and for the nation are presented. Basic error and accuracy metrics for all available spot forecasts and the entire nation indicate that the skill of the spot forecasts is higher than that available from the NDFD, with the greatest improvement for maximum temperature and the least improvement for maximum wind speed.

  18. How much are you prepared to PAY for a forecast?

    NASA Astrophysics Data System (ADS)

    Arnal, Louise; Coughlan, Erin; Ramos, Maria-Helena; Pappenberger, Florian; Wetterhall, Fredrik; Bachofen, Carina; van Andel, Schalk Jan

    2015-04-01

    Probabilistic hydro-meteorological forecasts are a crucial element of the decision-making chain in the field of flood prevention. The operational use of probabilistic forecasts is increasingly promoted through the development of new novel state-of-the-art forecast methods and numerical skill is continuously increasing. However, the value of such forecasts for flood early-warning systems is a topic of diverging opinions. Indeed, the word value, when applied to flood forecasting, is multifaceted. It refers, not only to the raw cost of acquiring and maintaining a probabilistic forecasting system (in terms of human and financial resources, data volume and computational time), but also and most importantly perhaps, to the use of such products. This game aims at investigating this point. It is a willingness to pay game, embedded in a risk-based decision-making experiment. Based on a ``Red Cross/Red Crescent, Climate Centre'' game, it is a contribution to the international Hydrologic Ensemble Prediction Experiment (HEPEX). A limited number of probabilistic forecasts will be auctioned to the participants; the price of these forecasts being market driven. All participants (irrespective of having bought or not a forecast set) will then be taken through a decision-making process to issue warnings for extreme rainfall. This game will promote discussions around the topic of the value of forecasts for decision-making in the field of flood prevention.

  19. The GOCF/AWAP system - forecasting temperature extremes

    NASA Astrophysics Data System (ADS)

    Fawcett, Robert; Hume, Timothy

    2010-08-01

    Gridded hourly temperature forecasts from the Bureau of Meteorology's Gridded Operational Consensus Forecasting (GOCF) system are combined in real time with the Australian Water Availability Project (AWAP) gridded daily temperature analyses to produce gridded daily maximum and minimum temperature forecasts with lead times from one to five days. These forecasts are compared against the historical record of AWAP daily temperature analyses (1911 to present), to identify regions where record or near-record temperatures are predicted to occur. This paper describes the GOCF/AWAP system, showing how the daily maximum and minimum temperature forecasts are prepared from the hourly forecasts, and how they are bias-corrected in real time using the AWAP analyses, against which they are subsequently verified. Using monthly climatologies of long-term daily mean, standard deviation and all-time highest and lowest on record, derived forecast products (for both maximum and minimum temperature) include ordinary and standardised anomalies, "forecast - highest on record" and "forecast - lowest on record". Compensation for the climatological variation across the country is achieved in these last two products, which provide the necessary guidance as to whether or not record-breaking temperatures are expected, by expressing the forecast departure from the previous record in both °C and standard deviations.

  20. Application of fuzzy logic to forecast seasonal runoff

    NASA Astrophysics Data System (ADS)

    Mahabir, C.; Hicks, F. E.; Robinson Fayek, A.

    2003-12-01

    Each spring in Alberta, Canada, the potential snowmelt runoff is forecast for several basins to assess the water supply situation. Water managers need this forecast to plan water allocations for the following summer season. The Lodge Creek and Middle Creek basins, located in southeastern Alberta, are two basins that require this type of late winter forecast of potential spring runoff. Historically, the forecast has been based upon a combination of regression equations. These results are then interpreted by a forecaster and are modified based on the forecaster's heuristic knowledge of the basin. Unfortunately, this approach has had limited success in the past, in terms of the accuracy of these forecasts, and consequently an alternative methodology is needed.In this study, the applicability of fuzzy logic modelling techniques for forecasting water supply was investigated. Fuzzy logic has been applied successfully in several fields where the relationship between cause and effect (variable and results) are vague. Fuzzy variables were used to organize knowledge that is expressed linguistically into a formal analysis. For example, high snowpack, average snowpack and low snowpack became variables. By applying fuzzy logic, a water supply forecast was created that classified potential runoff into three forecast zones: low, average and high. Spring runoff forecasts from the fuzzy expert systems were found to be considerably more reliable than the regression models in forecasting the appropriate runoff zone, especially in terms of identifying low or average runoff years. Based on the modelling results in these two basins, it is concluded that fuzzy logic has a promising potential for providing reliable water supply forecasts. Copyright

  1. The Value of Humans in the Operational River Forecasting Enterprise

    NASA Astrophysics Data System (ADS)

    Pagano, T. C.

    2012-04-01

    The extent of human control over operational river forecasts, such as by adjusting model inputs and outputs, varies from nearly completely automated systems to those where forecasts are generated after discussion among a group of experts. Historical and realtime data availability, the complexity of hydrologic processes, forecast user needs, and forecasting institution support/resource availability (e.g. computing power, money for model maintenance) influence the character and effectiveness of operational forecasting systems. Automated data quality algorithms, if used at all, are typically very basic (e.g. checks for impossible values); substantial human effort is devoted to cleaning up forcing data using subjective methods. Similarly, although it is an active research topic, nearly all operational forecasting systems struggle to make quantitative use of Numerical Weather Prediction model-based precipitation forecasts, instead relying on the assessment of meteorologists. Conversely, while there is a strong tradition in meteorology of making raw model outputs available to forecast users via the Internet, this is rarely done in hydrology; Operational river forecasters express concerns about exposing users to raw guidance, due to the potential for misinterpretation and misuse. However, this limits the ability of users to build their confidence in operational products through their own value-added analyses. Forecasting agencies also struggle with provenance (i.e. documenting the production process and archiving the pieces that went into creating a forecast) although this is necessary for quantifying the benefits of human involvement in forecasting and diagnosing weak links in the forecasting chain. In hydrology, the space between model outputs and final operational products is nearly unstudied by the academic community, although some studies exist in other fields such as meteorology.

