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. 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. PMID:18695214

  4. 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.

  5. 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.

  6. 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 between the…

  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. Pharmacotherapy for borderline patients: business as usual or by default?

    PubMed

    Ingenhoven, Theo

    2015-04-01

    In their analysis of a representative sample from the Prescribing Observatory for Mental Health in the UK health services, Paton et al found that 92% of patients with borderline personality disorder (BPD) received prescriptions for psychotropic medications. Although international guidelines recommend pharmacotherapy for comorbid psychiatric disorders whenever necessary, 82% of the UK BPD patients without such comorbid conditions nevertheless received pharmacotherapy "by default," mostly off-label polypharmacy without adequate psychiatric controls for effectiveness and tolerability. Business as usual? Bad care? International practice guidelines for the treatment of BPD all recommend evidence-based psychological treatment whenever possible (especially manualized psychotherapy like dialectical behavior therapy, schema-focused therapy, mentalization-based treatment, transference-focused psychotherapy) as the first-choice treatment.

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

    PubMed Central

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

    2013-01-01

    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. PMID:24003127

  10. 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.

  11. 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. PMID:24003127

  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+

    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.

  15. 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.

  16. 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. PMID:25588807

  17. 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…

  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. 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. PMID:26121163

  4. Future changes in climate, ocean circulation, ecosystems, and biogeochemical cycling simulated for a business-as-usual CO2 emission scenario until year 4000 AD

    NASA Astrophysics Data System (ADS)

    Schmittner, Andreas; Oschlies, Andreas; Matthews, H. Damon; Galbraith, Eric D.

    2008-03-01

    A new model of global climate, ocean circulation, ecosystems, and biogeochemical cycling, including a fully coupled carbon cycle, is presented and evaluated. The model is consistent with multiple observational data sets from the past 50 years as well as with the observed warming of global surface air and sea temperatures during the last 150 years. It is applied to a simulation of the coming two millennia following a business-as-usual scenario of anthropogenic CO2 emissions (SRES A2 until year 2100 and subsequent linear decrease to zero until year 2300, corresponding to a total release of 5100 GtC). Atmospheric CO2 increases to a peak of more than 2000 ppmv near year 2300 (that is an airborne fraction of 72% of the emissions) followed by a gradual decline to ˜1700 ppmv at year 4000 (airborne fraction of 56%). Forty-four percent of the additional atmospheric CO2 at year 4000 is due to positive carbon cycle-climate feedbacks. Global surface air warms by ˜10°C, sea ice melts back to 10% of its current area, and the circulation of the abyssal ocean collapses. Subsurface oxygen concentrations decrease, tripling the volume of suboxic water and quadrupling the global water column denitrification. We estimate 60 ppb increase in atmospheric N2O concentrations owing to doubling of its oceanic production, leading to a weak positive feedback and contributing about 0.24°C warming at year 4000. Global ocean primary production almost doubles by year 4000. Planktonic biomass increases at high latitudes and in the subtropics whereas it decreases at midlatitudes and in the tropics. In our model, which does not account for possible direct impacts of acidification on ocean biology, production of calcium carbonate in the surface ocean doubles, further increasing surface ocean and atmospheric pCO2. This represents a new positive feedback mechanism and leads to a strengthening of the positive interaction between climate change and the carbon cycle on a multicentennial to millennial

  5. 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…

  6. 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. PMID:25673635

  7. Not business as usual for water utilities

    SciTech Connect

    Rodgers, L.M.

    1990-07-05

    This article addresses the implementation of the requirements of the Safe Drinking Water Act (SDWA) Amendments of 1986 and their economic impacts to water utilities, financiers, stockholders and consumers. The author looks at various funding schemes, rate structure changes and potential mergers all designed to finance the compliance with new EPA standards.

  8. 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.

  9. 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…

  10. 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…

  11. Drosophila grim induces apoptosis in mammalian cells.

    PubMed Central

    Clavería, C; Albar, J P; Serrano, A; Buesa, J M; Barbero, J L; Martínez-A, C; Torres, M

    1998-01-01

    Genetic studies have shown that grim is a central genetic switch of programmed cell death in Drosophila; however, homologous genes have not been described in other species, nor has its mechanism of action been defined. We show here that grim expression induces apoptosis in mouse fibroblasts. Cell death induced by grim in mammalian cells involves membrane blebbing, cytoplasmic loss and nuclear DNA fragmentation. Grim-induced apoptosis is blocked by both natural and synthetic caspase inhibitors. We found that grim itself shows caspase-dependent proteolytic processing of its C-terminus in vitro. Grim-induced death is antagonized by bcl-2 in a dose-dependent manner, and neither Fas signalling nor p53 are required for grim pro-apoptotic activity. Grim protein localizes both in the cytosol and in the mitochondria of mouse fibroblasts, the latter location becoming predominant as apoptosis progresses. These results show that Drosophila grim induces death in mammalian cells by specifically acting on mitochondrial apoptotic pathways executed by endogenous caspases. These findings advance our knowledge of the mechanism by which grim induces apoptosis and show the conservation through evolution of this crucial programmed cell death pathway. PMID:9857177

  12. "Not Business as Usual": Sport Education Pedagogy in Practice

    ERIC Educational Resources Information Center

    Kim, Jinhee; Penney, Dawn; Cho, Mihye; Choi, Heejin

    2006-01-01

    This article focuses on a Sport Education project in Korea that has explored pedagogical issues during teachers' initial and developing implementation of Sport Education. Drawing on data gathered between 2004 and 2005 in collaboration with teachers in a middle school in Korea, the article presents a detailed analysis of developments in one case…

  13. 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…

  14. 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.

  15. 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…

  16. Gondwana breakup and plate kinematics: Business as usual

    NASA Astrophysics Data System (ADS)

    Eagles, Graeme; Vaughan, Alan P. M.

    2009-05-01

    A tectonic model of the Weddell Sea is built by composing a simple circuit with optimized rotations describing the growth of the South Atlantic and SW Indian oceans. The model independently and accurately reproduces the consensus elements of the Weddell Sea's spreading record and continental margins, and offers solutions to remaining controversies there. At their present resolutions, plate kinematic data from the South Atlantic and SW Indian oceans and Weddell Sea rule against the proposed, but controversial, independent movements of small plates during Gondwana breakup that have been attributed to the presence or impact of a mantle plume. Hence, although supercontinent breakup here was accompanied by extraordinary excess volcanism, there is no indication from plate kinematics that the causes of that volcanism provided a unique driving mechanism for it.

  17. 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…

  18. 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 Commission of "two holistic…

  19. 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…

  20. 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…

  1. Grim19 Attenuates DSS Induced Colitis in an Animal Model.

    PubMed

    Kim, Jae-Kyung; Lee, Seung Hoon; Lee, Seon-Young; Kim, Eun-Kyung; Kwon, Jeong-Eun; Seo, Hyeon-Beom; Lee, Han Hee; Lee, Bo-In; Park, Sung-Hwan; Cho, Mi-La

    2016-01-01

    DSS induced colitis is a chronic inflammatory disease characterized by inflammation in the gastrointestinal tract, which destabilizes the gut and induces an uncontrolled immune response. Although DSS induced colitis is generally thought to develop as a result of an abnormally active intestinal immune system, its pathogenesis remains unclear. Gene associated with retinoid interferon induced mortality (Grim) 19 is an endogenous specific inhibitor of STAT3, which regulates the expression of proinflammatory cytokines. In this study, we investigated the influence of GRIM19 in a DSS induced colitis mouse model. We hypothesized that Grim19 would ameliorate DSS induced colitis by altering STAT3 activity and intestinal inflammation. Grim19 ameliorated DSS induced colitis severity and protected intestinal tissue. The expression of STAT3 and proinflammatory cytokines such as IL-1β and TNF-α in colon and lymph nodes was decreased significantly by Grim19. Moreover, DSS induced colitis progression in a Grim19 transgenic mouse line was inhibited in association with a reduction in STAT3 and IL-17 expression. These results suggest that Grim19 attenuates DSS induced colitis by suppressing the excessive inflammatory response mediated by STAT3 activation.

  2. Advances in fracture algorithm development in GRIM

    NASA Astrophysics Data System (ADS)

    Cullis, I.; Church, P.; Greenwood, P.; Huntington-Thresher, W.; Reynolds, M.

    2003-09-01

    The numerical treatment of fracture processes has long been a major challenge in any hydrocode, but has been particularly acute in Eulerian Hydrocodes. This is due to the difficulties in establishing a consistent process for treating failure and the post failure treatment, which is complicated by advection, mixed cell and interface issues, particularly post failure. This alone increase the complexity of incorporating and validating a failure model compared to a Lagrange hydrocode, where the numerical treatment is much simpler. This paper outlines recent significant progress in the incorporation of fracture models in GRIM and the advection of damage across cell boundaries within the mesh. This has allowed a much more robust treatment of fracture in an Eulerian frame of reference and has greatly expanded the scope of tractable dynamic fracture scenarios. The progress has been possible due to a careful integration of the fracture algorithm within the numerical integration scheme to maintain a consistent representation of the physics. The paper describes various applications, which demonstrate the robustness and efficiency of the scheme and highlight some of the future challenges.

  3. 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.

  4. Overexpression of GRIM-19, a mitochondrial respiratory chain complex I protein, suppresses hepatocellular carcinoma growth

    PubMed Central

    Kong, Dexia; Zhao, Lijing; Du, Yanwei; He, Ping; Zou, Yabin; Yang, Luoluo; Sun, Liankun; Wang, Hebin; Xu, Deqi; Meng, Xiangwei; Sun, Xun

    2014-01-01

    GRIM-19 has been demonstrated as an important regulator for the normal tissue development. Recently, more evidences regarded GRIM-19 as the new tumor suppressor. However, the possible mechanisms underlying GRIM-19 suppressing cancer growth are unclear. In the present study, Paired hepatocellular carcinoma (HCC) and adjacent non-tumor liver tissues were obtained from 54 patients who underwent primary surgical HCC tissue resection. GRIM-19 protein expression in HCC tissues was performed by immunohistochemistry. Cells were transfected by lentiviruses plasmid expressing GRIM-19. RT-PCR and Western blot analyses were performed to confirm the expression of GRIM-19 mRNA or protein. Cell proliferation was assessed by MTT and FCM analyses. Mitochondrial membrane potential and apoptosis were respectively determined by using fluorescence microscopy and FCM analyses. AKT1, pAKT1, cyclinD1, CDK4, PCNA, Bax, Bcl-2, cleaved caspase-9, cleaved caspase-3, and cytochrome C were detected by Western blot and immunofluorescence. GRIM-19 protein expression was markedly lower in HCC than in paired adjacent non-tumor liver tissues. GRIM-19 overexpression in HCC cells significantly induced cell cycle arrest and enhanced apoptosis. We also found that AKT1 expression and phosphorylation were regulated by the expression of GRIM-19. Collectively, our study demonstrated that GRIM-19 overexpression suppressed HCC growth and downregulated AKT1 expression, suggesting that GRIM-19 might play a crucial role in hepatocarcinogenesis through negatively regulating the PI3K/AKT signaling pathway. PMID:25550785

  5. The GRIM-19 plays a vital role in shrimps' responses to Vibrio alginolyticus.

    PubMed

    Peng, Ting; Gu, Mei-Mei; Zhao, Chang-Sheng; Wang, Wei-Na; Huang, Ming-Zhu; Xie, Chen-Ying; Xiao, Yu-Chao; Cha, Gui-Hong; Liu, Yuan

    2016-02-01

    GRIM-19 (gene associated with retinoid-interferon-induced mortality 19), a novel cell death regulatory gene, plays important roles in cell apoptosis, mitochondrial respiratory chain and immune response. It has been reported to interact physically with STAT3 and inhibit STAT3-dependent signal transduction. In this study, a new GRIM-19 gene, which is a 789-bp gene encoding a 149 amino acids protein, is identified and characterized from Litopenaeus vannamei. The tissue distribution patterns showed that LvGRIM-19 was widely expressed in all examined tissues, with the highest expression in muscle. Quantitative real-time PCR revealed that LvGRIM-19 was down-regulated in hepatopancreas after infection with the Vibrio alginolyticus. Knockdown of LvGRIM-19 by RNA interference resulted in a lower mortality of L. vannamei under V. alginolyticus infection, as well as an enhancement in the protein expression of STAT gene and JAK gene. V. alginolyticus infection caused an increase apoptotic cell ratio and ROS production of L. vannamei, while LvGRIM-19 silenced shrimps showed significantly lower than GFP group. Our results suggest that the GRIM-19 plays a vital role in shrimps' responses to V. alginolyticus. Interferenced LvGRIM-19 treatment during V. alginolyticus infection could increase 12 h survival rate, which might indicated that LvGRIM-19 is closely related to death of shrimps. PMID:26702559

  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. 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)

  8. Business as Usual: Exploring Private Sector Participation in American Public Schools.

    ERIC Educational Resources Information Center

    Shakeshaft, Charol; Trachtman, Roberta

    Although there is widespread publicity about the involvement of businesses with schools, and as President Reagan as well as authors of reform reports continue to call upon the private sector to help education, it is unclear to what extent such relationships exist and what they are accomplishing. A 10-page, 55-question survey was mailed to the…

  9. Challenges and Hurdles to Business as Usual in Drug Development for Treatment of Rare Diseases.

    PubMed

    Swinney, D C

    2016-10-01

    Only 10-15 first-in-class new medicines are approved each year by the global pharmaceutical industry for all diseases, of which less than a third is for rare (orphan) diseases. The drug discovery processes to identify rare and common diseases are similar, suggesting it will be impossible to discover new drugs for even a small fraction of the rare diseases using the current paradigm. Different approaches are required to address this large unmet medical need. PMID:27393380

  10. 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…

  11. Challenges and Hurdles to Business as Usual in Drug Development for Treatment of Rare Diseases.

    PubMed

    Swinney, D C

    2016-10-01

    Only 10-15 first-in-class new medicines are approved each year by the global pharmaceutical industry for all diseases, of which less than a third is for rare (orphan) diseases. The drug discovery processes to identify rare and common diseases are similar, suggesting it will be impossible to discover new drugs for even a small fraction of the rare diseases using the current paradigm. Different approaches are required to address this large unmet medical need.

  12. Business as Usual: The Use of English in the Professional World in Hong Kong

    ERIC Educational Resources Information Center

    Evans, Stephen

    2010-01-01

    This article examines the role of written and spoken English vis-a-vis written Chinese, Cantonese and Putonghua in the four key service industries that have driven Hong Kong's economy in the past decade. The study forms part of a long-standing and continuing investigation into the impact of Hong Kong's transition from British colony to Chinese…

  13. 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…

  14. "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…

  15. 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…

  16. Strategy Use by Nonnative English-Speaking Students in an MBA Program: Not Business as Usual!

    ERIC Educational Resources Information Center

    Parks, Susan; Raymond, Patricia M.

    2004-01-01

    Despite the long-standing interest in strategy use and language learning, little attention has been given to how social context may constrain or facilitate this use or the development of new strategies. Drawing on data from a longitudinal qualitative study, we discuss this issue in relation to the experiences of Chinese students from the People's…

  17. GRIM-19 Restores Cervical Cancer Cell Senescence by Repressing hTERT Transcription.

    PubMed

    Zhou, Ying; Xu, Fei; Tao, Feng; Feng, Dingqing; Ling, Bin; Qian, Lili; Yang, Xia; Wang, Qingyuan; Wang, Huiyan; Zhao, Weidong; Cheng, Yong; Shan, Ge; Kalvakolanu, Dhan V; Xiao, Weihua

    2016-08-01

    High telomerase activity promotes tumor growth by stabilizing damaged chromosomes and their mitotic replication. Overactivation of telomerase activity has been reported in cervical cancer, a malignancy caused by high-risk human papillomaviruses (HR-HPVs). The HR-HPV E6 can activate hTERT promoter by interacting with E6AP or other binding proteins and by stabilizing the interaction between hTERT and E6AP. GRIM-19 is a novel tumor suppressor that affects multiple targets in a cell to regulate growth. We have previously reported the interaction of GRIM-19 with 18E6 and E6AP to disrupt the E6/E6AP complex and increase the autoubiquitination of E6AP. In this study, we characterized the interaction of GRIM-19 with 16E6 (an oncoprotein produced by HPV16) and identified the binding sites that mediate this interaction. We also found that GRIM-19 expression in cervical cancer cells could inhibit telomerase activity by inhibiting the transactivation of the hTERT promoter by E6, thereby promoting cervical cancer cell senescence. Moreover, we identified a negative correlation between GRIM-19 and hTERT expression in cervical cancer tissues. Suppression of GRIM-19 and induction of hTERT levels were associated with lymph node metastasis, advanced clinical stage, and poor prognosis. This study identified another important novel antitumor molecular link associated with GRIM-19 in the tumorigenesis. PMID:27142689

  18. Expression and functional characterization of a gene associated with retinoid-interferon-induced mortality 19 (GRIM-19) from orange-spotted grouper (Epinephelus coioides).

    PubMed

    Shi, Yan; Zhao, Zhe; Zhu, Xinping; Chen, Kunci; Zhang, Qiya

    2013-01-01

    GRIM-19 is a nuclear encoded subunit of complex I that has been implicated in apoptosis. The protein participates in multiple functions including the innate immune response. GRIM-19 has been studied in humans and other mammals; however, fish GRIM-19 has not been well characterized. In this study, a new GRIM-19 gene, EcGRIM-19, was isolated from the orange-spotted grouper (Epinephelus coioides) cDNA library, which was constructed following LPS treatment. EcGRIM-19 is a 582-bp gene that encodes a 144-amino acid protein. The gene is a true ortholog of mammalian GRIM-19. EcGRIM-19 exhibits ubiquitous and constitutive expression in the different tissues of the orange-spotted grouper. The expression levels of EcGRIM-19 are altered in the gill, spleen, kidney and liver after induction with LPS. The subcellular localization analysis demonstrated that the EcGRIM-19 protein is localized predominantly in the mitochondria. In addition, amino acids 30-50 of the protein are responsible for the mitochondrial localization of EcGRIM-19. The caspase assay demonstrated that the overexpression of GRIM-19 enhanced the cellular sensitivity to interferon(IFN)-β- and retinoic acid (RA)-induced death in HeLa cells. The data presented in this study are important for further understanding the EcGRIM-19 gene function in fish.

  19. 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.

  20. GRIM-19 opposes reprogramming of glioblastoma cell metabolism via HIF1α destabilization.

    PubMed

    Liu, Qian; Wang, Lulu; Wang, Zhaojuan; Yang, Yang; Tian, Jingxia; Liu, Guoliang; Guan, Dongshi; Cao, Xinmin; Zhang, Yanmin; Hao, Aijun

    2013-08-01

    The metabolism that sustains cancer cells is adapted preferentially to glycolysis, even under aerobic conditions (Warburg effect). This effect was one of the first alterations in cancer cells recognized as conferring a survival advantage. In this study, we show that gene associated with retinoid-interferon-induced mortality-19 (GRIM-19), which was previously identified as a tumor suppressor protein associated with growth inhibition and cell apoptosis, contributes to the switch between oxidative and glycolytic pathways. In parallel to this, vascular endothelial growth factor, which promotes neovascularization, is also regulated. We have identified hypoxia-inducible factor 1α (HIF1α) as the downstream factor of GRIM-19 in human glioblastoma cell lines. Downregulation of GRIM-19 promotes HIF1α synthesis in a STAT3-dependent manner, which acts as a potential competitive inhibitor for von Hippel-Lindau (pVHL)-HIF1α interaction, and thereby prevents HIF1α from pVHL-mediated ubiquitination and proteasomal degradation. Taken together, it is concluded that GRIM-19, a potential tumor suppressor gene, performs its function in part via regulating glioblastoma metabolic reprogramming through STAT3-HIF1α signaling axis, and this has added new perspective to its role in tumorigenesis, thus providing potential strategies for tumor metabolic therapy. PMID:23580587

  1. Inhibitor of Apoptosis Proteins Physically Interact with and Block Apoptosis Induced by Drosophila Proteins HID and GRIM

    PubMed Central

    Vucic, Domagoj; Kaiser, William J.; Miller, Lois K.

    1998-01-01

    Reaper (RPR), HID, and GRIM activate apoptosis in cells programmed to die during Drosophila development. We have previously shown that transient overexpression of RPR in the lepidopteran SF-21 cell line induces apoptosis and that members of the inhibitor of apoptosis (IAP) family of antiapoptotic proteins can inhibit RPR-induced apoptosis and physically interact with RPR through their BIR motifs (D. Vucic, W. J. Kaiser, A. J. Harvey, and L. K. Miller, Proc. Natl. Acad. Sci. USA 94:10183–10188, 1997). In this study, we found that transient overexpression of HID and GRIM also induced apoptosis in the SF-21 cell line. Baculovirus and Drosophila IAPs blocked HID- and GRIM-induced apoptosis and also physically interacted with them through the BIR motifs of the IAPs. The region of sequence similarity shared by RPR, HID, and GRIM, the N-terminal 14 amino acids of each protein, was required for the induction of apoptosis by HID and its binding to IAPs. When stably overexpressed by fusion to an unrelated, nonapoptotic polypeptide, the N-terminal 37 amino acids of HID and GRIM were sufficient to induce apoptosis and confer IAP binding activity. However, GRIM was more complex than HID since the C-terminal 124 amino acids of GRIM retained apoptosis-inducing and IAP binding activity, suggesting the presence of two independent apoptotic motifs within GRIM. Coexpression of IAPs with HID stabilized HID levels and resulted in the accumulation of HID in punctate perinuclear locations which coincided with IAP localization. The physical interaction of IAPs with RPR, HID, and GRIM provides a common molecular mechanism for IAP inhibition of these Drosophila proapoptotic proteins. PMID:9584170

  2. 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.

  3. 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…

  4. Application of Goldthorpe PDF model to dynamic fracture. Applications using the GRIM Eulerian hydrocode

    NASA Astrophysics Data System (ADS)

    Cullis, I. G.; Church, P. D.; Townsley, R.; Greenwood, P.; Proud, W. G.

    2006-08-01

    The Goldthorpe Path Dependent Failure (PDF) model has been incorporated into the GRIM Eulerian hydrocode and has been applied to a number of dynamic fracture scenarios. The model has allowed a step change improvement in the simulation of fracture processes in an Euler scheme. The applications include shear plugging of a plate due to ballistic impact, prediction of the so-called V{50} for a small mass projectile and the impact of a generic EFP against an aluminium plate target. It has been noted that the prediction of temperature in hydrocodes, still requires more effort, particularly when materials approach the melt point. In addition there is also significant batch to batch variation in the fracture properties in materials, which needs to be taken into account when simulating a given application scenario. The paper discusses these points and recognises that GRIM is now an integral part of the design process for new ballistic designs.

  5. 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.

  6. 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

  7. Drosophila Morgue is an F box/ubiquitin conjugase domain protein important for grim-reaper mediated apoptosis.

    PubMed

    Wing, John P; Schreader, Barbara A; Yokokura, Takakazu; Wang, Yiqin; Andrews, Paul S; Huseinovic, Neda; Dong, Carolyn K; Ogdahl, Justyne L; Schwartz, Lawrence M; White, Kristin; Nambu, John R

    2002-06-01

    In Drosophila melanogaster, apoptosis is controlled by the integrated actions of the Grim-Reaper (Grim-Rpr) and Drosophila Inhibitor of Apoptosis (DIAP) proteins (reviewed in refs 1 4). The anti-apoptotic DIAPs bind to caspases and inhibit their proteolytic activities. DIAPs also bind to Grim-Rpr proteins, an interaction that promotes caspase activity and the initiation of apoptosis. Using a genetic modifier screen, we identified four enhancers of grim-reaper-induced apoptosis that all regulate ubiquitination processes: uba-1, skpA, fat facets (faf), and morgue. Strikingly, morgue encodes a unique protein that contains both an F box and a ubiquitin E2 conjugase domain that lacks the active site Cys required for ubiquitin linkage. A reduction of morgue activity suppressed grim-reaper-induced cell death in Drosophila. In cultured cells, Morgue induced apoptosis that was suppressed by DIAP1. Targeted morgue expression downregulated DIAP1 levels in Drosophila tissue, and Morgue and Rpr together downregulated DIAP1 levels in cultured cells. Consistent with potential substrate binding functions in an SCF ubiquitin E3 ligase complex, Morgue exhibited F box-dependent association with SkpA and F box-independent association with DIAP1. Morgue may thus have a key function in apoptosis by targeting DIAP1 for ubiquitination and turnover.

  8. 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.

  9. Guilty pleasures and grim necessities: affective attitudes in dilemmas of self-control.

    PubMed

    Giner-Sorolla, R

    2001-02-01

    Do self-control situations pit controlled reason against impulsive emotion, or do some emotions support the controlled choice? A pilot study of self-control attitudes found ambivalence between hedonic affect associated with short-term perspectives and self-conscious affect associated with the long term. In Study 1, negative self-conscious affect accompanied higher self-control among delayed-cost dilemmas ("guilty pleasures") but not delayed-benefit dilemmas ("grim necessities"). Study 2 showed that hedonic affect was more accessible than was self-conscious affect, but this difference was less among high self-control dilemmas. In Study 3, unobtrusively primed self-conscious emotion words caused dieters to eat less if the emotions were negative, more if positive. Hedonic positive and negative emotion words had the opposite effect. Self-conscious emotional associations, then, can support self-control if brought to mind before the chance to act.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Paradigm Shift or Business as Usual: The Reception and Implementation of the BYU-Idaho Learning Model by Faculty Members--A Mixed Methods Study

    ERIC Educational Resources Information Center

    Thurgood, Larry L.

    2010-01-01

    A mixed methods study examined how a newly developed campus-wide framework for learning and teaching, called the Learning Model, was accepted and embraced by faculty members at Brigham Young University-Idaho from September 2007 to January 2009. Data from two administrations of the Approaches to Teaching Inventory showed that (a) faculty members…

  17. 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

  18. 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.

  19. Down-Regulation of GRIM-19 Expression Is Associated With Hyperactivation of STAT3-Induced Gene Expression and Tumor Growth in Human Cervical Cancers

    PubMed Central

    Zhou, Ying; Li, Min; Wei, Ying; Feng, Dingqing; Peng, Cheng; Weng, Haiyan; Ma, Yang; Bao, Liang; Nallar, Shreeram; Kalakonda, Sudhakar; Xiao, Weihua

    2009-01-01

    Cervical cancer is the most common malignant disease responsible for the deaths of a large number of women in the developing world. Although certain strains of human papillomavirus (HPV) have been identified as the cause of this disease, events that lead to formation of malignant tumors are not fully clear. STAT3 is a major oncogenic transcription factor involved in the development and progression of a number of human tumors. However, the mechanisms that result in loss of control over STAT3 activity are not understood. Gene associated with Retinoid-Interferon-induced Mortality-19 (GRIM-19) is a tumor-suppressive protein identified using a genetic technique in the interferon/retinoid-induced cell death pathway. Here, we show that reduction in GRIM-19 protein levels occur in a number of primary human cervical cancers. Consequently, these tumors tend to express a high basal level of STAT3 and its downstream target genes. More importantly, using a surrogate model, we show that restoration of GRIM-19 levels reestablishes the control over STAT3-dependent gene expression and tumor growth in vivo. GRIM-19 suppressed the expression of tumor invasion- and angiogenesis-associated factors to limit tumor growth. This study identifies another major novel molecular pathway inactivated during the development of human cervical cancer. PMID:19642906

  20. 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 clothing or…

  1. 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

  2. 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.

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

    PubMed

    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

  4. 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

  5. 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…

  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. 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

  8. 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.

  9. Load forecasting by ANN

    SciTech Connect

    Highley, D.D.; Hilmes, T.J. )

    1993-07-01

    This article discusses the use and training of artificial neural networks (ANNs) for load forecasting. The topics of the article include a brief overview of neural networks, interest in ANNs, training of neural networks, a case study in load forecasting, and the potential for using an artificial neural network to perform short-term load forecasting.

  10. 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.

  11. 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.

  12. 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.

  13. Advanced chaos forecasting

    NASA Astrophysics Data System (ADS)

    Doerner, R.; Hübinger, B.; Martienssen, W.

    1994-07-01

    The exponential separation of initially adjacent trajectories restricts the predictability of deterministic chaotic motions. The predictability depends on the initial state from where the trajectory starts that shall be forecasted. By calculating the predictability simultaneously with the forecast, we are able to reject forecasts with low reliability immediately, thereby decreasing drastically the average forecast error. We test this scheme experimentally on Chua's circuit [Komuro, Tokunaga, Matsumoto, Chua, and Hotta, Int. J. Bifurc. Chaos 1, 139 (1991)], basing all calculations only on a time series of a single scalar variable.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Probabilistic river forecast methodology

    NASA Astrophysics Data System (ADS)

    Kelly, Karen Suzanne

    1997-09-01

    The National Weather Service (NWS) operates deterministic conceptual models to predict the hydrologic response of a river basin to precipitation. The output from these models are forecasted hydrographs (time series of the future river stage) at certain locations along a river. In order for the forecasts to be useful for optimal decision making, the uncertainty associated with them must be quantified. A methodology is developed for this purpose that (i) can be implemented with any deterministic hydrologic model, (ii) receives a probabilistic forecast of precipitation as input, (iii) quantifies all sources of uncertainty, (iv) operates in real-time and within computing constraints, and (v) produces probability distributions of future river stages. The Bayesian theory which supports the methodology involves transformation of a distribution of future precipitation into one of future river stage, and statistical characterization of the uncertainty in the hydrologic model. This is accomplished by decomposing total uncertainty into that associated with future precipitation and that associated with the hydrologic transformations. These are processed independently and then integrated into a predictive distribution which constitutes a probabilistic river stage forecast. A variety of models are presented for implementation of the methodology. In the most general model, a probability of exceedance associated with a given future hydrograph specified. In the simplest model, a probability of exceedance associated with a given future river stage is specified. In conjunction with the Ohio River Forecast Center of the NWS, the simplest model is used to demonstrate the feasibility of producing probabilistic river stage forecasts for a river basin located in headwaters. Previous efforts to quantify uncertainty in river forecasting have only considered selected sources of uncertainty, been specific to a particular hydrologic model, or have not obtained an entire probability

  19. 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.

  20. Forecasters of earthquakes

    NASA Astrophysics Data System (ADS)

    Maximova, Lyudmila

    1987-07-01

    For the first time Soviet scientists have set up a bioseismological proving ground which will stage a systematic extensive experiment of using birds, ants, mountain rodents including marmots, which can dig holes in the Earth's interior to a depth of 50 meters, for the purpose of earthquake forecasting. Biologists have accumulated extensive experimental data on the impact of various electromagnetic fields, including fields of weak intensity, on living organisms. As far as mammals are concerned, electromagnetic waves with frequencies close to the brain's biorhythms have the strongest effect. How these observations can be used to forecast earthquakes is discussed.

  1. US industrial battery forecast

    SciTech Connect

    Hollingsworth, V. III

    1996-09-01

    Last year was strong year for the US industrial battery market with growth in all segments. Sales of industrial batteries in North America grew 19.2% in 1995, exceeding last year`s forecasted growth rate of 11.6%. The results of the recently completed BCI Membership Survey forecast 1996 sales to be up 10.5%, and to continue to increase at a 10.4% compound annual rate through the year 2000. This year`s survey includes further detail on the stationary battery market with the inclusion of less than 25 Ampere-Hour batteries for the first time.

  2. Forecasting Credit Hours.

    ERIC Educational Resources Information Center

    Bivin, David; Rooney, Patrick Michael

    1999-01-01

    This study used Tobit analysis to estimate retention probabilities and credit hours at two universities. Tobit was judged as appropriate for this problem because it recognizes the lower bound of zero on credit hours and incorporates this bound into parameter estimates and forecasts. Models are estimated for credit hours in a single year and…

  3. Education Planning: Pupil Forecasting.

    ERIC Educational Resources Information Center

    Royal Inst. of Public Administration, Reading (England). Local Government Operational Research Unit.

    This computer-based system of enrollment projection predicts up to seven years ahead the number of school children of each age and sex who will be in school. The main distinguishing feature of the system is the ability to detect well in advance small changes in the geographical distribution of children. Forecasts are made for zones that will yield…

  4. 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…

  5. External Environmental Forecast.

    ERIC Educational Resources Information Center

    Lapin, Joel D.

    Representing current viewpoints of academics, futures experts, and social observers, this external environmental forecast presents projections and information of particular relevance to the future of Catonsville Community College. The following topics are examined: (1) population changes and implications for higher education; (2) state and local…

  6. Evolving forecasting classifications and applications in health forecasting

    PubMed Central

    Soyiri, Ireneous N; Reidpath, Daniel D

    2012-01-01

    Health forecasting forewarns the health community about future health situations and disease episodes so that health systems can better allocate resources and manage demand. The tools used for developing and measuring the accuracy and validity of health forecasts commonly are not defined although they are usually adapted forms of statistical procedures. This review identifies previous typologies used in classifying the forecasting methods commonly used in forecasting health conditions or situations. It then discusses the strengths and weaknesses of these methods and presents the choices available for measuring the accuracy of health-forecasting models, including a note on the discrepancies in the modes of validation. PMID:22615533

  7. How Grim is Pancreatic Cancer?

    PubMed Central

    Weledji, Elroy Patrick; Enoworock, George; Mokake, Martin; Sinju, Motaze

    2016-01-01

    Pancreatic ductal carcinoma continues to be the most lethal malignancy with rising incidence. It is the fourth most common cause of cancer death in the western world due to its low treatment success rate. In addition, because of its rapid growth and silent course, diagnosis is often only established in the advanced stages. As one of the most aggressive malignancies, the treatment of this disease is a great challenge to clinicians. This paper reviewed the natural history of pancreatic cancer, the current clinical practice and the future in pancreatic cancer management. PMID:27471581

  8. AIDS. Grim news for Asia.

    PubMed

    1992-12-01

    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. PMID:12285939

  9. How Grim is Pancreatic Cancer?

    PubMed

    Weledji, Elroy Patrick; Enoworock, George; Mokake, Martin; Sinju, Motaze

    2016-04-15

    Pancreatic ductal carcinoma continues to be the most lethal malignancy with rising incidence. It is the fourth most common cause of cancer death in the western world due to its low treatment success rate. In addition, because of its rapid growth and silent course, diagnosis is often only established in the advanced stages. As one of the most aggressive malignancies, the treatment of this disease is a great challenge to clinicians. This paper reviewed the natural history of pancreatic cancer, the current clinical practice and the future in pancreatic cancer management. PMID:27471581

  10. AIDS. Grim news for Asia.

    PubMed

    1992-12-01

    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.

  11. 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.

  12. The forecaster's added value

    NASA Astrophysics Data System (ADS)

    Turco, M.; Milelli, M.

    2009-09-01

    To the authors' knowledge there are relatively few studies that try to answer this topic: "Are humans able to add value to computer-generated forecasts and warnings ?". Moreover, the answers are not always positive. In particular some postprocessing method is competitive or superior to human forecast (see for instance Baars et al., 2005, Charba et al., 2002, Doswell C., 2003, Roebber et al., 1996, Sanders F., 1986). Within the alert system of ARPA Piemonte it is possible to study in an objective manner if the human forecaster is able to add value with respect to computer-generated forecasts. Every day the meteorology group of the Centro Funzionale of Regione Piemonte produces the HQPF (Human QPF) in terms of an areal average for each of the 13 regional warning areas, which have been created according to meteo-hydrological criteria. This allows the decision makers to produce an evaluation of the expected effects by comparing these HQPFs with predefined rainfall thresholds. Another important ingredient in this study is the very dense non-GTS network of rain gauges available that makes possible a high resolution verification. In this context the most useful verification approach is the measure of the QPF and HQPF skills by first converting precipitation expressed as continuous amounts into ‘‘exceedance'' categories (yes-no statements indicating whether precipitation equals or exceeds selected thresholds) and then computing the performances for each threshold. In particular in this work we compare the performances of the latest three years of QPF derived from two meteorological models COSMO-I7 (the Italian version of the COSMO Model, a mesoscale model developed in the framework of the COSMO Consortium) and IFS (the ECMWF global model) with the HQPF. In this analysis it is possible to introduce the hypothesis test developed by Hamill (1999), in which a confidence interval is calculated with the bootstrap method in order to establish the real difference between the

  13. 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.

  14. 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. PMID:26081307

  15. Technology 2005 : Reviews & Forecasts

    NASA Astrophysics Data System (ADS)

    Kimura, Ken

    Nine Technical Committees (TC's) of the Fundamentals and Materials Society of IEE Japan have contributed their Review & Forecast articles to the present. Special Issue of the IEEJ Transaction on Fundamentals and Materials. So you can survey the state-of-the-art of the 9 different technical fields with these articles. The series of reviews were submitted in reply to the request by experts in the respective fields.

  16. 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.

  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. 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.

  19. Global crop forecasting

    NASA Technical Reports Server (NTRS)

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

    1980-01-01

    The needs for and remote sensing means of global crop forecasting are discussed, and key results of the Large Area Crop Inventory Experiment (LACIE) are presented. Current crop production estimates provided by foreign countries are shown often to be inadequate, and the basic elements of crop production forecasts are reviewed. The LACIE project is introduced as a proof-of-concept experiment designed to assimilate remote sensing technology, monitor global wheat production, evaluate key technical problems, modify the technique accordingly and demonstrate the feasibility of a global agricultural monitoring system. The global meteorological data, sampling and aggregation techniques, Landsat data analysis procedures and yield forecast procedures used in the experiment are outlined. Accuracy assessment procedures employed to evaluate LACIE technology performance are presented, and improvements in system efficiency and capacity during the three years of operation are pointed out. Results of LACIE estimates of Soviet, U.S. and Canadian wheat production are presented which demonstrate the feasibility and accuracy of the remote-sensing approach for global food and fiber monitoring.