  2. Validation of Seasonal Forecast of Indian Summer Monsoon Rainfall

    NASA Astrophysics Data System (ADS)

    Das, Sukanta Kumar; Deb, Sanjib Kumar; Kishtawal, C. M.; Pal, Pradip Kumar

    2015-06-01

    The experimental seasonal forecast of Indian summer monsoon (ISM) rainfall during June through September using Community Atmosphere Model (CAM) version 3 has been carried out at the Space Applications Centre Ahmedabad since 2009. The forecasts, based on a number of ensemble members (ten minimum) of CAM, are generated in several phases and updated on regular basis. On completion of 5 years of experimental seasonal forecasts in operational mode, it is required that the overall validation or correctness of the forecast system is quantified and that the scope is assessed for further improvements of the forecast over time, if any. The ensemble model climatology generated by a set of 20 identical CAM simulations is considered as the model control simulation. The performance of the forecast has been evaluated by assuming the control simulation as the model reference. The forecast improvement factor shows positive improvements, with higher values for the recent forecasted years as compared to the control experiment over the Indian landmass. The Taylor diagram representation of the Pearson correlation coefficient (PCC), standard deviation and centered root mean square difference has been used to demonstrate the best PCC, in the order of 0.74-0.79, recorded for the seasonal forecast made during 2013. Further, the bias score of different phases of experiment revealed the fact that the ISM rainfall forecast is affected by overestimation in predicting the low rain-rate (less than 7 mm/day), but by underestimation in the medium and high rain-rate (higher than 11 mm/day). Overall, the analysis shows significant improvement of the ISM forecast over the last 5 years, viz. 2009-2013, due to several important modifications that have been implemented in the forecast system. The validation exercise has also pointed out a number of shortcomings in the forecast system; these will be addressed in the upcoming years of experiments to improve the quality of the ISM prediction.

  3. Improving Groundwater Predictions using Seasonal Precipitation Forecasts

    NASA Astrophysics Data System (ADS)

    Almanaseer, N.; Arumugam, S.; Bales, J. D.

    2011-12-01

    This research aims to evaluate the utility of precipitation forecasts in improving groundwater and streamflow predictions at seasonal and monthly time scales using statistical modeling techniques. For this purpose, we select ten groundwater wells from the Groundwater Climate Response Network (GCRN) and nine streamgauges from the Hydro-Climatic Data Network (HCDN) to represent groundwater and surface water variability with minimal anthropogenic influences over Flint River Basin (FRB) in Georgia, U.S. Preliminary analysis shows significant correlation between precipitation forecasts over FRB with observed precipitation (P), streamflow discharges (Q) and depth to groundwater (G). Three statistical models are developed using principle component regression (PCR) and canonical correlation analysis (CCA) with leave-5-out cross-validation to predict winter (JFM) and spring (AMJ) as well as monthly (Jan through Jun) groundwater and streamflow for the selected sites. The three models starts at the end of Dec and uses Oct, Nov and Dec (OND) observed records to predict 2-seasons and 6-months ahead. Model-1 is the "null model" that does not include precipitation forecasts as predictors. It is developed using PCR to predict seasonal and monthly Q and G independently based on previous (Oct. Nov. and Dec; OND) observations of Q or G at a given site without using climate information. Model predictands are JFM, AMJ for seasonal and Jan. through Jun for monthly. Model-2 is also developed using PCR, but it uses the issued at January precipitation forecasts from nine ECHAM 4.5 grid points as additional predictors. Model-3 is developed using CCA and it aims to integrate additional information on the predictands (i.e., groundwater) from adjacent basins to improve the prediction. Model-3 is designed to evaluate the role of climate versus the role groundwater and surface water flows in the selected basins. Finally, comparisons between the three models for each site and across the sites

  4. Novel methodology for pharmaceutical expenditure forecast

    PubMed Central

    Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    Background and objective The value appreciation of new drugs across countries today features a disruption that is making the historical data that are used for forecasting pharmaceutical expenditure poorly reliable. Forecasting methods rarely addressed uncertainty. The objective of this project was to propose a methodology to perform pharmaceutical expenditure forecasting that integrates expected policy changes and uncertainty (developed for the European Commission as the ‘EU Pharmaceutical expenditure forecast’; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). Methods 1) Identification of all pharmaceuticals going off-patent and new branded medicinal products over a 5-year forecasting period in seven European Union (EU) Member States. 2) Development of a model to estimate direct and indirect impacts (based on health policies and clinical experts) on savings of generics and biosimilars. Inputs were originator sales value, patent expiry date, time to launch after marketing authorization, price discount, penetration rate, time to peak sales, and impact on brand price. 3) Development of a model for new drugs, which estimated sales progression in a competitive environment. Clinical expected benefits as well as commercial potential were assessed for each product by clinical experts. Inputs were development phase, marketing authorization dates, orphan condition, market size, and competitors. 4) Separate analysis of the budget impact of products going off-patent and new drugs according to several perspectives, distribution chains, and outcomes. 5) Addressing uncertainty surrounding estimations via deterministic and probabilistic sensitivity analysis. Results This methodology has proven to be effective by 1) identifying the main parameters impacting the variations in pharmaceutical expenditure forecasting across countries: generics discounts and penetration, brand price after patent loss, reimbursement rate, the penetration of biosimilars and

  5. Probabilistic Flash Flood Forecasting using Stormscale Ensembles

    NASA Astrophysics Data System (ADS)

    Hardy, J.; Gourley, J. J.; Kain, J. S.; Clark, A.; Novak, D.; Hong, Y.