  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. 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

  2. Quantifying Regional Greenhouse Gas Emissions of HFC-134a From Atmospheric Measurements at the Trinidad Head (California), Cape Grim (Tasmania) and Mace Head (Ireland) Remote AGAGE Sites.

    NASA Astrophysics Data System (ADS)

    Manning, A. J.; Weiss, R. F.; Mühle, J.; Fraser, P. J.; Krummel, P. B.; O'Doherty, S.; Simmonds, P. G.

    2008-12-01

    Atmospheric measurement-based "top-down" approaches to emissions estimation provide a method of validating reported inventory-based "bottom-up" emissions assessments. At the AGAGE (Advanced Global Atmospheric Gases Experiment) measurement stations at Trinidad Head (THD) on the Northern California coast (41°N, 124°W), Cape Grim (CGM) on the northwestern tip of Tasmania (41°S, 145°E), and Mace Head (MHD) on the western coast of Ireland (53°N, 10°W), Medusa GC/MS and GC/ECD/FID instrumentation measure a wide range of trace gases in ambient air at high temporal resolution and high precision. Here, the western US, northwestern European and southern Australian emissions of the greenhouse gas (GHG) HFC-134a are estimated using the HFC-134a measurements, an atmospheric dispersion model (NAME), and an inversion methodology. NAME (Numerical Atmospheric dispersion Modelling Environment) is a Lagrangian atmospheric dispersion model that uses 3D meteorology from the UK Met Office numerical weather prediction model. Mid-latitude Northern and Southern Hemisphere baseline concentrations of HFC-134a are determined using NAME and statistical post- processing of the observations, and this baseline is used to generate a time series of "polluted" (above baseline) observations. In this application NAME is run backwards in time for ten days for each 3-hour interval in 1995-2008 for MHD, 2003-2008 for CGM and 2005-2008 for THD releasing thousands of model particles at each observing site. A map is then produced estimating all of the surface (0-100m) contributions within ten days of travel arriving at each site during each interval. The resulting matrix describes the dilution in concentration that occurs from a unit release from each grid as it travels to the measurement site. Iterative inversion modeling is then carried out to generate an emission estimate that provides the best statistical match between the modeled time series and the observations. Uncertainty in the emission

  3. Hydrological Forecasting Practices in Brazil

    NASA Astrophysics Data System (ADS)

    Fan, Fernando; Paiva, Rodrigo; Collischonn, Walter; Ramos, Maria-Helena

    2016-04-01

    This work brings a review on current hydrological and flood forecasting practices in Brazil, including the main forecasts applications, the different kinds of techniques that are currently being employed and the institutions involved on forecasts generation. A brief overview of Brazil is provided, including aspects related to its geography, climate, hydrology and flood hazards. A general discussion about the Brazilian practices on hydrological short and medium range forecasting is presented. Detailed examples of some hydrological forecasting systems that are operational or in a research/pre-operational phase using the large scale hydrological model MGB-IPH are also presented. Finally, some suggestions are given about how the forecasting practices in Brazil can be understood nowadays, and what are the perspectives for the future.

  4. 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.

  5. 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.

  6. 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).

  7. 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.

  8. 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.

  9. 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.

  10. 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

  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. 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)

  13. 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.

  14. 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.

  15. Reliable probabilistic forecasts from an ensemble reservoir inflow forecasting system

    NASA Astrophysics Data System (ADS)

    Bourdin, Dominique R.; Nipen, Thomas N.; Stull, Roland B.

    2014-04-01

    This paper describes a probabilistic reservoir inflow forecasting system that explicitly attempts to sample from major sources of uncertainty in the modeling chain. Uncertainty in hydrologic forecasts arises due to errors in the hydrologic models themselves, their parameterizations, and in the initial and boundary conditions (e.g., meteorological observations or forecasts) used to drive the forecasts. The Member-to-Member (M2M) ensemble presented herein uses individual members of a numerical weather model ensemble to drive two different distributed hydrologic models, each of which is calibrated using three different objective functions. An ensemble of deterministic hydrologic states is generated by spinning up the daily simulated state using each model and parameterization. To produce probabilistic forecasts, uncertainty models are used to fit probability distribution functions (PDF) to the bias-corrected ensemble. The parameters of the distribution are estimated based on statistical properties of the ensemble and past verifying observations. The uncertainty model is able to produce reliable probability forecasts by matching the shape of the PDF to the shape of the empirical distribution of forecast errors. This shape is found to vary seasonally in the case-study watershed. We present an "intelligent" adaptation to a Probability Integral Transform (PIT)-based probability calibration scheme that relabels raw cumulative probabilities into calibrated cumulative probabilities based on recent past forecast performance. As expected, the intelligent scheme, which applies calibration corrections only when probability forecasts are deemed sufficiently unreliable, improves reliability without the inflation of ignorance exhibited in certain cases by the original PIT-based scheme.

  16. 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.

  17. Atmospheric composition forecasting in Europe

    NASA Astrophysics Data System (ADS)

    Menut, L.; Bessagnet, B.

    2010-01-01

    The atmospheric composition is a societal issue and, following new European directives, its forecast is now recommended to quantify the air quality. It concerns both gaseous and particles species, identified as potential problems for health. In Europe, numerical systems providing daily air quality forecasts are numerous and, mostly, operated by universities. Following recent European research projects (GEMS, PROMOTE), an organization of the air quality forecast is currently under development. But for the moment, many platforms exist, each of them with strengths and weaknesses. This overview paper presents all existing systems in Europe and try to identify the main remaining gaps in the air quality forecast knowledge. As modeling systems are now able to reasonably forecast gaseous species, and in a lesser extent aerosols, the future directions would concern the use of these systems with ensemble approaches and satellite data assimilation. If numerous improvements were recently done on emissions and chemistry knowledge, improvements are still needed especially concerning meteorology, which remains a weak point of forecast systems. Future directions will also concern the use of these forecast tools to better understand and quantify the air pollution impact on health.

  18. Characterizing the uncertainty in river stage forecasts conditional on point forecast values

    NASA Astrophysics Data System (ADS)

    Yan, Jun; Liao, Gong-Yi; Gebremichael, Mekonnen; Shedd, Robert; Vallee, David R.

    2012-12-01

    Uncertainty information about river level forecast is as important as the forecast itself for forecast users. This paper presents a flexible, statistical approach that processes deterministic forecasts into probabilistic forecasts. The model is a smoothly changing conditional distribution of river stage given point forecast and other information available, such as lagged river level at the time of forecasting. The parametric distribution is a four-parameter skewt distribution, with each parameter modeled as a smooth function of the point forecast and the 1 day ago observed river level. The model was applied to 9 years of daily 6 h lead forecasts and 24 h lead forecasts in the warm season and their matching observations at the Plymouth station on the Pemigewasset River in New Hampshire. For each point forecast, the conditional distribution and resulting prediction intervals provide uncertainty information that are potentially very important to forecast users and algorithm developers in decision making and improvement of forecast quality.

  19. 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.

  20. 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)

  1. Latin American Battery Forecast Report

    SciTech Connect

    Malacon, S.

    1995-12-31

    A forecast of battery production in Latin America is described. The economic influence and political difficulties which have influenced the market are discussed. Data is presented for original equipment shipments and replacement batteries.

  2. 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.

  3. 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…

  4. 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.

  5. 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.

  6. 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.

  7. HESS Opinions "Forecaster priorities for improving probabilistic flood forecasts"

    NASA Astrophysics Data System (ADS)

    Wetterhall, F.; Pappenberger, F.; Alfieri, L.; Cloke, H. L.; Thielen-del Pozo, J.; Balabanova, S.; Daňhelka, J.; Vogelbacher, A.; Salamon, P.; Carrasco, I.; Cabrera-Tordera, A. J.; Corzo-Toscano, M.; Garcia-Padilla, M.; Garcia-Sanchez, R. J.; Ardilouze, C.; Jurela, S.; Terek, B.; Csik, A.; Casey, J.; Stankūnavičius, G.; Ceres, V.; Sprokkereef, E.; Stam, J.; Anghel, E.; Vladikovic, D.; Alionte Eklund, C.; Hjerdt, N.; Djerv, H.; Holmberg, F.; Nilsson, J.; Nyström, K.; Sušnik, M.; Hazlinger, M.; Holubecka, M.

    2013-11-01

    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.

  8. Fields, Flares, And Forecasts

    NASA Astrophysics Data System (ADS)

    Boucheron, L.; Al-Ghraibah, Amani; McAteer, J.; Cao, H.; Jackiewicz, J.; McNamara, B.; Voelz, D.; Calabro, B.; DeGrave, K.; Kirk, M.; Madadi, A.; Petsov, A.; Taylor, G.

    2011-05-01

    Solar active regions are the source of many energetic and geo-effective events such as solar flares and coronal mass ejections (CMEs). Understanding how these complex source regions evolve and produce these events is of fundamental importance, not only to solar physics, but also to the demands of space weather forecasting. We propose to investigate the physical properties of active region magnetic fields using fractal-, gradient-, neutral line-, emerging flux-, wavelet- and general image-based techniques, and to correlate them to solar activity. The combination of these projects with solarmonitor.org and the international Max Millenium Campaign presents an opportunity for accurate and timely flare predictions for the first time. Many studies have attempted to relate solar flares to their concomitant magnetic field distributions. However, a consistent, causal relationship between the magnetic field on the photosphere and the production of solar flares is unknown. Often the local properties of the active region magnetic field - critical in many theories of activity - are lost in the global definition of their diagnostics, in effect smoothing out variations that occur on small spatial scales. Mindful of this, our overall goal is to create measures that are sensitive to both the global and the small-scale nature of energy storage and release in the solar atmosphere in order to study solar flare prediction. This set of active region characteristics will be automatically explored for discriminating features through the use of feature selection methods. Such methods search a feature space while optimizing a criterion - the prediction of a flare in this case. The large size of the datasets used in this project make it well suited for an exploration of a large feature space. This work is funded through a New Mexico State University Interdisciplinary Research Grant.

  9. 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.

  10. 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.

  11. CME Ensemble Forecasting - A Primer

    NASA Astrophysics Data System (ADS)

    Pizzo, V. J.; de Koning, C. A.; Cash, M. D.; Millward, G. H.; Biesecker, D. A.; Codrescu, M.; Puga, L.; Odstrcil, D.

    2014-12-01

    SWPC has been evaluating various approaches for ensemble forecasting of Earth-directed CMEs. We have developed the software infrastructure needed to support broad-ranging CME ensemble modeling, including composing, interpreting, and making intelligent use of ensemble simulations. The first step is to determine whether the physics of the interplanetary propagation of CMEs is better described as chaotic (like terrestrial weather) or deterministic (as in tsunami propagation). This is important, since different ensemble strategies are to be pursued under the two scenarios. We present the findings of a comprehensive study of CME ensembles in uniform and structured backgrounds that reveals systematic relationships between input cone parameters and ambient flow states and resulting transit times and velocity/density amplitudes at Earth. These results clearly indicate that the propagation of single CMEs to 1 AU is a deterministic process. Thus, the accuracy with which one can forecast the gross properties (such as arrival time) of CMEs at 1 AU is determined primarily by the accuracy of the inputs. This is no tautology - it means specifically that efforts to improve forecast accuracy should focus upon obtaining better inputs, as opposed to developing better propagation models. In a companion paper (deKoning et al., this conference), we compare in situ solar wind data with forecast events in the SWPC operational archive to show how the qualitative and quantitative findings presented here are entirely consistent with the observations and may lead to improved forecasts of arrival time at Earth.

  12. 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.

  13. 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.

  14. Rapid growth of hydrofluorocarbon 134a and hydrochlorofluorocarbons 141b, 142b, and 22 from Advanced Global Atmospheric Gases Experiment (AGAGE) observations at Cape Grim, Tasmania, and Mace Head, Ireland

    NASA Astrophysics Data System (ADS)

    O'Doherty, S.; Cunnold, D. M.; Manning, A.; Miller, B. R.; Wang, R. H. J.; Krummel, P. B.; Fraser, P. J.; Simmonds, P. G.; McCulloch, A.; Weiss, R. F.; Salameh, P.; Porter, L. W.; Prinn, R. G.; Huang, J.; Sturrock, G.; Ryall, D.; Derwent, R. G.; Montzka, S. A.

    2004-03-01

    An update of in situ Advanced Global Atmospheric Gases Experiment (AGAGE) hydrofluorocarbon (HFC)/hydrochlorofluorocarbon (HCFC) measurements made at Mace Head, Ireland, and Cape Grim, Tasmania, from 1998 to 2002 are reported. HCFC-142b, HCFC-141b, HCFC-22 and HFC-134a show continued rapid growth in the atmosphere at mean rates of 1.1, 1.6, 6.0, and 3.4 ppt/year, respectively. Emissions inferred from measurements are compared to recent estimates from consumption data. Minor updates to the industry estimates of emissions are reported together with a discussion of how to best determine OH concentrations from these trace gas measurements. In addition, AGAGE measurements and derived emissions are compared to those deduced from NOAA-Climate Monitoring and Diagnostics Laboratory flask measurements (which are mostly made at different locations). European emission estimates obtained from Mace Head pollution events using the Nuclear Accident Model (NAME) dispersion model and the best fit algorithm (known as simulated annealing) are presented as 3-year rolling average emissions over Europe for the period 1999-2001. Finally, the measurements of HCFC-141b, HCFC-142b, and HCFC-22 discussed in this paper have been combined with the Atmospheric Lifetime Experiment (ALE)/Global Atmospheric Gases Experiment (GAGE)/AGAGE measurements of CFC-11, CFC-12, CFC-113, CCl4, and CH3CCl3 to produce the evolution of tropospheric chlorine loading.

  15. 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.

  16. 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.

  17. 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.

  18. ALFA: Automated load forecasting assistant

    SciTech Connect

    Jabbour, K.; Riveros, J.F.V.; Landsbergen, D.; Meyer, W.

    1988-08-01

    ALFA, an expert system for forecasting short term demand for electricity is presented. ALFA is in operation at the new Energy Management System center at Niagara Mohawk Power Corporation in Upstate New York, generating the real time hourly load forecasts up to 48 hours in advance. ALFA uses an extensive 10 year historical data base of hourly observations of 12 weather variables and load, and a rule base that takes into account daily, weekly, and seasonal variations of load, as well as holidays, special events, and load growth. A satellite interface for the real-time acquisition of weather data, and the machine-operator interface are also discussed.

  19. 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.

  20. 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.

  1. 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

  2. Accuracy of forecasts in strategic intelligence

    PubMed Central

    Mandel, David R.; Barnes, Alan

    2014-01-01

    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. PMID:25024176

  3. Error growth in operational ECMWF forecasts

    NASA Technical Reports Server (NTRS)

    Kalnay, E.; Dalcher, A.

    1985-01-01

    A parameterization scheme used at the European Centre for Medium Range Forecasting to model the average growth of the difference between forecasts on consecutive days was extended by including the effect of error growth on forecast model deficiencies. Error was defined as the difference between the forecast and analysis fields during the verification time. Systematic and random errors were considered separately in calculating the error variance for a 10 day operational forecast. A good fit was obtained with measured forecast errors and a satisfactory trend was achieved in the difference between forecasts. Fitting six parameters to forecast errors and differences that were performed separately for each wavenumber revealed that the error growth rate grew with wavenumber. The saturation error decreased with the total wavenumber and the limit of predictability, i.e., when error variance reaches 95 percent of saturation, decreased monotonically with the total wavenumber.

  4. 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.

  5. Forecasting for energy and chemical decision analysis

    SciTech Connect

    Cazalet, E.G.

    1984-08-01

    This paper focuses on uncertainty and bias in forecasts used for major energy and chemical investment decisions. Probability methods for characterizing uncertainty in the forecast are reviewed. Sources of forecasting bias are classified based on the results of relevant psychology research. Examples are drawn from the energy and chemical industry to illustrate the value of explicit characterization of uncertainty and reduction of bias in forecasts.

  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. An Experiment in Probabilistic Forecasting.

    ERIC Educational Resources Information Center

    Brown, Thomas A.

    Students were asked to make forecasts of fourteen quantities where true values would not become known for five or six months. The quantities were selected to be typical of the subjects which would be of interest to a decisionmaker in business or government, and included GNP, consumer prices, draft calls, deaths in South Vietnam, and election…

  8. 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.

  9. Forecasting phenology under global warming.

    PubMed

    Ibáñez, Inés; Primack, Richard B; Miller-Rushing, Abraham J; Ellwood, Elizabeth; Higuchi, Hiroyoshi; Lee, Sang Don; Kobori, Hiromi; Silander, John A

    2010-10-12

    As a consequence of warming temperatures around the world, spring and autumn phenologies have been shifting, with corresponding changes in the length of the growing season. Our understanding of the spatial and interspecific variation of these changes, however, is limited. Not all species are responding similarly, and there is significant spatial variation in responses even within species. This spatial and interspecific variation complicates efforts to predict phenological responses to ongoing climate change, but must be incorporated in order to build reliable forecasts. Here, we use a long-term dataset (1953-2005) of plant phenological events in spring (flowering and leaf out) and autumn (leaf colouring and leaf fall) throughout Japan and South Korea to build forecasts that account for these sources of variability. Specifically, we used hierarchical models to incorporate the spatial variability in phenological responses to temperature to then forecast species' overall and site-specific responses to global warming. We found that for most species, spring phenology is advancing and autumn phenology is getting later, with the timing of events changing more quickly in autumn compared with the spring. Temporal trends and phenological responses to temperature in East Asia contrasted with results from comparable studies in Europe, where spring events are changing more rapidly than are autumn events. Our results emphasize the need to study multiple species at many sites to understand and forecast regional changes in phenology. PMID:20819816

  10. 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…

  11. Premier Forecasting Center Avoids Ax

    NASA Astrophysics Data System (ADS)

    Simpson, Sarah

    2004-03-01

    Last fall, the U.S. Senate proposed eliminating all 2004 funding for NOAA's Space Environment Center (SEC), but fortunately for the world's premier space weather forecasting center and its myriad customers, the Senate did not get its way. When the full Congress passed the final budget on 22 January, the center's budget for the year was at least restored-at least partially.

  12. Wavelet-based Evapotranspiration Forecasts

    NASA Astrophysics Data System (ADS)

    Bachour, R.; Maslova, I.; Ticlavilca, A. M.; McKee, M.; Walker, W.

    2012-12-01

    Providing a reliable short-term forecast of evapotranspiration (ET) could be a valuable element for improving the efficiency of irrigation water delivery systems. In the last decade, wavelet transform has become a useful technique for analyzing the frequency domain of hydrological time series. This study shows how wavelet transform can be used to access statistical properties of evapotranspiration. The objective of the research reported here is to use wavelet-based techniques to forecast ET up to 16 days ahead, which corresponds to the LANDSAT 7 overpass cycle. The properties of the ET time series, both physical and statistical, are examined in the time and frequency domains. We use the information about the energy decomposition in the wavelet domain to extract meaningful components that are used as inputs for ET forecasting models. Seasonal autoregressive integrated moving average (SARIMA) and multivariate relevance vector machine (MVRVM) models are coupled with the wavelet-based multiresolution analysis (MRA) results and used to generate short-term ET forecasts. Accuracy of the models is estimated and model robustness is evaluated using the bootstrap approach.

  13. 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.

  14. Volcanic forcing in decadal forecasts

    NASA Astrophysics Data System (ADS)

    Ménégoz, Martin; Doblas-Reyes, Francisco; Guemas, Virginie; Asif, Muhammad; Prodhomme, chloe

    2016-04-01

    Volcanic eruptions can significantly impact the climate system, by injecting large amounts of particles into the stratosphere. By reflecting backward the solar radiation, these particles cool the troposphere, and by absorbing the longwave radiation, they warm the stratosphere. As a consequence of this radiative forcing, the global mean surface temperature can decrease by several tenths of degrees. However, large eruptions are also associated to a complex dynamical response of the climate system that is particularly tricky do understand regarding the low number of available observations. Observations seem to show an increase of the positive phases of the Northern Atlantic Oscillation (NAO) the two winters following large eruptions, associated to positive temperature anomalies over the Eurasian continent. The summers following large eruptions are generally particularly cold, especially over the continents of the Northern Hemisphere. Overall, it is really challenging to forecast the climate response to large eruptions, as it is both modulated by, and superimposed to the climate background conditions, largely driven themselves by internal variability at seasonal to decadal scales. This work describes the additional skill of a forecast system used for seasonal and decadal predictions when it includes observed volcanic forcing over the last decades. An idealized volcanic forcing that could be used for real-time forecasts is also evaluated. This work consists in a base for forecasts that will be performed in the context of the next large volcanic eruption.

  15. 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.

  16. 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).

  17. 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.

  18. 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.

  19. 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)

  20. 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…

  1. 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…

  2. 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

  3. The COMESEP SEP forecast tool

    NASA Astrophysics Data System (ADS)

    Dierckxsens, Mark; Tziotziou, Kostas; Dalla, Silvia; Patsou, Ioanna; Marsh, Mike; Crosby, Norma; Malandraki, Olga; Lygeros, Nik

    2014-05-01

    The FP7 COMESEP (COronal Mass Ejections and Solar Energetic Particles: forecasting the space weather impact) project developed tools for forecasting geomagnetic storms and solar energetic particle (SEP) radiation storms. Here we present the SEP forecast tool which provides a prediction of the probability for an SEP event to occur near Earth following the real-time observation of an X-ray flare, and estimates the most likely impact if such an event would occur. The tool has been operational on the COMESEP alert system (http://www.comesep.eu/alert) since November 2013. Alerts are provided for proton storms with E>10 MeV and E>60 MeV in the form of a risk level, combining the probability and expected impact. The predictions are based on a statistical analysis of SEP events and their parent solar activity during Solar Cycle 23. The input parameters are the flare intensity and longitude location, as well as the CME speed and width, if an observed CME can be associated with the flare. This information is also received through the COMESEP system. Alerts are based on the available information when triggered and are subsequently updated if more information becomes available. The forecast for the probability, the impact and risk level are evaluated on events from solar cycles 22 and 24. The effect of including flare location and CME parameters is also studied. The performance of the SEP forecast tool within the COMESEP alert system will be described. This work has received funding from the European Commission FP7 Project COMESEP (263252)

  4. 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)

  5. On the reliability of seasonal climate forecasts.

    PubMed

    Weisheimer, A; Palmer, T N

    2014-07-01

    Seasonal climate forecasts are being used increasingly across a range of application sectors. A recent UK governmental report asked: how good are seasonal forecasts on a scale of 1-5 (where 5 is very good), and how good can we expect them to be in 30 years time? Seasonal forecasts are made from ensembles of integrations of numerical models of climate. We argue that 'goodness' should be assessed first and foremost in terms of the probabilistic reliability of these ensemble-based forecasts; reliable inputs are essential for any forecast-based decision-making. We propose that a '5' should be reserved for systems that are not only reliable overall, but where, in particular, small ensemble spread is a reliable indicator of low ensemble forecast error. We study the reliability of regional temperature and precipitation forecasts of the current operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts, universally regarded as one of the world-leading operational institutes producing seasonal climate forecasts. A wide range of 'goodness' rankings, depending on region and variable (with summer forecasts of rainfall over Northern Europe performing exceptionally poorly) is found. Finally, we discuss the prospects of reaching '5' across all regions and variables in 30 years time.

  6. Statistical calibration of seasonal ensemble streamflow forecasts

    NASA Astrophysics Data System (ADS)

    Wood, A. W.; Wiley, M.; Nijssen, B.

    2008-12-01

    Model-based streamflow forecast ensembles routinely exhibit errors due to input forecast uncertainty, initial condition uncertainty and hydrologic modeling error, and such errors can undermine the suitability of raw model forecast output for use in follow-on applications such as reservoir management. This presentation evaluates the use of quantile regression for modeling and correcting streamflow prediction errors at seasonal lead times. Quantile regression has been used rarely in the hydrologic forecasting area, yet its insensitivity to outliers and avoidance of parametric assumptions about forecast errors makes it suitable for representing quantiles of datasets (such as streamflow) that often have skewed or otherwise irregular distributions. For illustration, a local linear quantile regression framework is applied to seasonal streamflow hindcasts in the Pacific Northwest and elsewhere in the western US, and found to reduce forecast bias and improve reliability, albeit with a slight loss of forecast resolution.

  7. Univariate time series forecasting algorithm validation

    NASA Astrophysics Data System (ADS)

    Ismail, Suzilah; Zakaria, Rohaiza; Muda, Tuan Zalizam Tuan

    2014-12-01

    Forecasting is a complex process which requires expert tacit knowledge in producing accurate forecast values. This complexity contributes to the gaps between end users and expert. Automating this process by using algorithm can act as a bridge between them. Algorithm is a well-defined rule for solving a problem. In this study a univariate time series forecasting algorithm was developed in JAVA and validated using SPSS and Excel. Two set of simulated data (yearly and non-yearly); several univariate forecasting techniques (i.e. Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) and recent forecasting process (such as data partition, several error measures, recursive evaluation and etc.) were employed. Successfully, the results of the algorithm tally with the results of SPSS and Excel. This algorithm will not just benefit forecaster but also end users that lacking in depth knowledge of forecasting process.

  8. Climate Time Series Analysis and Forecasting

    NASA Astrophysics Data System (ADS)

    Young, P. C.; Fildes, R.

    2009-04-01

    This paper will discuss various aspects of climate time series data analysis, modelling and forecasting being carried out at Lancaster. This will include state-dependent parameter, nonlinear, stochastic modelling of globally averaged atmospheric carbon dioxide; the computation of emission strategies based on modern control theory; and extrapolative time series benchmark forecasts of annual average temperature, both global and local. The key to the forecasting evaluation will be the iterative estimation of forecast error based on rolling origin comparisons, as recommended in the forecasting research literature. The presentation will conclude with with a comparison of the time series forecasts with forecasts produced from global circulation models and a discussion of the implications for climate modelling research.

  9. Using Climate Forecasts for Drought Management

    NASA Astrophysics Data System (ADS)

    Steinemann, Anne C.

    2006-10-01

    Drought hazards, and the ability to mitigate them with advance warning, offer potentially valuable applications of climate forecast products. Yet the value is often untapped, owing to the gap between climate science and societal decisions. This study bridged that gap; it determined forecast needs among water managers, translated forecasts to meet those needs, and shaped drought decision making to take advantage of forecasts. NOAA Climate Prediction Center (CPC) seasonal precipitation outlooks were converted into a forecast precipitation index (FPI) tailored for water managers in the southeastern United States. The FPI expresses forecasts as a departure from the climatological normal and is consistent with other drought indicators. Evaluations of CPC seasonal forecasts issued during 1995 2000 demonstrated positive skill for drought seasons in the Southeast. In addition, using evaluation criteria of water managers, 88% of forecasts for drought seasons would have appropriately prompted drought responses. Encouraged by these evaluations, and the understandability of the FPI, state water managers started using the forecasts in 2001 for deciding whether to pay farmers to suspend irrigation. Economic benefits of this forecast information were estimated at $100 $350 million in a state-declared drought year (2001, 2002) and $5 $30 million in the other years (2003, 2004). This study provides four main contributions: 1) an investigation of the needs and potential benefits of seasonal forecast information for water management, 2) a method for translating the CPC forecasts into a format needed by water managers, 3) the integration of forecast information into agency decision making, and 4) the economic valuation of that forecast information.

  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. An artificial neutral network hourly temperature forecaster with applications in load forecasting

    SciTech Connect

    Khotanzad, A.; Davis, M.H.; Abaye, A.; Maratukulam, D.J.

    1996-05-01

    Many short term load forecasting techniques use forecast hourly temperatures in generating a load forecast. Some utility companies, however, do not have access to a weather service that provides these forecasts. To fill this need, a temperature forecaster, based on artificial neural networks, has been developed that predicts hourly temperatures up to seven days in the future. The prediction is based on forecast daily high and low temperatures and other information that would be readily available to any utility. The forecaster has been evaluated using data from eight utilities in the US. The mean absolute error of one day ahead forecasts for these utilities is 1.48{degree}F. The forecaster is implemented at several electric utilities and is being used in production environments.

  12. Errors in Moral Forecasting: Perceptions of Affect Shape the Gap Between Moral Behaviors and Moral Forecasts.

    PubMed

    Teper, Rimma; Tullett, Alexa M; Page-Gould, Elizabeth; Inzlicht, Michael

    2015-07-01

    Research in moral decision making has shown that there may not be a one-to-one relationship between peoples' moral forecasts and behaviors. Although past work suggests that physiological arousal may account for part of the behavior-forecasting discrepancy, whether or not perceptions of affect play an important determinant remains unclear. Here, we investigate whether this discrepancy may arise because people fail to anticipate how they will feel in morally significant situations. In Study 1, forecasters predicted cheating significantly more on a test than participants in a behavior condition actually cheated. Importantly, forecasters who received false somatic feedback, indicative of high arousal, produced forecasts that aligned more closely with behaviors. In Study 2, forecasters who misattributed their arousal to an extraneous source forecasted cheating significantly more. In Study 3, higher dispositional emotional awareness was related to less forecasted cheating. These findings suggest that perceptions of affect play a key role in the behavior-forecasting dissociation.

  13. Probabilistic Downscaling Methods for Developing Categorical Streamflow Forecasts using Climate Forecasts

    NASA Astrophysics Data System (ADS)

    Mazrooei, A. H.

    2015-12-01

    Statistical information from climate forecast ensembles can be utilized in developing probabilistic streamflow forecasts for providing the uncertainty in streamflow forecast potential. This study examines the use of Multinomial Logistic Regression (MLR) in downscaling the probabilistic information from the large-scale climate forecast ensembles into a point-scale categorical streamflow forecasts. Performance of MLR in developing one-month lead categorical forecasts is evaluated for various river basins over the US Sunbelt. Comparison of MLR with the estimated categorical forecasts from Principle Component Regression (PCR) method under both cross-validation and split-sampling validation reveals that in general the forecasts from MLR has better performance and lower Rank Probability Score (RPS) compared to the PCR forecasts. In addition, MLR performs better than PCR method particularly in arid basins that exhibit strong skewness in seasonal flows with records of distinct dry years. A theoretical underpinning for this improved performance of MLR is also provided.

  14. Post Processing Numerical Weather Prediction Model Rainfall Forecasts for Use in Ensemble Streamflow Forecasting in Australia

    NASA Astrophysics Data System (ADS)

    Shrestha, D. L.; Robertson, D.; Bennett, J.; Ward, P.; Wang, Q. J.

    2012-12-01

    Through the water information research and development alliance (WIRADA) project, CSIRO is conducting research to improve flood and short-term streamflow forecasting services delivered by the Australian Bureau of Meteorology. WIRADA aims to build and test systems to generate ensemble flood and short-term streamflow forecasts with lead times of up to 10 days by integrating rainfall forecasts from Numerical Weather Prediction (NWP) models and hydrological modelling. Here we present an overview of the latest progress towards developing this system. Rainfall during the forecast period is a major source of uncertainty in streamflow forecasting. Ensemble rainfall forecasts are used in streamflow forecasting to characterise the rainfall uncertainty. In Australia, NWP models provide forecasts of rainfall and other weather conditions for lead times of up to 10 days. However, rainfall forecasts from Australian NWP models are deterministic and often contain systematic errors. We use a simplified Bayesian joint probability (BJP) method to post-process rainfall forecasts from the latest generation of Australian NWP models. The BJP method generates reliable and skilful ensemble rainfall forecasts. The post-processed rainfall ensembles are then used to force a semi-distributed conceptual rainfall runoff model to produce ensemble streamflow forecasts. The performance of the ensemble streamflow forecasts is evaluated on a number of Australian catchments and the benefits of using post processed rainfall forecasts are demonstrated.

  15. 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).

  16. 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.

  17. Communicating uncertainty in hydrological forecasts: mission impossible?

    NASA Astrophysics Data System (ADS)

    Ramos, Maria-Helena; Mathevet, Thibault; Thielen, Jutta; Pappenberger, Florian

    2010-05-01

    Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted

  18. 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.

  19. 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

  20. 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.

  1. Seasonal hydrological ensemble forecasts over Europe

    NASA Astrophysics Data System (ADS)

    Arnal, Louise; Wetterhall, Fredrik; Pappenberger, Florian

    2015-04-01

    Seasonal forecasts have an important socio-economic value in hydro-meteorological forecasting. The applications are for example hydropower management, spring flood prediction and water resources management. The latter includes prediction of low flows, primordial for navigation, water quality assessment, droughts and agricultural water needs. Traditionally, seasonal hydrological forecasts are done using the observed discharge from previous years, so called Ensemble Streamflow Prediction (ESP). With the recent increasing development of seasonal meteorological forecasts, the incentive for developing and improving seasonal hydrological forecasts is great. In this study, a seasonal hydrological forecast, driven by the ECMWF's System 4 (SEA), was compared with an ESP of modelled discharge using observations. The hydrological model used for both forecasts was the LISFLOOD model, run over a European domain with a spatial resolution of 5 km. The forecasts were produced from 1990 until the present time, with a daily time step. They were issued once a month with a lead time of seven months. The SEA forecasts are constituted of 15 ensemble members, extended to 51 members every three months. The ESP forecasts comprise 20 ensembles and served as a benchmark for this comparative study. The forecast systems were compared using a diverse set of verification metrics, such as continuous ranked probability scores, ROC curves, anomaly correlation coefficients and Nash-Sutcliffe efficiency coefficients. These metrics were computed over several time-scales, ranging from a weekly to a six-months basis, for each season. The evaluation enabled the investigation of several aspects of seasonal forecasting, such as limits of predictability, timing of high and low flows, as well as exceedance of percentiles. The analysis aimed at exploring the spatial distribution and timely evolution of the limits of predictability.

  2. [Application of phenological pattern recognition in ecological dynamic forecasting].

    PubMed

    Pei, Tiefan; Jin, Changiie

    2005-09-01

    This paper described the principles, methods, and procedures of ecological dynamic forecasting by the automation techniques of pattern recognition and mathematical logic judgment on the basis of phenological data and model output maps from T42L9 numerical weather prediction model. This new forecasting method proposed on the basis of modern meteorology and automation techniques enables the classic phenology to apply to a new field ecological forecasting. It enables phenological forecasting to develop from single-station forecasting stage to regional forecasting stage, which is greatly corresponded to the development stage from single station forecasting stage to synoptic stage in weather forecasting, and enables agro-meteorological forecasting to develop from qualitative and statistical forecasting stage to ecological dynamic forecasting stage. With this new qualitative forecasting method, both the predicted objective and predictors are of considerable bio-physical interests. The ecological dynamic forecasting method could be applied to crop sowing, crop growth, irrigation and fertilization, and diseases and pests

  3. Empirical seasonal forecasts of the NAO

    NASA Astrophysics Data System (ADS)

    Sanchezgomez, E.; Ortizbevia, M.

    2003-04-01

    We present here seasonal forecasts of the North Atlantic Oscillation (NAO) issued from ocean predictors with an empirical procedure. The Singular Values Decomposition (SVD) of the cross-correlation matrix between predictor and predictand fields at the lag used for the forecast lead is at the core of the empirical model. The main predictor field are sea surface temperature anomalies, although sea ice cover anomalies are also used. Forecasts are issued in probabilistic form. The model is an improvement over a previous version (1), where Sea Level Pressure Anomalies were first forecast, and the NAO Index built from this forecast field. Both correlation skill between forecast and observed field, and number of forecasts that hit the correct NAO sign, are used to assess the forecast performance , usually above those values found in the case of forecasts issued assuming persistence. For certain seasons and/or leads, values of the skill are above the .7 usefulness treshold. References (1) SanchezGomez, E. and Ortiz Bevia M., 2002, Estimacion de la evolucion pluviometrica de la Espana Seca atendiendo a diversos pronosticos empiricos de la NAO, in 'El Agua y el Clima', Publicaciones de la AEC, Serie A, N 3, pp 63-73, Palma de Mallorca, Spain

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. 1992 five year battery forecast

    SciTech Connect

    Amistadi, D.

    1992-12-01

    Five-year trends for automotive and industrial batteries are projected. Topic covered include: SLI shipments; lead consumption; automotive batteries (5-year annual growth rates); industrial batteries (standby power and motive power); estimated average battery life by area/country for 1989; US motor vehicle registrations; replacement battery shipments; potential lead consumption in electric vehicles; BCI recycling rates for lead-acid batteries; US average car/light truck battery life; channels of distribution; replacement battery inventory end July; 2nd US battery shipment forecast.

  15. 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.

  16. Uncertainty forecasts improve weather-related decisions and attenuate the effects of forecast error.

    PubMed

    Joslyn, Susan L; LeClerc, Jared E

    2012-03-01

    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 warning system is used. The work reported here tested the relative benefits of several forecast formats, comparing decisions made with and without uncertainty forecasts. In three experiments, participants assumed the role of a manager of a road maintenance company in charge of deciding whether to pay to salt the roads and avoid a potential penalty associated with icy conditions. Participants used overnight low temperature forecasts accompanied in some conditions by uncertainty estimates and in others by decision advice comparable to categorical warnings. Results suggested that uncertainty information improved decision quality overall and increased trust in the forecast. Participants with uncertainty forecasts took appropriate precautionary action and withheld unnecessary action more often than did participants using deterministic forecasts. When error in the forecast increased, participants with conventional forecasts were reluctant to act. However, this effect was attenuated by uncertainty forecasts. Providing categorical decision advice alone did not improve decisions. However, combining decision advice with uncertainty estimates resulted in the best performance overall. The results reported here have important implications for the development of forecast formats to increase compliance with severe weather warnings as well as other domains in which one must act in the face of uncertainty.