    2013-12-01

    Flash flooding is one of the most costly and deadly natural hazards in the US and across the globe. The loss of life and property from flash floods could be mitigated with better guidance from hydrological models, but these models have limitations. For example, they are commonly initialized using rainfall estimates derived from weather radars, but the time interval between observations of heavy rainfall and a flash flood can be on the order of minutes, particularly for small basins in urban settings. Increasing the lead time for these events is critical for protecting life and property. Therefore, this study advances the use of quantitative precipitation forecasts (QPFs) from a stormscale NWP ensemble system into a distributed hydrological model setting to yield basin-specific, probabilistic flash flood forecasts (PFFFs). Rainfall error characteristics of the individual members are first diagnosed and quantified in terms of structure, amplitude, and location (SAL; Wernli et al., 2008). Amplitude and structure errors are readily correctable due to their diurnal nature, and the fine scales represented by the CAPS QPF members are consistent with radar-observed rainfall, mainly showing larger errors with afternoon convection. To account for the spatial uncertainty of the QPFs, we use an elliptic smoother, as in Marsh et al. (2012), to produce probabilistic QPFs (PQPFs). The elliptic smoother takes into consideration underdispersion, which is notoriously associated with stormscale ensembles, and thus, is good for targeting the approximate regions that may receive heavy rainfall. However, stormscale details contained in individual members are still needed to yield reasonable flash flood simulations. Therefore, on a case study basis, QPFs from individual members are then run through the hydrological model with their predicted structure and corrected amplitudes, but the locations of individual rainfall elements are perturbed within the PQPF elliptical regions using Monte

  6. 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

  7. Verification of short lead time forecast models: applied to Kp and Dst forecasting

    NASA Astrophysics Data System (ADS)

    Wintoft, Peter; Wik, Magnus

    2016-04-01

    In the ongoing EU/H2020 project PROGRESS models that predicts Kp, Dst, and AE from L1 solar wind data will be used as inputs to radiation belt models. The possible lead times from L1 measurements are shorter (10s of minutes to hours) than the typical duration of the physical phenomena that should be forecast. Under these circumstances several metrics fail to single out trivial cases, such as persistence. In this work we explore metrics and approaches for short lead time forecasts. We apply these to current Kp and Dst forecast models. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 637302.

  8. Rebuttal of "Polar bear population forecasts: a public-policy forecasting audit"

    USGS Publications Warehouse

    Amstrup, Steven C.; Caswell, Hal; DeWeaver, Eric; Stirling, Ian; Douglas, David C.; Marcot, Bruce G.; Hunter, Christine M.

    2009-01-01

    Observed declines in the Arctic sea ice have resulted in a variety of negative effects on polar bears (Ursus maritimus). Projections for additional future declines in sea ice resulted in a proposal to list polar bears as a threatened species under the United States Endangered Species Act. To provide information for the Department of the Interior's listing-decision process, the US Geological Survey (USGS) produced a series of nine research reports evaluating the present and future status of polar bears throughout their range. In response, Armstrong et al. [Armstrong, J. S., K. C. Green, W. Soon. 2008. Polar bear population forecasts: A public-policy forecasting audit. Interfaces 38(5) 382–405], which we will refer to as AGS, performed an audit of two of these nine reports. AGS claimed that the general circulation models upon which the USGS reports relied were not valid forecasting tools, that USGS researchers were not objective or lacked independence from policy decisions, that they did not utilize all available information in constructing their forecasts, and that they violated numerous principles of forecasting espoused by AGS. AGS (p. 382) concluded that the two USGS reports were "unscientific and inconsequential to decision makers." We evaluate the AGS audit and show how AGS are mistaken or misleading on every claim. We provide evidence that general circulation models are useful in forecasting future climate conditions and that corporate and government leaders are relying on these models to do so. We clarify the strict independence of the USGS from the listing decision. We show that the allegations of failure to follow the principles of forecasting espoused by AGS are either incorrect or are based on misconceptions about the Arctic environment, polar bear biology, or statistical and mathematical methods. We conclude by showing that the AGS principles of forecasting are too ambiguous and subjective to be used as a reliable basis for auditing scientific

  9. An Ensemble Approach for Forecasting Net Interchange Schedule

    SciTech Connect

    Vlachopoulou, Maria; Gosink, Luke J.; Pulsipher, Trenton C.; Ferryman, Thomas A.; Zhou, Ning; Tong, Jianzhong

    2013-09-01

    The net interchange schedule (NIS) is the sum of the transactions (MW) between an ISO/RTO and its neighbors. Effective forecasting of the submitted NIS can improve grid operation efficiency. This paper applies a Bayesian model averaging (BMA) technique to forecast submitted NIS. As an ensemble approach, the BMA method aggregates different forecasting models in order to improve forecasting accuracy and consistency. In this study, the BMA method is compared to two alternative approaches: a stepwise regression method and an artificial neural network (ANN) trained for NIS forecasting. In our comparative analysis, we use field measurement data from the Pennsylvania, New Jersey, and Maryland (PJM) Regional Transmission Organization (RTO) to train and test each method. Our preliminary results indicate that ensemble-based methods can provide more accurate and consistent NIS forecasts in comparison to non-ensemble alternate methods.

  10. Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

    SciTech Connect

    Zhang, J.; Hodge, B. M.; Florita, A.; Lu, S.; Hamann, H. F.; Banunarayanan, V.