  17. Perturbation of convection-permitting NWP forecasts for flash-flood ensemble forecasting

    NASA Astrophysics Data System (ADS)

    Vincendon, B.; Ducrocq, V.; Nuissier, O.; Vié, B.

    2011-05-01

    Mediterranean intense weather events often lead to devastating flash-floods. Extending the forecasting lead times further than the watershed response times, implies the use of numerical weather prediction (NWP) to drive hydrological models. However, the nature of the precipitating events and the temporal and spatial scales of the watershed response make them difficult to forecast, even using a high-resolution convection-permitting NWP deterministic forecasting. This study proposes a new method to sample the uncertainties of high-resolution NWP precipitation forecasts in order to quantify the predictability of the streamflow forecasts. We have developed a perturbation method based on convection-permitting NWP-model error statistics. It produces short-term precipitation ensemble forecasts from single-value meteorological forecasts. These rainfall ensemble forecasts are then fed into a hydrological model dedicated to flash-flood forecasting to produce ensemble streamflow forecasts. The verification on two flash-flood events shows that this forecasting ensemble performs better than the deterministic forecast. The performance of the precipitation perturbation method has also been found to be broadly as good as that obtained using a state-of-the-art research convection-permitting NWP ensemble, while requiring less computing time.

  18. Uncertainty forecasts improve weather-related decisions and attenuate the effects of forecast error.

    PubMed

    Joslyn, Susan L; LeClerc, Jared E

    2012-03-01

    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 warning system is used. The work reported here tested the relative benefits of several forecast formats, comparing decisions made with and without uncertainty forecasts. In three experiments, participants assumed the role of a manager of a road maintenance company in charge of deciding whether to pay to salt the roads and avoid a potential penalty associated with icy conditions. Participants used overnight low temperature forecasts accompanied in some conditions by uncertainty estimates and in others by decision advice comparable to categorical warnings. Results suggested that uncertainty information improved decision quality overall and increased trust in the forecast. Participants with uncertainty forecasts took appropriate precautionary action and withheld unnecessary action more often than did participants using deterministic forecasts. When error in the forecast increased, participants with conventional forecasts were reluctant to act. However, this effect was attenuated by uncertainty forecasts. Providing categorical decision advice alone did not improve decisions. However, combining decision advice with uncertainty estimates resulted in the best performance overall. The results reported here have important implications for the development of forecast formats to increase compliance with severe weather warnings as well as other domains in which one must act in the face of uncertainty. PMID:21875244

  19. Earthquakes - Volcanoes (Causes and Forecast)

    NASA Astrophysics Data System (ADS)

    Tsiapas, E.

    2009-04-01

    EARTHQUAKES - VOLCANOES (CAUSES AND FORECAST) ELIAS TSIAPAS RESEARCHER NEA STYRA, EVIA,GREECE TEL.0302224041057 tsiapas@hol.gr The earthquakes are caused by large quantities of liquids (e.g. H2O, H2S, SO2, ect.) moving through lithosphere and pyrosphere (MOHO discontinuity) till they meet projections (mountains negative projections or projections coming from sinking lithosphere). The liquids are moved from West Eastward carried away by the pyrosphere because of differential speed of rotation of the pyrosphere by the lithosphere. With starting point an earthquake which was noticed at an area and from statistical studies, we know when, where and what rate an earthquake may be, which earthquake is caused by the same quantity of liquids, at the next east region. The forecast of an earthquake ceases to be valid if these components meet a crack in the lithosphere (e.g. limits of lithosphere plates) or a volcano crater. In this case the liquids come out into the atmosphere by the form of gasses carrying small quantities of lava with them (volcano explosion).

  20. 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.

  1. 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.

  2. 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…

  3. 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.

  4. 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…

  5. 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

  6. Forecasting Popularity of Videos Using Social Media

    NASA Astrophysics Data System (ADS)

    Xu, Jie; van der Schaar, Mihaela; Liu, Jiangchuan; Li, Haitao

    2015-03-01

    This paper presents a systematic online prediction method (Social-Forecast) that is capable to accurately forecast the popularity of videos promoted by social media. Social-Forecast explicitly considers the dynamically changing and evolving propagation patterns of videos in social media when making popularity forecasts, thereby being situation and context aware. Social-Forecast aims to maximize the forecast reward, which is defined as a tradeoff between the popularity prediction accuracy and the timeliness with which a prediction is issued. The forecasting is performed online and requires no training phase or a priori knowledge. We analytically bound the prediction performance loss of Social-Forecast as compared to that obtained by an omniscient oracle and prove that the bound is sublinear in the number of video arrivals, thereby guaranteeing its short-term performance as well as its asymptotic convergence to the optimal performance. In addition, we conduct extensive experiments using real-world data traces collected from the videos shared in RenRen, one of the largest online social networks in China. These experiments show that our proposed method outperforms existing view-based approaches for popularity prediction (which are not context-aware) by more than 30% in terms of prediction rewards.

  7. 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...

  8. Intermediate range forecasting - observational requirements and techniques

    NASA Astrophysics Data System (ADS)

    Hayden, Christopher M.

    1992-07-01

    The 1990s will witness a significant increase in meteorological observations, both traditional and innovative. Numerical weather forecast models will improve in terms of scale definition and physics. The role the observations, especially those from space, may play in improving the intermediater range forecast is presented. The greatest challenge is to insure that the modeler and the observationalist exploit their opportunities together.

  9. 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)

  10. 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.

  11. Ozone ensemble forecast with machine learning algorithms

    NASA Astrophysics Data System (ADS)

    Mallet, Vivien; Stoltz, Gilles; Mauricette, Boris

    2009-03-01

    We apply machine learning algorithms to perform sequential aggregation of ozone forecasts. The latter rely on a multimodel ensemble built for ozone forecasting with the modeling system Polyphemus. The ensemble simulations are obtained by changes in the physical parameterizations, the numerical schemes, and the input data to the models. The simulations are carried out for summer 2001 over western Europe in order to forecast ozone daily peaks and ozone hourly concentrations. On the basis of past observations and past model forecasts, the learning algorithms produce a weight for each model. A convex or linear combination of the model forecasts is then formed with these weights. This process is repeated for each round of forecasting and is therefore called sequential aggregation. The aggregated forecasts demonstrate good results; for instance, they always show better performance than the best model in the ensemble and they even compete against the best constant linear combination. In addition, the machine learning algorithms come with theoretical guarantees with respect to their performance, that hold for all possible sequences of observations, even nonstochastic ones. Our study also demonstrates the robustness of the methods. We therefore conclude that these aggregation methods are very relevant for operational forecasts.

  12. 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.

  13. 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…

  14. 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.

  15. Streamflow Ensemble Generation using Climate Forecasts

    NASA Astrophysics Data System (ADS)

    Watkins, D. W.; O'Connell, S.; Wei, W.; Nykanen, D.; Mahmoud, M.

    2002-12-01

    Although significant progress has been made in understanding the correlation between large-scale atmospheric circulation patterns and regional streamflow anomalies, there is a general perception that seasonal climate forecasts are not being used to the fullest extent possible for optimal water resources management. Possible contributing factors are limited knowledge and understanding of climate processes and prediction capabilities, noise in climate signals and inaccuracies in forecasts, and hesitancy on the part of water managers to apply new information or methods that could expose them to greater liability. This work involves a decision support model based on streamflow ensembles developed for the Lower Colorado River Authority in Central Texas. Predicative skill is added to ensemble forecasts that are based on climatology by conditioning the ensembles on observable climate indicators, including streamflow (persistence), soil moisture, land surface temperatures, and large-scale recurrent patterns such as the El Ni¤o-Southern Oscillation, Pacific Decadal Oscillation, and the North Atlantic Oscillation. A Bayesian procedure for updating ensemble probabilities is outlined, and various skill scores are reviewed for evaluating forecast performance. Verification of the ensemble forecasts using a resampling procedure indicates a small but potentially significant improvement in forecast skill that could be exploited in seasonal water management decisions. The ultimate goal of this work will be explicit incorporation of climate forecasts in reservoir operating rules and estimation of the value of the forecasts.

  16. 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…

  17. Why preferring parametric forecasting to nonparametric methods?

    PubMed

    Jabot, Franck

    2015-05-01

    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.

  18. Solar power deployment: Forecasting and planning

    NASA Astrophysics Data System (ADS)

    Alanazi, Mohana

    The rapid growth of Photovoltaic (PV) technology has been very visible over the past decade. Recently, the penetration of PV plants to the existing grid has significantly increased. Such increase in the integration of solar energy has brought attention to the solar irradiance forecasting. This thesis presents a thorough research of PV technology, how solar power can be forecasted, and PV planning under uncertainty. Over the last decade, the PV was one of the fastest growing renewable energy technologies. However, the PV system output varies based on weather conditions. Due to the variability and the uncertainty of solar power, the integration of the electricity generated by PV system is considered one of the challenges that have confronted the PV system. This thesis proposes a new forecasting method to reduce the uncertainty of the PV output so the power operator will be able to accommodate its variability. The new forecasting method proposes different processes to be undertaken before the data is fed to the forecasting model. The method converts the data sets included in the forecasting from non-stationary data to a stationary data by applying different processes including: removing the offset, removing night time solar values, and normalization. The new forecasting method aims to reduce the forecasting error and analyzes the error effect on the long term planning through calculating the payback period considering different errors.

  19. 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.

  20. Monthly forecasting of agricultural pests in Switzerland

    NASA Astrophysics Data System (ADS)

    Hirschi, M.; Dubrovsky, M.; Spirig, C.; Samietz, J.; Calanca, P.; Weigel, A. P.; Fischer, A. M.; Rotach, M. W.

    2012-04-01

    Given the repercussions of pests and diseases on agricultural production, detailed forecasting tools have been developed to simulate the degree of infestation depending on actual weather conditions. The life cycle of pests is most successfully predicted if the micro-climate of the immediate environment (habitat) of the causative organisms can be simulated. Sub-seasonal pest forecasts therefore require weather information for the relevant habitats and the appropriate time scale. The pest forecasting system SOPRA (www.sopra.info) currently in operation in Switzerland relies on such detailed weather information, using hourly weather observations up to the day the forecast is issued, but only a climatology for the forecasting period. Here, we aim at improving the skill of SOPRA forecasts by transforming the weekly information provided by ECMWF monthly forecasts (MOFCs) into hourly weather series as required for the prediction of upcoming life phases of the codling moth, the major insect pest in apple orchards worldwide. Due to the probabilistic nature of operational monthly forecasts and the limited spatial and temporal resolution, their information needs to be post-processed for use in a pest model. In this study, we developed a statistical downscaling approach for MOFCs that includes the following steps: (i) application of a stochastic weather generator to generate a large pool of daily weather series consistent with the climate at a specific location, (ii) a subsequent re-sampling of weather series from this pool to optimally represent the evolution of the weekly MOFC anomalies, and (iii) a final extension to hourly weather series suitable for the pest forecasting model. Results show a clear improvement in the forecast skill of occurrences of upcoming codling moth life phases when incorporating MOFCs as compared to the operational pest forecasting system. This is true both in terms of root mean squared errors and of the continuous rank probability scores of the

  1. 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.

  2. PV production forecast in La Reunion Island

    NASA Astrophysics Data System (ADS)

    Dubus, L.; Leboucher, V.; Garo, M.

    2010-09-01

    Photovoltaic power production is developing quickly in La Reunion (Indian Ocean). In order to integrate this fluctuating energy source into the network, reliable production forecasts are necessary from real time to day+3. Weather forecasts from standard models are in general inadequate, in particular due to too coarse resolution in this complex orography area. In this study, we use observations (Météo-France) and reanalysis (ERAinterim) fields to evaluate the potential predictability of PV production, for individual solar power plants and from the island aggregated point of view. This in particular allows to select the best weather predictors for PV production. The forecast quality of the selected fields was then established, in order to use only the interesting ones. Finally, NWPs are used to estimate which part of PV production predictability is accessible with state of the art weather forecasting models. This leads to requirements on temporal and spatial resolution of NWP to improve the forecast quality.

  3. Uncertainty in dispersion forecasts using meteorological ensembles

    SciTech Connect

    Chin, H N; Leach, M J

    1999-07-12

    The usefulness of dispersion forecasts depends on proper interpretation of results. Understanding the uncertainty in model predictions and the range of possible outcomes is critical for determining the optimal course of action in response to terrorist attacks. One of the objectives for the Modeling and Prediction initiative is creating tools for emergency planning for special events such as the upcoming the Olympics. Meteorological forecasts hours to days in advance are used to estimate the dispersion at the time of the event. However, there is uncertainty in any meteorological forecast, arising from both errors in the data (both initial conditions and boundary conditions) and from errors in the model. We use ensemble forecasts to estimate the uncertainty in the forecasts and the range of possible outcomes.

  4. Do probabilistic forecasts lead to better decisions?

    NASA Astrophysics Data System (ADS)

    Ramos, M. H.; van Andel, S. J.; Pappenberger, F.

    2013-06-01

    The last decade has seen growing research in producing probabilistic hydro-meteorological forecasts and increasing their reliability. This followed the promise that, supplied with information about uncertainty, people would take better risk-based decisions. In recent years, therefore, research and operational developments have also started focusing attention on ways of communicating the probabilistic forecasts to decision-makers. Communicating probabilistic forecasts includes preparing tools and products for visualisation, but also requires understanding how decision-makers perceive and use uncertainty information in real time. At the EGU General Assembly 2012, we conducted a laboratory-style experiment in which several cases of flood forecasts and a choice of actions to take were presented as part of a game to participants, who acted as decision-makers. Answers were collected and analysed. In this paper, we present the results of this exercise and discuss if we indeed make better decisions on the basis of probabilistic forecasts.

  5. Guideline for developing an ozone forecasting program

    SciTech Connect

    Dye, T.S.; MacDonald, C.P.; Anderson, C.B.

    1999-07-01

    The purpose of this document is to provide guidance to help air quality agencies develop, operate, and evaluate ozone forecasting programs. This guidance document provides: Background information about ozone and the weather`s effect on ozone; A list of how ozone forecasts are currently used; A summary and evaluation of methods currently used to forecast ozone; and Steps you can follow to develop and operate an ozone forecasting program. The intended audience of this document is project managers, meteorologists, air quality analysts, and data analysts. Project managers can learn about the level of effort needed to set up and operate a forecasting program. Meteorologists can learn about the various methods to predict ozone and the steps needed to create a program.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. Challenges in Forecasting SEP Events

    NASA Astrophysics Data System (ADS)

    Luhmann, Janet; Mays, M. Leila; Odstrcil, Dusan; Bain, Hazel; Li, Yan; Leske, Richard; Cohen, Christina

    2015-04-01

    A long-standing desire of space weather prediction providers has been the ability to forecast SEP (Solar Energetic Particle) events as a part of their offerings. SEPs can have deleterious effects on the space environment and space hardware, that also impact human exploration missions. Developments of observationally driven, physics based models in the last solar cycle have made it possible to use solar magnetograms and coronagraph images to simulate, up to a month in advance for solar wind structure, and up to days in advance for interplanetary Coronal Mass Ejection (ICME) driven shocks, time series of upstream parameters similar in content to those obtained by L1 spacecraft. However, SEPs have been missing from these predictions. Because SEP event modeling requires different physical considerations it has typically been approached with cosmic ray transport concepts and treatments. However, many extra complications arise because of the moving, evolving nature of the ICME shock source of the largest events. In general, a realistic SEP event model for these so-called 'gradual' events requires an accurate description of the time-dependent 3D heliosphere as an underlying framework. We describe some applications of an approach to SEP event simulations that uses the widely-applied ENLIL heliospheric model to describe both underlying solar wind and ICME shock characteristics. Experimentation with this set-up illustrates the importance of knowing the shock connectivity to the observer, and of the need to include even non-observer-impacting CMEs in the heliospheric model. It also provides a possible path forward toward the goal of having routine SEP forecasts together with the other heliospheric predictions.

  12. 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.

  13. 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. PMID:23456373

  14. 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.

  15. Evaluation of Flood Forecast and Warning in Elbe river basin - Impact of Forecaster's Strategy

    NASA Astrophysics Data System (ADS)

    Danhelka, Jan; Vlasak, Tomas

    2010-05-01

    Czech Hydrometeorological Institute (CHMI) is responsible for flood forecasting and warning in the Czech Republic. To meet that issue CHMI operates hydrological forecasting systems and publish flow forecast in selected profiles. Flood forecast and warning is an output of system that links observation (flow and atmosphere), data processing, weather forecast (especially NWP's QPF), hydrological modeling and modeled outputs evaluation and interpretation by forecaster. Forecast users are interested in final output without separating uncertainties of separate steps of described process. Therefore an evaluation of final operational forecasts was done for profiles within Elbe river basin produced by AquaLog forecasting system during period 2002 to 2008. Effects of uncertainties of observation, data processing and especially meteorological forecasts were not accounted separately. Forecast of flood levels exceedance (peak over the threshold) during forecasting period was the main criterion as flow increase forecast is of the highest importance. Other evaluation criteria included peak flow and volume difference. In addition Nash-Sutcliffe was computed separately for each time step (1 to 48 h) of forecasting period to identify its change with the lead time. Textual flood warnings are issued for administrative regions to initiate flood protection actions in danger of flood. Flood warning hit rate was evaluated at regions level and national level. Evaluation found significant differences of model forecast skill between forecasting profiles, particularly less skill was evaluated at small headwater basins due to domination of QPF uncertainty in these basins. The average hit rate was 0.34 (miss rate = 0.33, false alarm rate = 0.32). However its explored spatial difference is likely to be influenced also by different fit of parameters sets (due to different basin characteristics) and importantly by different impact of human factor. Results suggest that the practice of interactive

  16. 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

  17. Performance of aftershock forecasts: problem and formulation

    NASA Astrophysics Data System (ADS)

    Jiang, C.; Wu, Z.; Li, L.

    2010-12-01

    WFSD project deals with the problems of earthquake physics, in which one of the important designed aims is the forecast of the on-going aftershock activity of the Wenchuan earthquake, taking the advantage of the fast response to great earthquakes. Correlation between fluid measurements and aftershocks provided heuristic clues to the forecast of aftershocks, invoking the discussion on the performance of such ‘precursory anomalies’, even if in a retrospective perspective. In statistical seismology, one of the critical issues is how to test the statistical significance of an earthquake forecast scheme against real seismic activity. Due to the special characteristics of aftershock series and the feature of aftershock forecasts that it deals with a limited spatial range and specific temporal duration, the test of the performance of aftershock forecasts has to be different from the standard tests for main shock series. In this presentation we address and discuss the possible schemes for testing the performance of aftershock forecasts - a seemingly simple but practically important issue in statistical seismology. As a simple and preliminary approach, we use an alternative form of Receiver Operating Characteristic (ROC) test, as well as other similar tests, considering the properties of aftershock series by using Omori law, ETAS model, and/or CFS calculation. We also discussed the lessons and experiences of the Wenchuan aftershock forecasts, exploring how to make full use of the present knowledge of the regularity of aftershocks to serve the earthquake rescue and relief endeavor as well as the post-earthquake reconstruction.

  18. 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.

  19. 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.

  20. Tropical ocean initialisation strategies for seasonal forecasting

    NASA Astrophysics Data System (ADS)

    Mulholland, David; Haines, Keith

    2016-04-01

    Operational seasonal ENSO forecasts show substantial skill in tropical regions, but are sensitive to the initialisation procedure used in the ocean. Due to errors in wind stress forcing and in modelling the vertical transfer of momentum, a bias correction method is often used during ocean data assimilation in order to assimilate hydrographic data, e.g. from the TOGA/TAO array. While this improves the ocean state, particularly the circulation, during the analysis, it leads to an inconsistency at the beginning of a coupled forecast, since the bias correction term is generally not retained during the forecast itself. We present results from a number of ensemble simulations carried out with the European Centre for Medium-range Weather Forecasts (ECMWF) coupled forecast system, comparing different initialisation strategies for the equatorial ocean. Rapid adjustments in the ocean at the beginning of the forecast are found to induce additional variability in the thermocline. We then show that this spurious variability can be substantially reduced by persisting or more slowly adjusting the bias correction term during the first month, and that this leads to significant improvements in ENSO SST forecast skill, at lead times of 3-7 months. The results highlight the importance of ocean initialisation in maximising the skill of ENSO predictions.

  1. 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

  2. Accurate Weather Forecasting for Radio Astronomy

    NASA Astrophysics Data System (ADS)

    Maddalena, Ronald J.

    2010-01-01

    The NRAO Green Bank Telescope routinely observes at wavelengths from 3 mm to 1 m. As with all mm-wave telescopes, observing conditions depend upon the variable atmospheric water content. The site provides over 100 days/yr when opacities are low enough for good observing at 3 mm, but winds on the open-air structure reduce the time suitable for 3-mm observing where pointing is critical. Thus, to maximum productivity the observing wavelength needs to match weather conditions. For 6 years the telescope has used a dynamic scheduling system (recently upgraded; www.gb.nrao.edu/DSS) that requires accurate multi-day forecasts for winds and opacities. Since opacity forecasts are not provided by the National Weather Services (NWS), I have developed an automated system that takes available forecasts, derives forecasted opacities, and deploys the results on the web in user-friendly graphical overviews (www.gb.nrao.edu/ rmaddale/Weather). The system relies on the "North American Mesoscale" models, which are updated by the NWS every 6 hrs, have a 12 km horizontal resolution, 1 hr temporal resolution, run to 84 hrs, and have 60 vertical layers that extend to 20 km. Each forecast consists of a time series of ground conditions, cloud coverage, etc, and, most importantly, temperature, pressure, humidity as a function of height. I use the Liebe's MWP model (Radio Science, 20, 1069, 1985) to determine the absorption in each layer for each hour for 30 observing wavelengths. Radiative transfer provides, for each hour and wavelength, the total opacity and the radio brightness of the atmosphere, which contributes substantially at some wavelengths to Tsys and the observational noise. Comparisons of measured and forecasted Tsys at 22.2 and 44 GHz imply that the forecasted opacities are good to about 0.01 Nepers, which is sufficient for forecasting and accurate calibration. Reliability is high out to 2 days and degrades slowly for longer-range forecasts.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. Ninth electric utility forecasting symposium: Proceedings. Forecasting and DSM -- Organizing for success

    SciTech Connect

    1995-05-01

    EPRI and the San Diego Gas and Electric Company (SDG and E) hosted a two-and-one-half day symposium in San Diego, California on September 8--10, 1993. Plenary presentations, topical paper sessions, and demonstrations covered a wide variety of topics, ranging from traditional forecasting topics to the changing nature of customers in the next century. The objectives of the symposium were to: exchange information and ideas about new forecasting methods, tools, and data sources; promote an exchange of views between those who produce forecasts and those who use forecasts; explore the relationship between forecasting and DSM; and discuss possible future trends for the electric utility industry and to consider the future role of forecasting. Selected papers are indexed separately for inclusion in the Energy Science and Technology Database.

  9. 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)

  10. 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...

  11. Impact of Seasonal Forecasts on Agriculture

    NASA Astrophysics Data System (ADS)

    Aldor-Noiman, S. C.

    2014-12-01

    More extreme and volatile weather conditions are a threat to U.S. agricultural productivity today, as multiple environmental conditions during the growing season impact crop yields. That's why farmers' agronomic management decisions are dominated by consideration for near, medium and seasonal forecasts of climate. The Climate Corporation aims to help farmers around the world protect and improve their farming operations by providing agronomic decision support tools that leverage forecasts on multiple timescales to provide valuable insights directly to farmers. In this talk, we will discuss the impact of accurate seasonal forecasts on major decisions growers face each season. We will also discuss assessment and evaluation of seasonal forecasts in the context of agricultural applications.

  12. Flood forecasting for Tucurui Hydroelectrical Plant, Brazil

    SciTech Connect

    Solomon, S.I.; Basso, E.; Osorio, C.; Melo de Moraes, H.; Serrano, A.

    1986-04-01

    The construction of the Tucurui Hydroelectric Plant on the Tocantins River basin in Brazil requires flood forecasting to ensure the safety of the cofferdam. The latter has been initially designed for a flood with a return frequency of one in 25 years. Lack of adequate forecasting facilities during the earlier stages of construction has resulted in significant damages and construction delays. Statistical forecasting models were developed by Projeto de Hidrologia y Climatologie da Amazonia (PHCA) for the purpose of preventing further damage at the site. The application of these models during the 1980 flood season, when the highest flood on record occurred at the Tucurui site, proved of great assistance in preventing the flooding of the cofferdam. In conjunction with the development of these models a number of data collection platforms using data transmission through the GOES system were installed to provide the data required for forecasting.

  13. Short term energy forecasting with neural networks

    SciTech Connect

    McMenamin, J.S.; Monforte, F.A. )

    1998-01-01

    Artificial neural networks are beginning to be used by electric utilities to forecast hourly system loads on a day-ahead basis. This paper discusses the neural network specification in terms of conventional econometric language, providing parallel concepts for terms such as training, learning, and nodes in the hidden layer. It is shown that these models are flexible nonlinear equations that can be estimated using nonlinear least squares. It is argued that these models are especially well suited to hourly load forecasting, reflecting the presence of important nonlinearities and variable interactions. The paper proceeds to show how conventional statistics, such as the BIC and MAPE statistics can be used to select the number of nodes in the hidden layer. It is concluded that these models provide a powerful, robust and sensible approach to hourly load forecasting that will provide modest improvements in forecast accuracy relative to well-specified regression models.

  14. International health spending forecasts: concepts and evaluation.

    PubMed

    Getzen, T E; Poullier, J P

    1992-05-01

    Health care depends on the organizational and financial decisions which constituted each national system. Since those decisions were made at various times over the preceding years under different macroeconomic conditions, current expenditures are a distributed lag function of GDP growth and inflation rates. The accuracy of forecasts from such causal econometric models are compared to exponential smoothing, moving average, and ARIMA methods. Data fro 19 OECD countries 1965-79 are used for calibration, and then ex ante forecasts are generated for 1980-87 so that actual forecast accuracy can be tested. The greatest reduction in mean absolute error was obtained with the econometric model estimated in aggregate across all 19 countries, although single-country models, exponential smoothing and international averaging were also effective. A combination of all four forecasts was more accurate than any one alone, reducing MAE by 25% relative to a constant growth projection.

  15. 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.

  16. Prediction Techniques in Operational Space Weather Forecasting

    NASA Astrophysics Data System (ADS)

    Zhukov, Andrei

    2016-07-01

    The importance of forecasting space weather conditions is steadily increasing as our society is becoming more and more dependent on advanced technologies that may be affected by disturbed space weather. Operational space weather forecasting is still a difficult task that requires the real-time availability of input data and specific prediction techniques that are reviewed in this presentation, with an emphasis on solar and interplanetary weather. Key observations that are essential for operational space weather forecasting are listed. Predictions made on the base of empirical and statistical methods, as well as physical models, are described. Their validation, accuracy, and limitations are discussed in the context of operational forecasting. Several important problems in the scientific basis of predicting space weather are described, and possible ways to overcome them are discussed, including novel space-borne observations that could be available in future.

  17. Moisture Forecast Bias Correction in GEOS DAS

    NASA Technical Reports Server (NTRS)

    Dee, D.

    1999-01-01

    Data assimilation methods rely on numerous assumptions about the errors involved in measuring and forecasting atmospheric fields. One of the more disturbing of these is that short-term model forecasts are assumed to be unbiased. In case of atmospheric moisture, for example, observational evidence shows that the systematic component of errors in forecasts and analyses is often of the same order of magnitude as the random component. we have implemented a sequential algorithm for estimating forecast moisture bias from rawinsonde data in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The algorithm is designed to remove the systematic component of analysis errors and can be easily incorporated in an existing statistical data assimilation system. We will present results of initial experiments that show a significant reduction of bias in the GEOS DAS moisture analyses.

  18. 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.

  19. 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 ...

  20. Drought forecasting over Europe using Standardized Precipitation Index and monthly forecasts

    NASA Astrophysics Data System (ADS)

    Kurnik, B.

    2009-09-01

    In this study drought forecasting with the Standardized Precipitation Index - SPI computed from monthly meteorological forecasts and ERA-40 data is presented. Both datasets are produced and delivered by European Centre for Medium-Range Weather Forecasts (ECMWF). The SPI is based on rainfall only. It is a statistical indicator evaluating the lack or surplus of precipitation during a given period of time as a function of the long-term average precipitation and its distribution. It is calculated using a continuous, long-term (more than 30 years) series of historic monthly precipitation records. Depending on the purpose of the analysis the SPI can be calculated for different time scales (from less than 1 month to 24 or 48 months) The forecasted 3 monthly SPI (SPI-3) is computed as a combination of ECMWF probabilistic monthly meteorological forecasts and two months of ERA-40 precipitation data over the European area. Probability that forecasted SPI-3 exceeds predefined threshold is derived from 50 ensemble states of the monthly forecast. Brier Score (BS) and Brier Skill Score (BSS) methods have been used for validation of probabilistic SPI-3 forecasts against observations data derived from the Global Precipitation Climatology Centre - GPCC. Additionally also categorical verification has been applied with conversion from probabilistic to categorical forecast system using probabilistic thresholds (60 % and 75 %). Performance measures, such as Proportion correct (PC), Hit rate (HR) and False alarm ratio (FAR) together with Pierce's skill score (PSS), have been applied. In the analyzed spatial and temporal domain BS values for ECMWF forecast are generally low. Higher BS has been calculated in the winter 2005/2006 and in the areas where instability of SPI is quite high. BSS shows the ECMWF forecasts are better skilled than climatology in spatial and temporal domain. BSS values are positive in around 55 % of the cases. Adjusted contingency table verification show similar

  1. Tracking Progress in North American Monsoon Seasonal Forecasts: The NAME Forecast Forum (Invited)

    NASA Astrophysics Data System (ADS)

    Gochis, D. J.

    2009-12-01

    The North American Monsoon Experiment (NAME) was developed and implemented in an effort to improve the low prediction skill of intraseasonal and seasonal forecasts of North American Monsoon behavior. As a logical follow-on to NAM diagnostic and modeling activities, the NAME research and operational seasonal prediction communities have developed the NAME Forecast Forum (NFF), whose aim is to consolidate and assess, in real time, the performance of intraseasonal and seasonal monsoon forecasts and to make these forecasts available to a range of regional stakeholders. This forum, first implemented in the 2008 NAM season, showed that dynamical forecast models predict many general precipitation patterns moderately well but do not fully capture monsoon extent and magnitude. In this talk we will present results of the NAM precipitation forecasts for the past two summers, 2008 and 2009. These summers are interesting in the context of evaluating model performance in situations of climatic extremes. Summer rainfall over Mexico during 2008 was the highest on record for the past 60 years while 2009 saw many regions experiencing far below normal rainfall. The possible reasons for these extreme seasons will be explored as they relate to the apparent skill of seasonal forecasts submitted to the NAME Forecast Forum. Future plans for the Forecast Forum will also be presented.

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. The HFIP High Resolution Hurricane Forecast Test

    NASA Astrophysics Data System (ADS)

    Nance, L. B.; Bernardet, L.; Bao, S.; Brown, B.; Carson, L.; Fowler, T.; Halley Gotway, J.; Harrop, C.; Szoke, E.; Tollerud, E. I.; Wolff, J.; Yuan, H.

    2010-12-01

    Tropical cyclones are a serious concern for the nation, causing significant risk to life, property and economic vitality. The National Oceanic and Atmospheric Administration (NOAA) National Weather Service has a mission of issuing tropical cyclone forecasts and warnings, aimed at protecting life and property and enhancing the national economy. In the last 10 years, the errors in hurricane track forecasts have been reduced by about 50% through improved model guidance, enhanced observations, and forecaster expertise. However, little progress has been made during this period toward reducing forecasted intensity errors. To address this shortcoming, NOAA established the Hurricane Forecast Improvement Project (HFIP) in 2007. HFIP is a 10-year plan to improve one to five day tropical cyclone forecasts, with a focus on rapid intensity change. Recent research suggests that prediction models with grid spacing less than 1 km in the inner core of the hurricane may provide a substantial improvement in intensity forecasts. The 2008-09 staging of the High Resolution Hurricane (HRH) Test focused on quantifying the impact of increased horizontal resolution in numerical models on hurricane intensity forecasts. The primary goal of this test was an evaluation of the effect of increasing horizontal resolution within a given model across a variety of storms with different intensity, location and structure. The test focused on 69 retrospectives cases from the 2005 and 2007 hurricane seasons. Six modeling groups participated in the HRH test utilizing a variety of models, including three configurations of the Weather Research and Forecasting (WRF) model, the operational GFDL model, the Navy’s tropical cyclone model, and a model developed at the University of Wisconsin-Madison (UWM). The Development Testbed Center (DTC) was tasked with providing objective verification statistics for a variety of metrics. This presentation provides an overview of the HRH Test and a summary of the standard

  8. Application of hydrologic forecast model.

    PubMed

    Hua, Xu; Hengxin, Xue; Zhiguo, Chen

    2012-01-01

    In order to overcome the shortcoming of the solution may be trapped into the local minimization in the traditional TSK (Takagi-Sugeno-Kang) fuzzy inference training, this paper attempts to consider the TSK fuzzy system modeling approach based on the visual system principle and the Weber law. This approach not only utilizes the strong capability of identifying objects of human eyes, but also considers the distribution structure of the training data set in parameter regulation. In order to overcome the shortcoming of it adopting the gradient learning algorithm with slow convergence rate, a novel visual TSK fuzzy system model based on evolutional learning is proposed by introducing the particle swarm optimization algorithm. The main advantage of this method lies in its very good optimization, very strong noise immunity and very good interpretability. The new method is applied to long-term hydrological forecasting examples. The simulation results show that the method is feasible and effective, the new method not only inherits the advantages of traditional visual TSK fuzzy models but also has the better global convergence and accuracy than the traditional model.

  9. 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.

  10. 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.

  11. Spatiotemporal drought forecasting using nonlinear models

    NASA Astrophysics Data System (ADS)

    Vasiliades, Lampros; Loukas, Athanasios

    2010-05-01

    Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with

  12. 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.

  13. Forecasting area of strong aftershock occurrence

    NASA Astrophysics Data System (ADS)

    Baranov, Sergey; Shebalin, Peter

    2016-04-01

    Forecasting an area of strong aftershock was never, at our knowledge, considered in terms of operational forecasting. Different declustering models exist to separate post-factum the aftershocks from "independent" events. Large number of studies discussed in previous years the form of the distribution of the aftershocks distances from the mainshock fault. Here we present results of our attempts to assimilate the above researches into a model that can be used in operational aftershock forecasting. Our study was based on data provided by ANSS catalog for 1980-2015. We tried more than 20 well known and suggested by ourselves models of aftershock areas to retrospective forecasting of strong aftershock areas. We tried the models based on data for 12 hours after a mainshock and estimated their forecast quality using special modification of L-test to achieve an optimal model. As a result of our study is a model that can be used in operational forecasting area of strong aftershocks. The research was supported by Russian Foundation for Basic Research (Project 16-05-00263A).

  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. Traffic flow forecasting: Comparison of modeling approaches

    SciTech Connect

    Smith, B.L.; Demetsky, M.J.

    1997-08-01

    The capability to forecast traffic volume in an operational setting has been identified as a critical need for intelligent transportation systems (ITS). In particular, traffic volume forecasts will support proactive, dynamic traffic control. However, previous attempts to develop traffic volume forecasting models have met with limited success. This research effort focused on developing traffic volume forecasting models for two sites on Northern Virginia`s Capital Beltway. Four models were developed and tested for the freeway traffic flow forecasting problem, which is defined as estimating traffic flow 15 min into the future. They were the historical average, time-series, neural network, and nonparametric regression models. The nonparametric regression model significantly outperformed the other models. A Wilcoxon signed-rank test revealed that the nonparametric regression model experienced significantly lower errors than the other models. In addition, the nonparametric regression model was easy to implement, and proved to be portable, performing well at two distinct sites. Based on its success, research is ongoing to refine the nonparametric regression model and to extend it to produce multiple interval forecasts.

  16. 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.

  17. USWRP Workshop on Air Quality Forecasting

    SciTech Connect

    Dabberdt, Walter F.; Carroll, Mary Anne; Appleby, William; Baumgardner, Darrel; Carmichael, Gregory; Davidson, Paula; Doran, J. C.; Dye, Timothy G.; Grimmond, Susan; Middleton, Paulette; Neff, William; Zhang, Yang

    2006-02-01

    There has recently been increased emphasis on air quality forecasting (AQF) and the research and development activities that are required to improve AQF skill and implement an operational AQF capability. In November 2001, the US Weather Research Program (USWRP) charged Prospectus Develop Team 11 with identification of the meteorological research needs for improved air quality forecasting (Dabberdt et al. 2004a). Subsequently, the Interagency Working Group (IWG) of the USWRP tentatively adopted Air Quality as one of its principal scientific foci. In addition, the National Oceanic and Atmospheric Administration (NOAA) and the United States Environmental Protection Agency (EPA) have made substantial progress towards developing an operational air quality forecast system. With these activities as background, the lead scientist of the USWRP requested that a community workshop be conducted to further define and prioritize AQF research needs and opportunities. The results of the workshop would then be used in the development of an Implementation Plan that the IWG would use to prioritize and support research directed at improving air quality knowledge, monitoring and forecasting capabilities, and evaluating new air quality forecast products. The resulting USWRP Air Quality Forecasting Workshop was held April 29 – May 1, 2003, in Houston, Texas. This report summarizes the findings and recommendations.