    2013-10-01

    Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The results show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.

  11. An Operational Environmental Meteorology Forecasting system for Eastern China

    NASA Astrophysics Data System (ADS)

    Zhou, Guangqiang; Xu, Jianming; Xie, Ying; Wu, Jianbin; Yu, Zhongqi; Chang, Luyu

    2015-04-01

    Since 2012 an operational environmental meteorology forecasting system was setup to provide daily forecasts of environmental meteorology pollutants for the Eastern China region. Initialized with 0.5 degree GFS meteorological fields, the system uses the WRF-Chem model to provide daily 96-hour forecasts. Model forecasts for meteorological fields and pollutants concentrations (e.g. PM2.5 and O3) as well as haze conditions are displayed through an open platform. Verifications of the model results in terms of statistical and graphical products are also displayed at the website. Currently, the modeling system provides strong support for the daily AQI forecasting of Shanghai, and it also provides guidance products for other meteorological agencies in the Eastern China region. Here the modeling system design will be presented, together with long-term verification results for PM2.5 and O3forecasts.

  12. Wind speed forecasting in the central California wind resource area

    SciTech Connect

    McCarthy, E.F.

    1997-12-31

    A wind speed forecasting program was implemented in the summer seasons of 1985 - 87 in the Central California Wind Resource Area (WRA). The forecasting program is designed to use either meteorological observations from the WRA and local upper air observations or upper air observations alone to predict the daily average windspeed at two locations. Forecasts are made each morning at 6 AM and are valid for a 24 hour period. Ease of use is a hallmark of the program as the daily forecast can be made using data entered into a programmable HP calculator. The forecasting program was the first step in a process to examine whether the electrical energy output of an entire wind power generation facility or defined subsections of the same facility could be predicted up to 24 hours in advance. Analysis of the results of the summer season program using standard forecast verification techniques show the program has skill over persistence and climatology.

  13. Toward Integrative Uncertainty Accounting in Operational Hydrologic Ensemble Forecasting

    NASA Astrophysics Data System (ADS)

    Seo, D.; Demargne, J.; Wu, L.; Brown, J. D.; Schaake, J. C.

    2007-12-01

    Operational hydrologic forecasts are subject to large meteorological and hydrologic uncertainties, i.e., uncertainties in the hydrologic initial and boundary conditions, future boundary conditions, and observations. To produce reliable and skillful hydrologic ensemble forecasts, it is essential that both meteorological and hydrologic uncertainties are accurately accounted for. Toward that goal, NWS is developing a prototype hydrologic ensemble forecasting capability referred to as the eXperimental Ensemble Forecast System (XEFS) for operation at the NWS River Forecast Centers (RFC). It is envisioned that all or parts of this system may be shared with the research community for collaborative research and development toward improved operational hydrologic forecasting. In this talk, we describe the XEFS framework for integrative uncertainty accounting, identify key issues and share initial results.

  14. Satellite provided fixed communications services: A forecast of potential domestic demand through the year 2000: Volume 2: Main text

    NASA Technical Reports Server (NTRS)

    Kratochvil, D.; Bowyer, J.; Bhushan, C.; Steinnagel, K.; Kaushal, D.; Al-Kinani, G.

    1983-01-01

    Potential satellite-provided fixed communications services, baseline forecasts, net long haul forecasts, cost analysis, net addressable forecasts, capacity requirements, and satellite system market development are considered.

  15. [Population forecasts for the Netherlands, 1985-2035].

    PubMed

    Cruijsen Hgjm

    1986-03-01

    Some results from the most recent official population forecasts for the Netherlands for the period up to 2035 are presented. These projections were prepared using a cohort-component model, and provide forecasts for individual years of age, sex, and marital status. The assumptions used in their preparation are described. Three variants are presented for the forecasts, of which the medium variant is considered the most probable. (summary in ENG)

  16. An Assessment of Municipal and Industrial Water Use Forecasting Approaches.

    DTIC Science & Technology

    1981-05-01

    water conservation policy . A water use forecast is a conditional prediction of the level of water use at sane future time. The forecast may refer to...concerns, federal water resources policy has been significantly reformulated. Potential water conservation measures must now be identified and...effectively review, or to substantially revise forecasts provided by state and local entities. Present policy requires the Corps to consider a wide range

  17. AFGWC (Air Force Global Weather Central) Cloud Forecast Models

    DTIC Science & Technology

    1987-04-01

    Weather Center, Offutt AFB, NE 68113. This document contains export- controlled technical data. USAF ETAC/DOL ltr, 9 Feb 1995 UNCLASSIFIED ::Am:tiiiiii...wmmmmm •..-111111111111 ?TWWT’ . " iwimni WC FILE COP* Lf> 5 I o < AFGWC CLOUD FORECAST MODELS EDITED BY MAJOR TIMOTHY D, CRUM SCm ’-■ It...5LAYBR model makes extra-tropical forecasts for periods up to 48 hours. Forecasts of layer and total cloud, cloud type, layer temperatures , and

  18. Clear turbulence forecasting - Towards a union of art and science

    NASA Technical Reports Server (NTRS)

    Keller, J. L.

    1985-01-01

    The development of clear air turbulence (CAT) forecasting over the last several decades is reviewed in the context of empirical and theoretical research into the nature of nonconvective turbulence in the free atmosphere, particularly at jet stream levels. Various qualitative CAT forecasting techniques are examined, and prospects for an effective quantitative index to aid aviation meteorologists in jet stream level turbulence monitoring and forecasting are examined. Finally, the use of on-board sensors for short-term warning is discussed.

  19. Integrated Forecast and Reservoir Management for Northern California

    NASA Astrophysics Data System (ADS)

    Georgakakos, K. P.; Graham, N.; Georgakakos, A. P.; Yao, H.

    2011-12-01

    The INFORM (Integrated Forecast and Reservoir Management) Demonstration Project was created to demonstrate the utility of climate, weather and hydrologic predictions for water resources management in Northern California (includes Trinity River, the Sacramento River, the Feather River, the American River, the San Joaquin River, and the Sacramento-San Joaquin Delta). The INFORM system integrates climate-weather-hydrology forecasting and adaptive reservoir management methods, explicitly accounting for system input and model uncertainties. Operational ensemble forecasts from the Global Forecast System (GFS) and the Climate Forecast System (CFS) of the National Centers of Environmental Prediction (NCEP) are used to drive the WRF model and an Intermediate Complexity Regional Model (ICRM) to produce ensemble precipitation and temperature forecasts with a 10km x 10km resolution and from 6 hours to 30 days. These forecasts feed hydrologic models and provide ensemble inflow forecasts for the major reservoirs of Northern California. The ensemble inflow forecasts are input to a multiobjective and multisite adaptive decision support system designed to support the planning and management processes by deriving real time trade-offs among all relevant water management objectives (i.e., water supply and conservation, hydroelectric power production, flood control, and fisheries and environmental management) at user preferred risk levels. Operational tests over an initial three-year demonstration phase showed good operational performance both for wet and dry years. The presentation focuses on (1) modeling aspects of the current forecast and reservoir components and recent tests and (2) use of recent forecasts for the generation of applicable operational tradeoffs. The test results corroborate the operational value of the integrated forecast-management system.

  20. Regional Model Nesting Within GFS Daily Forecasts Over West Africa

    NASA Technical Reports Server (NTRS)

    Druyan, Leonard M.; Fulakeza, Matthew; Lonergan, Patrick; Worrell, Ruben

    2010-01-01

    The study uses the RM3, the regional climate model at the Center for Climate Systems Research of Columbia University and the NASA/Goddard Institute for Space Studies (CCSR/GISS). The paper evaluates 30 48-hour RM3 weather forecasts over West Africa during September 2006 made on a 0.5 grid nested within 1 Global Forecast System (GFS) global forecasts. September 2006 was the Special Observing Period #3 of the African Monsoon Multidisciplinary Analysis (AMMA). Archived GFS initial conditions and lateral boundary conditions for the simulations from the US National Weather Service, National Oceanographic and Atmospheric Administration were interpolated four times daily. Results for precipitation forecasts are validated against Tropical Rainfall Measurement Mission (TRMM) satellite estimates and data from the Famine Early Warning System (FEWS), which includes rain gauge measurements, and forecasts of circulation are compared to reanalysis 2. Performance statistics for the precipitation forecasts include bias, root-mean-square errors and spatial correlation coefficients. The nested regional model forecasts are compared to GFS forecasts to gauge whether nesting provides additional realistic information. They are also compared to RM3 simulations driven by reanalysis 2, representing high potential skill forecasts, to gauge the sensitivity of results to lateral boundary conditions. Nested RM3/GFS forecasts generate excessive moisture advection toward West Africa, which in turn causes prodigious amounts of model precipitation. This problem is corrected by empirical adjustments in the preparation of lateral boundary conditions and initial conditions. The resulting modified simulations improve on the GFS precipitation forecasts, achieving time-space correlations with TRMM of 0.77 on the first day and 0.63 on the second day. One realtime RM3/GFS precipitation forecast made at and posted by the African Centre of Meteorological Application for Development (ACMAD) in Niamey, Niger

  1. Incorporating weather uncertainty in demand forecasts for electricity market planning

    NASA Astrophysics Data System (ADS)

    Ziser, C. J.; Dong, Z. Y.; Wong, K. P.

    2012-07-01

    A major component of electricity network planning is to ensure supply capability into the future, through generation and transmission development. Accurate forecasts of maximum demand are a crucial component of this process, with future weather conditions having a large impact on forecast accuracy. This article presents an improved methodology for the consideration of weather uncertainty in electricity demand forecasts. Case studies based on the Australian national electricity market are used to validate the proposed methodology.

  2. Dust and Sand Forecasting in Iraq and Adjoining Countries

    DTIC Science & Technology

    1991-11-01

    8217’Illllllllt AD-A247 588 AWS/TN--91/001 DUST AND SAND FORECASTING IN IRAQ AND ADJOINING COUNTRIES by MSGT WALTER D. WILKERSON AFGWC/DOF NOVEMBER 1991...Sand Forecasting in Iraq and Adjoining Countries 6. Author: MSgt Walter D. Wilkerson, AFGWC/DOF 7. Performiig Organization Name and Address: Air...weather forecasting , discusses airborne dust and sand in Iraq, Kuwait, Syria, eastern Jordan, western Iran, and the northern Arabian Peninsula. Describes

  3. Retrospective Analysis of Technology Forecasting: In-Scope Extension

    DTIC Science & Technology

    2012-08-13

    were the means used to collect and verify forecasts, as well as the use of deep web research and broad sourcing. The study methodology is summarized in...include: • Searching the “ deep web ” to find forecast documents that are not indexed by standard search engines and therefore cannot be retrieved...used books and published reports that contain technological forecasts To search the deep web , we contracted with Bright Planet, which used proprietary

  4. Impact of AIRS Thermodynamic Profile on Regional Weather Forecast

    NASA Technical Reports Server (NTRS)

    Chou, Shih-Hung; Zavodsky, Brad; Jedlovee, Gary

    2010-01-01

    Prudent assimilation of AIRS thermodynamic profiles and quality indicators can improve initial conditions for regional weather models. AIRS-enhanced analysis has warmer and moister PBL. Forecasts with AIRS profiles are generally closer to NAM analyses than CNTL. Assimilation of AIRS leads to an overall QPF improvement in 6-h accumulated precipitation forecasts. Including AIRS profiles in assimilation process enhances the moist instability and produces stronger updrafts and a better precipitation forecast than the CNTL run.