  18. Satellite based Ocean Forecasting, the SOFT project

    NASA Astrophysics Data System (ADS)

    Stemmann, L.; Tintoré, J.; Moneris, S.

    2003-04-01

    The knowledge of future oceanic conditions would have enormous impact on human marine related areas. For such reasons, a number of international efforts are being carried out to obtain reliable and manageable ocean forecasting systems. Among the possible techniques that can be used to estimate the near future states of the ocean, an ocean forecasting system based on satellite imagery is developped through the Satelitte based Ocean ForecasTing project (SOFT). SOFT, established by the European Commission, considers the development of a forecasting system of the ocean space-time variability based on satellite data by using Artificial Intelligence techniques. This system will be merged with numerical simulation approaches, via assimilation techniques, to get a hybrid SOFT-numerical forecasting system of improved performance. The results of the project will provide efficient forecasting of sea-surface temperature structures, currents, dynamic height, and biological activity associated to chlorophyll fields. All these quantities could give valuable information on the planning and management of human activities in marine environments such as navigation, fisheries, pollution control, or coastal management. A detailed identification of present or new needs and potential end-users concerned by such an operational tool is being performed. The project would study solutions adapted to these specific needs.

  19. Status and Future of Dust Storm Forecasting

    NASA Astrophysics Data System (ADS)

    Westphal, D. L.

    2002-12-01

    In recent years, increased attention has been given to the large amounts of airborne dust derived from the deserts and desertified areas of the world and transported over scales ranging from local to global. This dust can have positive and negative impacts on human activities and the environment, including modifying cloud formation, fertilizing the ocean, degrading air quality, reducing visibility, transporting pathogens, and inducing respiratory problems. The atmospheric radiative forcing by the dust has implications for global climate change and presently is one of the largest unknowns in climate models. These uncertainties have lead to much of the funding for research into the sources, properties, and fate of atmospheric dust. As a result of advances in numerical weather prediction over the past decades and the recent climate research, we are now in a position to produce operational dust storm forecasts. International organizations and national agencies are developing programs for dust forecasting. The approaches and applications of dust detection and forecasting are as varied as the nations that are developing the models. The basic components of a dust forecasting system include atmospheric forcing, dust production, and dust microphysics. The forecasting applications include air and auto traffic safety, shipping, health, national security, climate and weather. This presentation will summarize the methods of dust storm forecasting and illustrate the various applications. The major remaining uncertainties (e.g. sources and initialization) will be discussed as well as approaches for solving those problems.

  20. 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…

  1. 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

  2. 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

  3. 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

  4. 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

  5. Impact of precipitation forecast uncertainties and initial soil moisture conditions on a probabilistic flood forecasting chain

    NASA Astrophysics Data System (ADS)

    Silvestro, Francesco; Rebora, Nicola

    2014-11-01

    One of the main difficulties that flood forecasters are faced with is evaluating how errors and uncertainties in forecasted precipitation propagate into streamflow forecast. These errors, must be combined with the effects of different initial soil moisture conditions that generally have a significant impact on the final results of a flood forecast. This is further complicated by the fact that a probabilistic approach is needed, especially when small and medium size basins are considered (the variability of the streamflow scenarios is in fact strongly influenced by the aforementioned factors). Moreover, the ensemble size is a degree of freedom when a precipitation downscaling algorithm is part of the forecast chain. In fact, a change of ensemble size could lead to different final results once the other inputs and parameters are fixed. In this work, a series of synthetic experiments have been designed and implemented to test an operational probabilistic flood forecast system in order to augment the knowledge of how streamflow forecasts can be affected by errors and uncertainties associated with the three aforementioned elements: forecasted rainfall, soil moisture initial conditions, and ensemble size.

  6. 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…

  7. 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).

  8. 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). PMID:24128184

  9. 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.

  10. 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.

  11. Optimizing Tsunami Forecast Model Accuracy

    NASA Astrophysics Data System (ADS)

    Whitmore, P.; Nyland, D. L.; Huang, P. Y.

    2015-12-01

    Recent tsunamis provide a means to determine the accuracy that can be expected of real-time tsunami forecast models. Forecast accuracy using two different tsunami forecast models are compared for seven events since 2006 based on both real-time application and optimized, after-the-fact "forecasts". Lessons learned by comparing the forecast accuracy determined during an event to modified applications of the models after-the-fact provide improved methods for real-time forecasting for future events. Variables such as source definition, data assimilation, and model scaling factors are examined to optimize forecast accuracy. Forecast accuracy is also compared for direct forward modeling based on earthquake source parameters versus accuracy obtained by assimilating sea level data into the forecast model. Results show that including assimilated sea level data into the models increases accuracy by approximately 15% for the events examined.

  12. 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.

  13. Evaluation of ensemble forecast uncertainty using a new proper score: application to medium-range and seasonal forecasts

    NASA Astrophysics Data System (ADS)

    Christensen, Hannah; Moroz, Irene; Palmer, Tim

    2015-04-01

    Forecast verification is important across scientific disciplines as it provides a framework for evaluating the performance of a forecasting system. In the atmospheric sciences, probabilistic skill scores are often used for verification as they provide a way of unambiguously ranking the performance of different probabilistic forecasts. In order to be useful, a skill score must be proper -- it must encourage honesty in the forecaster, and reward forecasts which are reliable and which have good resolution. A new score, the Error-spread Score (ES), is proposed which is particularly suitable for evaluation of ensemble forecasts. It is formulated with respect to the moments of the forecast. The ES is confirmed to be a proper score, and is therefore sensitive to both resolution and reliability. The ES is tested on forecasts made using the Lorenz '96 system, and found to be useful for summarising the skill of the forecasts. The European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system (EPS) is evaluated using the ES. Its performance is compared to a perfect statistical probabilistic forecast -- the ECMWF high resolution deterministic forecast dressed with the observed error distribution. This generates a forecast that is perfectly reliable if considered over all time, but which does not vary from day to day with the predictability of the atmospheric flow. The ES distinguishes between the dynamically reliable EPS forecasts and the statically reliable dressed deterministic forecasts. Other skill scores are tested and found to be comparatively insensitive to this desirable forecast quality. The ES is used to evaluate seasonal range ensemble forecasts made with the ECMWF System 4. The ensemble forecasts are found to be skilful when compared with climatological or persistence forecasts, though this skill is dependent on region and time of year.

  14. 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.

  15. Skill of global hydrological forecasting system FEWS GLOWASIS using climatic ESP forecasts

    NASA Astrophysics Data System (ADS)

    Weerts, A. H.; Candogan, N.; Winsemius, H. C.; van Beek, R.; Westerhoff, R.

    2012-04-01

    Forecasting of water availability and scarcity is a prerequisite for the management of hydropower reservoirs, basin-scale management of water resources, agriculture and disaster relief. The EU 7th Framework Program project Global Water Scarcity Information Service (GLOWASIS) aims to pre-validate a service that provides real-time global-scale information on water scarcity. In this contribution, we demonstrate what skill (compared to a climatology) may be reached with a global seasonal ensemble forecasting system consisting of: a) a global hydrological model PCR-GLOBWB; b) an updating procedure for initial forecasting states, based on the best-guess global rainfall information. As best guess, a combination of ERA-Interim Reanalysis rainfall and Global Precipitation Climatology Project (GPCP) observations is being used; c) a forecast based on Ensemble Streamflow Prediction (ESP)procedure and reverse ESP procedure (Wood and Lettenmaier, 2008). In the ESP procedure, a meteorological forecast ensemble is generated based on past years of observation series (i.e. climatological observations). As observations, the combination of ERA-Interim and GPCP is used. In reverse ESP, an ensemble is generated by using a set of initial states from a large sample of updates at the specific month of interest, and forecasts are produced using one observed set. This analysis allows us to measure how much skill may be expected from hydrological inertia and climatology alone, leaving aside for the moment potential skill improvement by using seasonal meteorological forecasts. In future work, we will measure how much skill improvement compared to the forecasts mentioned above may be reached, when ECMWF Seasonal forecasts are used. This will allow us to measure the contributions to skill of each component (initial state inertia, hydrology and meteorological inputs) of the forecast system.

  16. 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

  17. 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

  18. 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.

  19. Towards custom made seasonal/decadal forecasting

    NASA Astrophysics Data System (ADS)

    Mahlstein, Irina; Spirig, Christoph; Liniger, Mark

    2014-05-01

    Climate indices offer the possibility to deliver information to the end user that can be easily applied to their field of work. For instance, a 3-monthly mean average temperature does not say much about the Heating Degree Days of a season, or how many frost days there are to be expected. Hence, delivering aggregated climate information can be more useful to the consumer than just raw data. In order to ensure that the end-users actually get what they need, the providers need to know what exactly they need to deliver. Hence, the specific user-needs have to be identified. In the framework of EUPORIAS, interviews with the end-user were conducted in order to learn more about the types of information that are needed. But also to investigate what knowledge exists among the users about seasonal/decadal forecasting and in what way uncertainties are taken into account. It is important that we gain better knowledge of how forecasts/predictions are applied by the end-user to their specific situation and business. EUPORIAS, which is embedded in the framework of EU FP7, aims exactly to improve that knowledge and deliver very specific forecasts that are custom made. Here we present examples of seasonal forecasts and their skill of several climate impact indices with direct relevance for specific economic sectors, such as energy. The results are compared to the visualization of conventional depiction of seasonal forecasts, such as 3 monthly average temperature tercile probabilities and the differences are highlighted.

  20. 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.

  1. Forecasting the Emergency Department Patients Flow.

    PubMed

    Afilal, Mohamed; Yalaoui, Farouk; Dugardin, Frédéric; Amodeo, Lionel; Laplanche, David; Blua, Philippe

    2016-07-01

    Emergency department (ED) have become the patient's main point of entrance in modern hospitals causing it frequent overcrowding, thus hospital managers are increasingly paying attention to the ED in order to provide better quality service for patients. One of the key elements for a good management strategy is demand forecasting. In this case, forecasting patients flow, which will help decision makers to optimize human (doctors, nurses…) and material(beds, boxs…) resources allocation. The main interest of this research is forecasting daily attendance at an emergency department. The study was conducted on the Emergency Department of Troyes city hospital center, France, in which we propose a new practical ED patients classification that consolidate the CCMU and GEMSA categories into one category and innovative time-series based models to forecast long and short term daily attendance. The models we developed for this case study shows very good performances (up to 91,24 % for the annual Total flow forecast) and robustness to epidemic periods.

  2. 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. PMID:16433097

  3. In Brief: Atlantic seasonal hurricane forecast

    NASA Astrophysics Data System (ADS)

    Showstack, Randy

    2007-12-01

    Two hurricane forecasters are predicting that 2008 will be an above-average Atlantic basin tropical cyclone season with an above-average probability of a major hurricane making landfall in the United States. During 2008, there could be about seven hurricanes (the annual average is 5.9) and 13 named storms (the average is 9.6), according to a 7 December report by Philip Klotzbach, research scientist at Colorado State University in Fort Collins, and William Gray, university professor emeritus of atmospheric sciences. The forecasters indicate that they believe the Atlantic basin is in an active hurricane cycle that is associated with a strong thermohaline circulation and an active phase of the Atlantic Multidecadal Oscillation. The report notes that, ``real-time operational early December forecasts have not shown forecast skill over climatology during this 16-year period [1992-2007]. This has occurred despite the fact that the skill over the hindcast period...showed appreciable skill.'' For more information, visit the Web site: http://hurricane.atmos.colostate.edu/Forecasts/2007/dec2007/dec2007.pdf.

  4. Monitoring and forecasting Etna volcanic plumes

    NASA Astrophysics Data System (ADS)

    Scollo, S.; Prestifilippo, M.; Spata, G.; D'Agostino, M.; Coltelli, M.

    2009-09-01

    In this paper we describe the results of a project ongoing at the Istituto Nazionale di Geofisica e Vulcanologia (INGV). The objective is to develop and implement a system for monitoring and forecasting volcanic plumes of Etna. Monitoring is based at present by multispectral infrared measurements from the Spin Enhanced Visible and Infrared Imager on board the Meteosat Second Generation geosynchronous satellite, visual and thermal cameras, and three radar disdrometers able to detect ash dispersal and fallout. Forecasting is performed by using automatic procedures for: i) downloading weather forecast data from meteorological mesoscale models; ii) running models of tephra dispersal, iii) plotting hazard maps of volcanic ash dispersal and deposition for certain scenarios and, iv) publishing the results on a web-site dedicated to the Italian Civil Protection. Simulations are based on eruptive scenarios obtained by analysing field data collected after the end of recent Etna eruptions. Forecasting is, hence, supported by plume observations carried out by the monitoring system. The system was tested on some explosive events occurred during 2006 and 2007 successfully. The potentiality use of monitoring and forecasting Etna volcanic plumes, in a way to prevent threats to aviation from volcanic ash, is finally discussed.

  5. 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

  6. Heterogeneity: The key to failure forecasting.

    PubMed

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

    2015-08-26

    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.

  7. 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.

  8. Does money matter in inflation forecasting?

    NASA Astrophysics Data System (ADS)

    Binner, J. M.; Tino, P.; Tepper, J.; Anderson, R.; Jones, B.; Kendall, G.

    2010-11-01

    This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two nonlinear techniques, namely, recurrent neural networks and kernel recursive least squares regression-techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naïve random walk model. The best models were nonlinear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. Beyond its economic findings, our study is in the tradition of physicists’ long-standing interest in the interconnections among statistical mechanics, neural networks, and related nonparametric statistical methods, and suggests potential avenues of extension for such studies.

  9. 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.

  10. Forecasting the Emergency Department Patients Flow.

    PubMed

    Afilal, Mohamed; Yalaoui, Farouk; Dugardin, Frédéric; Amodeo, Lionel; Laplanche, David; Blua, Philippe

    2016-07-01

    Emergency department (ED) have become the patient's main point of entrance in modern hospitals causing it frequent overcrowding, thus hospital managers are increasingly paying attention to the ED in order to provide better quality service for patients. One of the key elements for a good management strategy is demand forecasting. In this case, forecasting patients flow, which will help decision makers to optimize human (doctors, nurses…) and material(beds, boxs…) resources allocation. The main interest of this research is forecasting daily attendance at an emergency department. The study was conducted on the Emergency Department of Troyes city hospital center, France, in which we propose a new practical ED patients classification that consolidate the CCMU and GEMSA categories into one category and innovative time-series based models to forecast long and short term daily attendance. The models we developed for this case study shows very good performances (up to 91,24 % for the annual Total flow forecast) and robustness to epidemic periods. PMID:27272135

  11. 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

  12. 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

  13. 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.

  14. Heterogeneity: The key to failure forecasting.

    PubMed

    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

  15. Seasonal Climate Forecasts and Adoption by Agriculture

    NASA Astrophysics Data System (ADS)

    Garbrecht, Jurgen; Meinke, Holger; Sivakumar, Mannava V. K.; Motha, Raymond P.; Salinger, Michael J.

    2005-06-01

    Recent advances in atmospheric and ocean sciences and a better understanding of the global climate have led to skillful climate forecasts at seasonal to interannual timescales, even in midlatitudes. These scientific advances and forecasting capabilities have opened the door to practical applications that benefit society. The benefits include the reduction of weather/climate related risks and vulnerability, increased economic opportunities, enhanced food security, mitigation of adverse climate impacts, protection of environmental quality, and so forth. Agriculture in particular can benefit substantially from accurate long-lead seasonal climate forecasts. Indeed, agricultural production very much depends on weather, climate, and water availability, and unexpected departures from anticipated climate conditions can thwart the best laid management plans. Timely climate forecasts offer means to reduce losses in drought years, increase profitability in good years, deal more effectively with climate variability, and choose from targeted risk-management strategies. In addition to benefiting farmers, forecasts can also help marketing systems and downstream users prepare for anticipated production outcomes and associated consequences.

  16. Worst case forecasting of Hurricane Irene (2011)

    NASA Astrophysics Data System (ADS)

    Hoffman, R. N.; Gombos, D.; Woods, B. K.

    2012-04-01

    Worst case scenarios for wind damage from Hurricane Irene are estimated from an ensemble of surface wind speed forecasts. Damage at any point is modeled by applying a simple damage function to census data estimates of property values. The forecast damage ensemble provides an estimate of the covariance structure of the damage. Under the assumption that the damage is multivariate Gaussian (mG), the damage covariance defines a high dimensional ellipsoidal surface for any probability quantile. The damage maximizing point on that ellipsoid, i.e., the ``exigent'' scenario, is found by the method of Lagrangian multipliers according to the Exigent Analysis Theorem (EAT). We will present the evolution of the exigent scenario as calculated at different forecast initial times and compare these forecast worst case estimates to the actual damage. We will also explore methods to quantify deviations from the mG assumption and their impact on our analysis. The EAT also provides the least damaging (or best case) scenario and this enables us to present the relative uncertainty of the damage forecasts and how this uncertainty evolves in terms of worst case minus best case damage maps.

  17. 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

  18. 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

  19. Market turning points forecasting using wavelet analysis

    NASA Astrophysics Data System (ADS)

    Bai, Limiao; Yan, Sen; Zheng, Xiaolian; Chen, Ben M.

    2015-11-01

    Based on the system adaptation framework we previously proposed, a frequency domain based model is developed in this paper to forecast the major turning points of stock markets. This system adaptation framework has its internal model and adaptive filter to capture the slow and fast dynamics of the market, respectively. The residue of the internal model is found to contain rich information about the market cycles. In order to extract and restore its informative frequency components, we use wavelet multi-resolution analysis with time-varying parameters to decompose this internal residue. An empirical index is then proposed based on the recovered signals to forecast the market turning points. This index is successfully applied to US, UK and China markets, where all major turning points are well forecasted.

  20. Thin-Slice Forecasts of Gubernatorial Elections

    PubMed Central

    Benjamin, Daniel J.; Shapiro, Jesse M.

    2010-01-01

    We showed 10-second, silent video clips of unfamiliar gubernatorial debates to a group of experimental participants and asked them to predict the election outcomes. The participants’ predictions explain more than 20 percent of the variation in the actual two-party vote share across the 58 elections in our study, and their importance survives a range of controls, including state fixed effects. In a horse race of alternative forecasting models, participants’ forecasts significantly outperform economic variables in predicting vote shares, and are comparable in predictive power to a measure of incumbency status. Participants’ forecasts seem to rest on judgments of candidates’ personal attributes (such as likeability), rather than inferences about candidates’ policy positions. Though conclusive causal inference is not possible in our context, our findings may be seen as suggestive evidence of a causal effect of candidate appeal on election outcomes. PMID:20431718

  1. 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.