  5. A Study of Slovenian Armed Forces Ammunition Forecasting Methodology

    DTIC Science & Technology

    2012-12-14

    purpose of this research is to investigate Slovenian Armed Forces (SAF) ammunition forecasting methods and determine if the current planning method can...documents. The research shows that current planning methods do not support SAF ammunition forecasting for future operations. Guidance for future projects...of this research is to investigate Slovenian Armed Forces (SAF) ammunition forecasting methods and determine if the current planning method can and

  6. No-source tsunami forecasting for Alaska communities

    NASA Astrophysics Data System (ADS)

    Tolkova, E.; Nicolsky, D.; Suleimani, E.

    2014-12-01

    The presented tsunami forecasting technique employs observations of the approaching tsunami at DART stations near the Aleutian trench to provide fast local forecasts for the Alaska communities. The suggested technique yields a prediction independent of the tsunami source estimate; increases forecast accuracy by using observations close to the target area; allows for checking the accuracy of the inversion-based forecast before the wave hits the coast. We demonstrate this forecasting technology, introduced in (Power and Tolkova, 2013, Ocean Dynamics, 63(11), 1213-1232), with imitating real-time forecasts of the 2011 Tohoku tsunami at several coastal sites in Alaska (to be compared with the gage records). The coastal forecasts are generated as the wave is registered at regional DART stations (46402, 46043, 46409, 46410). Note that while the DART array spans the Pacific Rim, the inversion-based forecasting methodologies can incorporate data from only 1-3 stations in the vicinity of the tsunami origin. We present a forecasting method which complements existing forecasting tools by using tsunami observations in a region to generate regional predictions independent of the tsunami source estimate. This method allows to utilize observing capabilities of the DART array, as well as tsunami detectors in cabled underwater networks (e.g. NEPTUNE in Canada). Future instrumentation on submarine communication cables will supply larger selection of open-ocean measurements and many more opportunities for this method. Figure: (Top) record of the 2012/10/28 Haida Gwaii tsunami at DART 46411; (Bottom) the tsunami record at Monterey tide gage (red) and its forecast (blue). The forecast is been made as the wave is been registered at the DART one hour before arriving at the gage (Power and Tolkova, 2013).

  7. Forecasting Emergency Department Crowding: An External, Multi-Center Evaluation

    PubMed Central

    Hoot, Nathan R.; Epstein, Stephen K.; Allen, Todd L.; Jones, Spencer S.; Baumlin, Kevin M.; Chawla, Neal; Lee, Anna T.; Pines, Jesse M.; Klair, Amandeep K.; Gordon, Bradley D.; Flottemesch, Thomas J.; LeBlanc, Larry J.; Jones, Ian; Levin, Scott R.; Zhou, Chuan; Gadd, Cynthia S.; Aronsky, Dominik

    2009-01-01

    Objective To apply a previously described tool to forecast ED crowding at multiple institutions, and to assess its generalizability for predicting the near-future waiting count, occupancy level, and boarding count. Methods The ForecastED tool was validated using historical data from five institutions external to the development site. A sliding-window design separated the data for parameter estimation and forecast validation. Observations were sampled at consecutive 10-minute intervals during 12 months (n = 52,560) at four sites and 10 months (n = 44,064) at the fifth. Three outcome measures – the waiting count, occupancy level, and boarding count – were forecast 2, 4, 6, and 8 hours beyond each observation, and forecasts were compared to observed data at corresponding times. The reliability and calibration were measured following previously described methods. After linear calibration, the forecasting accuracy was measured using the median absolute error (MAE). Results The tool was successfully used for five different sites. Its forecasts were more reliable, better calibrated, and more accurate at 2 hours than at 8 hours. The reliability and calibration of the tool were similar between the original development site and external sites; the boarding count was an exception, which was less reliable at four out of five sites. Some variability in accuracy existed among institutions; when forecasting 4 hours into the future, the MAE of the waiting count ranged between 0.6 and 3.1 patients, the MAE of the occupancy level ranged between 9.0 and 14.5% of beds, and the MAE of the boarding count ranged between 0.9 and 2.7 patients. Conclusion The ForecastED tool generated potentially useful forecasts of input and throughput measures of ED crowding at five external sites, without modifying the underlying assumptions. Noting the limitation that this was not a real-time validation, ongoing research will focus on integrating the tool with ED information systems. PMID:19716629

  8. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

    SciTech Connect

    Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad

    2015-12-08

    Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

  9. Wind Power Forecasting Error Distributions: An International Comparison; Preprint

    SciTech Connect

    Hodge, B. M.; Lew, D.; Milligan, M.; Holttinen, H.; Sillanpaa, S.; Gomez-Lazaro, E.; Scharff, R.; Soder, L.; Larsen, X. G.; Giebel, G.; Flynn, D.; Dobschinski, J.

    2012-09-01

    Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

  10. Tsunami Forecast Technology for Asteroid Impact Hazard Assessment

    NASA Astrophysics Data System (ADS)

    Titov, V. V.; Moore, C. W.

    2015-12-01

    Over 75% of all historically documented tsunamis have been generated by earthquakes. As the result, all existing Tsunami Warning and Forecast systems focus almost exclusively on detecting, warning and forecasting earthquake-generated tsunamis.The sequence of devastating tsunamis across the globe over the past 10 years has significantly heightened awareness and preparation activities associated with these high-impact events. Since the catastrophic 2004 Sumatra tsunami, NOAA has invested significant efforts in modernizing the U.S. tsunami warning system. Recent developments in tsunami modeling capability, inundation forecasting, sensing networks, dissemination capability and local preparation and mitigation activities have gone a long way toward enhancing tsunami resilience within the United States. The remaining quarter of the tsunami hazard problem is related to other mechanisms of tsunami generation, that may not have received adequate attention. Among those tsunami sources, the asteroid impact may be the most exotic, but possible one of the most devastating tsunami generation mechanisms. Tsunami forecast capabilities that have been developed for the tsunami warning system can be used to explore both, hazard assessment and the forecast of a tsunami generated by the asteroid impact. Existing tsunami flooding forecast technology allows for forecast for non-seismically generated tsunamis (asteroid impact, meteo-generated tsunamis, landslides, etc.), given an adequate data for the tsunami source parameters. Problems and opportunities for forecast of tsunamis from asteroid impact will be discussed. Preliminary results of impact-generated tsunami analysis for forecast and hazard assessment will be presented.

  11. Forecasting gaming revenues in Clark County, Nevada: Issues and methods

    SciTech Connect

    Edwards, B.K.; Bando, A.

    1992-07-01

    This paper describes the Western Area Gaming and Economic Response Simulator (WAGERS), a forecasting model that emphasizes the role of the gaming industry in Clark County, Nevada. Is is designed to generate forecasts of gaming revenues in Clark County, whose regional economy is dominated by the gaming industry. The model is meant to forecast Clark County gaming revenues and identifies the exogenous variables that affect gaming revenues. It will provide baseline forecasts of Clark County gaming revenues in order to assess changes in gaming-related economic activity resulting from changes in regional economic activity and tourism.

  12. Intermittent Demand Forecasting in a Tertiary Pediatric Intensive Care Unit.

    PubMed

    Cheng, Chen-Yang; Chiang, Kuo-Liang; Chen, Meng-Yin

    2016-10-01

    Forecasts of the demand for medical supplies both directly and indirectly affect the operating costs and the quality of the care provided by health care institutions. Specifically, overestimating demand induces an inventory surplus, whereas underestimating demand possibly compromises patient safety. Uncertainty in forecasting the consumption of medical supplies generates intermittent demand events. The intermittent demand patterns for medical supplies are generally classified as lumpy, erratic, smooth, and slow-moving demand. This study was conducted with the purpose of advancing a tertiary pediatric intensive care unit's efforts to achieve a high level of accuracy in its forecasting of the demand for medical supplies. On this point, several demand forecasting methods were compared in terms of the forecast accuracy of each. The results confirm that applying Croston's method combined with a single exponential smoothing method yields the most accurate results for forecasting lumpy, erratic, and slow-moving demand, whereas the Simple Moving Average (SMA) method is the most suitable for forecasting smooth demand. In addition, when the classification of demand consumption patterns were combined with the demand forecasting models, the forecasting errors were minimized, indicating that this classification framework can play a role in improving patient safety and reducing inventory management costs in health care institutions.

  13. A Stochastic-Dynamic Model for Real Time Flood Forecasting

    NASA Astrophysics Data System (ADS)

    Chow, K. C. A.; Watt, W. E.; Watts, D. G.

    1983-06-01

    A stochastic-dynamic model for real time flood forecasting was developed using Box-Jenkins modelling techniques. The purpose of the forecasting system is to forecast flood levels of the Saint John River at Fredericton, New Brunswick. The model consists of two submodels: an upstream model used to forecast the headpond level at the Mactaquac Dam and a downstream model to forecast the water level at Fredericton. Inputs to the system are recorded values of the water level at East Florenceville, the headpond level and gate position at Mactaquac, and the water level at Fredericton. The model was calibrated for the spring floods of 1973, 1974, 1977, and 1978, and its usefulness was verified for the 1979 flood. The forecasting results indicated that the stochastic-dynamic model produces reasonably accurate forecasts for lead times up to two days. These forecasts were then compared to those from the existing forecasting system and were found to be as reliable as those from the existing system.

  14. 7 CFR 612.3 - Data collected and forecasts.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... provide related drometeorological data, such as precipitation, temperature, humidity, solar tradiation, and wind. (b) Water supply forecasts in the western states area are generally made monthly...

  15. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis

    SciTech Connect

    Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad

    2015-10-02

    Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

  16. Forecasting gaming revenues in Clark County, Nevada: Issues and methods

    SciTech Connect

    Edwards, B.K.; Bando, A.

    1992-01-01

    This paper describes the Western Area Gaming and Economic Response Simulator (WAGERS), a forecasting model that emphasizes the role of the gaming industry in Clark County, Nevada. Is is designed to generate forecasts of gaming revenues in Clark County, whose regional economy is dominated by the gaming industry. The model is meant to forecast Clark County gaming revenues and identifies the exogenous variables that affect gaming revenues. It will provide baseline forecasts of Clark County gaming revenues in order to assess changes in gaming-related economic activity resulting from changes in regional economic activity and tourism.

  17. Forecast communication through the newspaper Part 2: perceptions of uncertainty

    NASA Astrophysics Data System (ADS)

    Harris, Andrew J. L.

    2015-04-01

    In the first part of this review, I defined the media filter and how it can operate to frame and blame the forecaster for losses incurred during an environmental disaster. In this second part, I explore the meaning and role of uncertainty when a forecast, and its basis, is communicated through the response and decision-making chain to the newspaper, especially during a rapidly evolving natural disaster which has far-reaching business, political, and societal impacts. Within the media-based communication system, there remains a fundamental disconnect of the definition of uncertainty and the interpretation of the delivered forecast between various stakeholders. The definition and use of uncertainty differs especially between scientific, media, business, and political stakeholders. This is a serious problem for the scientific community when delivering forecasts to the public though the press. As reviewed in Part 1, the media filter can result in a negative frame, which itself is a result of bias, slant, spin, and agenda setting introduced during passage of the forecast and its uncertainty through the media filter. The result is invariably one of anger and fury, which causes loss of credibility and blaming of the forecaster. Generation of a negative frame can be aided by opacity of the decision-making process that the forecast is used to support. The impact of the forecast will be determined during passage through the decision-making chain where the precautionary principle and cost-benefit analysis, for example, will likely be applied. Choice of forecast delivery format, vehicle of communication, syntax of delivery, and lack of follow-up measures can further contribute to causing the forecast and its role to be misrepresented. Follow-up measures to negative frames may include appropriately worded press releases and conferences that target forecast misrepresentation or misinterpretation in an attempt to swing the slant back in favor of the forecaster. Review of

  18. Flood forecasting for River Mekong with data-based models

    NASA Astrophysics Data System (ADS)

    Shahzad, Khurram M.; Plate, Erich J.

    2014-09-01

    In many regions of the world, the task of flood forecasting is made difficult because only a limited database is available for generating a suitable forecast model. This paper demonstrates that in such cases parsimonious data-based hydrological models for flood forecasting can be developed if the special conditions of climate and topography are used to advantage. As an example, the middle reach of River Mekong in South East Asia is considered, where a database of discharges from seven gaging stations on the river and 31 rainfall stations on the subcatchments between gaging stations is available for model calibration. Special conditions existing for River Mekong are identified and used in developing first a network connecting all discharge gages and then models for forecasting discharge increments between gaging stations. Our final forecast model (Model 3) is a linear combination of two structurally different basic models: a model (Model 1) using linear regressions for forecasting discharge increments, and a model (Model 2) using rainfall-runoff models. Although the model based on linear regressions works reasonably well for short times, better results are obtained with rainfall-runoff modeling. However, forecast accuracy of Model 2 is limited by the quality of rainfall forecasts. For best results, both models are combined by taking weighted averages to form Model 3. Model quality is assessed by means of both persistence index PI and standard deviation of forecast error.

  19. Metrics for the Evaluation the Utility of Air Quality Forecasting

    NASA Astrophysics Data System (ADS)

    Sumo, T. M.; Stockwell, W. R.

    2013-12-01

    Global warming is expected to lead to higher levels of air pollution and therefore the forecasting of both long-term and daily air quality is an important component for the assessment of the costs of climate change and its impact on human health. Some of the risks associated with poor air quality days (where the Air Pollution Index is greater than 100), include hospital visits and mortality. Accurate air quality forecasting has the potential to allow sensitive groups to take appropriate precautions. This research builds metrics for evaluating the utility of air quality forecasting in terms of its potential impacts. Our analysis of air quality models focuses on the Washington, DC/Baltimore, MD region over the summertime ozone seasons between 2010 and 2012. The metrics that are relevant to our analysis include: (1) The number of times that a high ozone or particulate matter (PM) episode is correctly forecasted, (2) the number of times that high ozone or PM episode is forecasted when it does not occur and (3) the number of times when the air quality forecast predicts a cleaner air episode when the air was observed to have high ozone or PM. Our evaluation of the performance of air quality forecasts include those forecasts of ozone and particulate matter and data available from the U.S. Environmental Protection Agency (EPA)'s AIRNOW. We also examined observational ozone and particulate matter data available from Clean Air Partners. Overall the forecast models perform well for our region and time interval.

  20. Using ensembles in water management: forecasting dry and wet episodes

    NASA Astrophysics Data System (ADS)

    van het Schip-Haverkamp, Tessa; van den Berg, Wim; van de Beek, Remco

    2015-04-01

    Extreme weather situations as droughts and extensive precipitation are becoming more frequent, which makes it more important to obtain accurate weather forecasts for the short and long term. Ensembles can provide a solution in terms of scenario forecasts. MeteoGroup uses ensembles in a new forecasting technique which presents a number of weather scenarios for a dynamical water management project, called Water-Rijk, in which water storage and water retention plays a large role. The Water-Rijk is part of Park Lingezegen, which is located between Arnhem and Nijmegen in the Netherlands. In collaboration with the University of Wageningen, Alterra and Eijkelkamp a forecasting system is developed for this area which can provide water boards with a number of weather and hydrology scenarios in order to assist in the decision whether or not water retention or water storage is necessary in the near future. In order to make a forecast for drought and extensive precipitation, the difference 'precipitation- evaporation' is used as a measurement of drought in the weather forecasts. In case of an upcoming drought this difference will take larger negative values. In case of a wet episode, this difference will be positive. The Makkink potential evaporation is used which gives the most accurate potential evaporation values during the summer, when evaporation plays an important role in the availability of surface water. Scenarios are determined by reducing the large number of forecasts in the ensemble to a number of averaged members with each its own likelihood of occurrence. For the Water-Rijk project 5 scenario forecasts are calculated: extreme dry, dry, normal, wet and extreme wet. These scenarios are constructed for two forecasting periods, each using its own ensemble technique: up to 48 hours ahead and up to 15 days ahead. The 48-hour forecast uses an ensemble constructed from forecasts of multiple high-resolution regional models: UKMO's Euro4 model,the ECMWF model, WRF and