  2. 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.

  3. 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.

  4. What might we learn from climate forecasts?

    PubMed Central

    Smith, Leonard A.

    2002-01-01

    Most climate models are large dynamical systems involving a million (or more) variables on big computers. Given that they are nonlinear and not perfect, what can we expect to learn from them about the earth's climate? How can we determine which aspects of their output might be useful and which are noise? And how should we distribute resources between making them “better,” estimating variables of true social and economic interest, and quantifying how good they are at the moment? Just as “chaos” prevents accurate weather forecasts, so model error precludes accurate forecasts of the distributions that define climate, yielding uncertainty of the second kind. Can we estimate the uncertainty in our uncertainty estimates? These questions are discussed. Ultimately, all uncertainty is quantified within a given modeling paradigm; our forecasts need never reflect the uncertainty in a physical system. PMID:11875200

  5. 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.

  6. Affective forecasting and the Big Five

    PubMed Central

    Hoerger, Michael; Quirk, Stuart W.

    2011-01-01

    Recent studies on affective forecasting clarify that the emotional reactions people anticipate often differ markedly from those they actually experience in response to affective stimuli and events. However, core personality differences in affective forecasting have received limited attention, despite their potential relevance to choice behavior. In the present study, 226 college undergraduates rated their anticipated and experienced reactions to the emotionally-evocative event of Valentine’s Day and completed a measure of the Big Five personality traits – neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness – and their facet scales. Neuroticism and extraversion were associated with baseline mood, experienced emotional reactions, and anticipated emotional reactions. The present findings hold implications for the study of individual differences in affective forecasting, personality theory, and interventions research. PMID:22021944

  7. 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.

  8. 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.

  9. 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.

  10. 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.

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

    DOE PAGES

    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 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

  12. 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. Copyright ?? 2010 Royal Meteorological Society.

  13. 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.

  14. 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).

  15. 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

  16. Requirements of Operational Verification of the NWSRFS-ESP Forecasts

    NASA Astrophysics Data System (ADS)

    Imam, B.; Werner, K.; Hartmann, H.; Sorooshian, S.; Pritchard, E.

    2006-12-01

    Forecast verification is the process of determining the quality of forecasts. This requires the utilization of quality measures that summarize one or more aspects of the relationship between forecasts and observations. Technically, the three main objectives of forecast verification are (a) monitoring, (b) improving, and (c) comparing the quality of different forecasting systems. However, users of forecast verification results range from administrators, who want to know the value of investing in forecast system improvement to forecasters and modelers, who want to assess areas of improving their own predictions, to forecast users, who weigh their decision based not only on the forecast but also on the perceived quality of such forecast. Our discussions with several forecasters and hydrologists in charge at various River Forecast Centers (RFCs) indicated that operational hydrologists view verification in a broader sense than their counterparts within the meteorological community. Their view encompasses verification as a possible tool in determining whether a forecast is ready for issuance as an "official" product or that it needs more work. In addition to the common challenges associated with verification of monthly and seasonal probabilistic forecasts. which include determining and obtaining the appropriate size of "forecast-observation" pairs data set, operational verification also requires the consideration of verification strategies for short-term forecasts. Under such condition, the identification of conditional verification (i.e., similar conditions) samples, tracking model states, input, and output, relative to their climatology, and the establishment of links between the forecast issuance, verification, and simulation components of the forecast system become important. In this presentation, we address the impacts of such view on the potential requirements of an operational verification system for the Ensemble Streamflow Prediction (ESP) component of the

  17. Incorporate Hydrologic Forecast for Real-Time Reservoir Operations

    NASA Astrophysics Data System (ADS)

    Zhao, T.; Cai, X.; Zhao, J.

    2011-12-01

    Advances in weather forecasting, hydrologic modeling, and hydro-climatic teleconnection relationships have significantly improved streamflow forecast precision and lead-time. The advances provide great opportunities to improve the operation rules of water resources systems, for example, updating reservoir operation curves using long-term forecast, or even replacing operation rules by real-time optimization and simulation models utilizing various streamflow forecast products. However, incorporation of forecast for real-time optimization of reservoir operation needs more understanding of the forecast uncertainty (FU) evolution with forecast horizon (FH, the advance time of a forecast) and the complicating effect of FU and FH. Increasing horizon may provide more information for decision making in a long time framework but with increasing error and less reliable information. This presentation addresses the challenges on the use of hydrologic forecast for real-time reservoir operations through the following two particular studies: 1) Evaluating the effectiveness of the various hydrological forecast products for reservoir operation with an explicit simulation of dynamic evolution of uncertainties involved in those products. A hypothetical example shows that optimal reservoir operation varies with the hydrologic forecast products. The utility of the reservoir operation with ensemble or probabilistic streamflow forecast (with a probabilistic uncertainty distribution) is the highest compared to deterministic streamflow forecast (DSF) with the forecast uncertainty represented in the form of deterministic forecast errors and DSF-based probabilistic streamflow forecast with the forecast uncertainty represented by a conditional distribution of forecast uncertainty for a given DSF. 2) Identifying an effective forecast horizon (EFH) under a limited inflow forecast considering the complicating effect of FH and FU, as well as streamflow variability and reservoir characteristics

  18. Drought Monitoring and Forecasting Using the Princeton/U Washington National Hydrologic Forecasting System

    NASA Astrophysics Data System (ADS)

    Wood, E. F.; Yuan, X.; Roundy, J. K.; Lettenmaier, D. P.; Mo, K. C.; Xia, Y.; Ek, M. B.

    2011-12-01

    Extreme hydrologic events in the form of droughts or floods are a significant source of social and economic damage in many parts of the world. Having sufficient warning of extreme events allows managers to prepare for and reduce the severity of their impacts. A hydrologic forecast system can give seasonal predictions that can be used by mangers to make better decisions; however there is still much uncertainty associated with such a system. Therefore it is important to understand the forecast skill of the system before transitioning to operational usage. Seasonal reforecasts (1982 - 2010) from the NCEP Climate Forecast System (both version 1 (CFS) and version 2 (CFSv2), Climate Prediction Center (CPC) outlooks and the European Seasonal Interannual Prediction (EUROSIP) system, are assessed for forecasting skill in drought prediction across the U.S., both singularly and as a multi-model system The Princeton/U Washington national hydrologic monitoring and forecast system is being implemented at NCEP/EMC via their Climate Test Bed as the experimental hydrological forecast system to support U.S. operational drought prediction. Using our system, the seasonal forecasts are biased corrected, downscaled and used to drive the Variable Infiltration Capacity (VIC) land surface model to give seasonal forecasts of hydrologic variables with lead times of up to six months. Results are presented for a number of events, with particular focus on the Apalachicola-Chattahoochee-Flint (ACF) River Basin in the South Eastern United States, which has experienced a number of severe droughts in recent years and is a pilot study basin for the National Integrated Drought Information System (NIDIS). The performance of the VIC land surface model is evaluated using observational forcing when compared to observed streamflow. The effectiveness of the forecast system to predict streamflow and soil moisture is evaluated when compared with observed streamflow and modeled soil moisture driven by

  19. 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

  20. Forecasting in foodservice: model development, testing, and evaluation.

    PubMed

    Miller, J L; Thompson, P A; Orabella, M M

    1991-05-01

    This study was designed to develop, test, and evaluate mathematical models appropriate for forecasting menu-item production demand in foodservice. Data were collected from residence and dining hall foodservices at Ohio State University. Objectives of the study were to collect, code, and analyze the data; develop and test models using actual operation data; and compare forecasting results with current methods in use. Customer count was forecast using deseasonalized simple exponential smoothing. Menu-item demand was forecast by multiplying the count forecast by a predicted preference statistic. Forecasting models were evaluated using mean squared error, mean absolute deviation, and mean absolute percentage error techniques. All models were more accurate than current methods. A broad spectrum of forecasting techniques could be used by foodservice managers with access to a personal computer and spread-sheet and database-management software. The findings indicate that mathematical forecasting techniques may be effective in foodservice operations to control costs, increase productivity, and maximize profits.

  1. 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)

  2. 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.

  3. Forecasting in foodservice: model development, testing, and evaluation.

    PubMed

    Miller, J L; Thompson, P A; Orabella, M M

    1991-05-01

    This study was designed to develop, test, and evaluate mathematical models appropriate for forecasting menu-item production demand in foodservice. Data were collected from residence and dining hall foodservices at Ohio State University. Objectives of the study were to collect, code, and analyze the data; develop and test models using actual operation data; and compare forecasting results with current methods in use. Customer count was forecast using deseasonalized simple exponential smoothing. Menu-item demand was forecast by multiplying the count forecast by a predicted preference statistic. Forecasting models were evaluated using mean squared error, mean absolute deviation, and mean absolute percentage error techniques. All models were more accurate than current methods. A broad spectrum of forecasting techniques could be used by foodservice managers with access to a personal computer and spread-sheet and database-management software. The findings indicate that mathematical forecasting techniques may be effective in foodservice operations to control costs, increase productivity, and maximize profits. PMID:2019699

  4. Practical overview of ARIMA models for time-series forecasting

    SciTech Connect

    Pack, D.J.

    1980-01-01

    Single series analysis methodology is illustrated. The commentary summarizes the Box-Jenkins philosophy and the ARIMA model structure, with particular emphasis on practical aspects of application, forecast interpretation, strengths weaknesses, and comparison to other time series forecasting approaches. (GHT)

  5. Wind power forecasting in U.S. Electricity markets

    SciTech Connect

    Botterud, Audun; Wang, Jianhui; Miranda, Vladimiro; Bessa, Ricardo J.

    2010-04-15

    Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts. (author)

  6. 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

  7. An Algorithm Combining for Objective Prediction with Subjective Forecast Information

    NASA Astrophysics Data System (ADS)

    Choi, JunTae; Kim, SooHyun

    2016-04-01

    As direct or post-processed output from numerical weather prediction (NWP) models has begun to show acceptable performance compared with the predictions of human forecasters, many national weather centers have become interested in automatic forecasting systems based on NWP products alone, without intervention from human forecasters. The Korea Meteorological Administration (KMA) is now developing an automatic forecasting system for dry variables. The forecasts are automatically generated from NWP predictions using a post processing model (MOS). However, MOS cannot always produce acceptable predictions, and sometimes its predictions are rejected by human forecasters. In such cases, a human forecaster should manually modify the prediction consistently at points surrounding their corrections, using some kind of smart tool to incorporate the forecaster's opinion. This study introduces an algorithm to revise MOS predictions by adding a forecaster's subjective forecast information at neighbouring points. A statistical relation between two forecast points - a neighbouring point and a dependent point - was derived for the difference between a MOS prediction and that of a human forecaster. If the MOS prediction at a neighbouring point is updated by a human forecaster, the value at a dependent point is modified using a statistical relationship based on linear regression, with parameters obtained from a one-year dataset of MOS predictions and official forecast data issued by KMA. The best sets of neighbouring points and dependent point are statistically selected. According to verification, the RMSE of temperature predictions produced by the new algorithm was slightly lower than that of the original MOS predictions, and close to the RMSE of subjective forecasts. For wind speed and relative humidity, the new algorithm outperformed human forecasters.

  8. 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...

  9. A pan-African Flood Forecasting System

    NASA Astrophysics Data System (ADS)

    Thiemig, V.; Bisselink, B.; Pappenberger, F.; Thielen, J.

    2014-05-01

    The African Flood Forecasting System (AFFS) is a probabilistic flood forecast system for medium- to large-scale African river basins, with lead times of up to 15 days. The key components are the hydrological model LISFLOOD, the African GIS database, the meteorological ensemble predictions of the ECMWF and critical hydrological thresholds. In this paper the predictive capability is investigated in a hindcast mode, by reproducing hydrological predictions for the year 2003 where important floods were observed. Results were verified with ground measurements of 36 subcatchments as well as with reports of various flood archives. Results showed that AFFS detected around 70% of the reported flood events correctly. In particular, the system showed good performance in predicting riverine flood events of long duration (>1 week) and large affected areas (>10 000 km2) well in advance, whereas AFFS showed limitations for small-scale and short duration flood events. The case study for "Save flooding" illustrated the good performance of AFFS in forecasting timing and severity of the floods, gave an example of the clear and concise output products, and showed that the system is capable of producing flood warnings even in ungauged river basins. Hence, from a technical perspective, AFFS shows a large potential as an operational pan-African flood forecasting system, although issues related to the practical implication will still need to be investigated.

  10. 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.

  11. Local Air Quality Conditions and Forecasts

    MedlinePlus

    ... Location Map Center Forecast AQI Current AQI Current Ozone Current PM AQI Loop Ozone Loop PM Loop Action Day Maps by Monitor ... Partners Kids Movies NAQ Conferences NOAA Older Adults Ozone Particle Pollution (PM2.5, PM10) Publications Publicaciones (En ...

  12. Forecasting catastrophe by exploiting chaotic dynamics

    SciTech Connect

    Stewart, H.B.; Lansbury, A.N.

    1990-01-01

    Our purpose here is to introduce a variation on the theme of short term forecasting from a chaotic time series. We show that for the lowest-dimensional chaotic attractors, it is possible to predict incipient catastrophes, or crises, by examining time series data taken near the catastrophic bifurcation threshold, but always remaining on the safe side of the threshold.

  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 Enrollments during Court-Ordered Desegregation.

    ERIC Educational Resources Information Center

    Morrison, Peter A.

    This paper considers the distinctive issues demographers face when they must forecast enrollments in a context of court-ordered desegregation. Specifically, it examines whether magnet schools strengthen a district's overall attractiveness to enrollees from outside, or whether they only siphon students away from other nonmagnet schools within the…

  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. 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.

  17. Forecasting sudden changes in environmental pollution patterns.

    PubMed

    Olascoaga, María J; Haller, George

    2012-03-27

    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.

  18. 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.

  19. 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).

  20. 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.

  1. 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,…

  2. 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.

  3. 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).

  4. Forecasting Extreme Flooding in South Asia (Invited)

    NASA Astrophysics Data System (ADS)

    Webster, P. J.

    2010-12-01

    In most years there is extensive flooding across India, Pakistan and Bangladesh. On average, 40 million people are displaced by floods in India and half that many again in Bangladesh. Occasionally, even more extensive and severe flooding occurs across South Asia. In 2007 and 2008 the Brahmaputra flooded three times causing severe disruption of commerce, agriculture and life in general. Systems set up by an international collaboration predicted these Bangladesh floods with an operational system at the 10 and 15-day horizon. These forecasts determined the risk of flooding and allowed the Bangladeshis in peril to prepare, harvesting crops and storing of household and agricultural assets. Savings in increments of annual income resulted form the forecasts. In July and August 2010, severe flooding occurred in Pakistan causing horrendous damage and loss of life. But these floods were also predictable at the 10-day time scale if the same forecasting system developed for Bangladesh had been implemented. Similar systems could be implemented in India but would require local cooperation. We describe the manner in which quantified probabilistic precipitation forecasts, coupled with hydrological models can provide useful and timely extended warnings of flooding.

  5. 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.

  6. Data mining methods for hydroclimatic forecasting

    NASA Astrophysics Data System (ADS)

    Wei, Wenge; Watkins, David W.

    2011-11-01

    Skillful streamflow forecasts at seasonal lead times may be useful to water managers seeking to provide reliable water supplies and maximize hydrosystem benefits. In this study, a class of data mining techniques, known as tree-structured models, is investigated to address the nonlinear dynamics of climate teleconnections and screen promising probabilistic streamflow forecast models for river-reservoir systems. In a case study of the Lower Colorado River system in central Texas, a number of potential predictors are evaluated for forecasting seasonal streamflow, including large-scale climate indices related to the El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and others. Results show that the tree-structured models can effectively capture the nonlinear features hidden in the data. Skill scores of probabilistic forecasts generated by both classification trees and logistic regression trees indicate that seasonal inflows throughout the system can be predicted with sufficient accuracy to improve water management, especially in the winter and spring seasons in central Texas.

  7. Educational Development and Forecasting in Socialist Societies.

    ERIC Educational Resources Information Center

    Rybalko, L.; Soloviev, E.

    Major trends and factors are discussed which are likely to influence the development of education in socialist countries over the next 20 years. There are three major sections to the paper: basic features of educational development; trends in educational development; and some aspects of educational forecasting and prospective planning. The…

  8. 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)

  9. 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.

  10. Small Area Forecasts: Policies, Results, and Evaluation.

    ERIC Educational Resources Information Center

    Southeast Michigan Council of Governments, Detroit.

    This document describes aspects of the Small Area Forecast (SAF) process, from the preparation of policy alternatives to measures to provide for evaluation. The three principle areas discussed are: (1) the six alternative sets of public policies which might be followed in the Southeast region of Michigan for meeting population needs in the areas…

  11. Wind and Load Forecast Error Model for Multiple Geographically Distributed Forecasts

    SciTech Connect

    Makarov, Yuri V.; Reyes Spindola, Jorge F.; Samaan, Nader A.; Diao, Ruisheng; Hafen, Ryan P.

    2010-11-02

    The impact of wind and load forecast errors on power grid operations is frequently evaluated by conducting multi-variant studies, where these errors are simulated repeatedly as random processes based on their known statistical characteristics. To generate these errors correctly, we need to reflect their distributions (which do not necessarily follow a known distribution law), standard deviations, auto- and cross-correlations. For instance, load and wind forecast errors can be closely correlated in different zones of the system. This paper introduces a new methodology for generating multiple cross-correlated random processes to simulate forecast error curves based on a transition probability matrix computed from an empirical error distribution function. The matrix will be used to generate new error time series with statistical features similar to observed errors. We present the derivation of the method and present some experimental results by generating new error forecasts together with their statistics.

  12. Demand forecasting using fuzzy neural computation, with special emphasis on weekend and public holiday forecasting

    SciTech Connect

    Srinivasan, D.; Chang, C.S.; Liew, A.C.

    1995-11-01

    This paper describes the implementation and forecasting results of a hybrid fuzzy neural technique, which combines neural network modeling, and techniques from fuzzy logic and fuzzy set theory for electric load forecasting. The strengths of this powerful technique lie in its ability to forecast accurately on weekdays, as well as, on weekends, public holidays, and days before and after public holidays. Furthermore, use of fuzzy logic effectively handles the load variations due to special events. The Fuzzy-Neural Network (FNN) has been extensively tested on actual data obtained from a power system for 24-hour ahead prediction based on forecast weather information. Very impressive results, with an average error of 0.62% on weekdays, 0.83% on Saturdays and 1.17% on Sundays and public holidays have been obtained. This approach avoids complex mathematical calculations and training on many years of data, and is simple to implement on a personal computer.

  13. STATUS AND PROGRESS IN PARTICULATE MATTER FORECASTING: INITIAL APPLICATION OF THE ETA- CMAQ FORECAST MODEL

    EPA Science Inventory

    This presentation reviews the status and progress in forecasting particulate matter distributions. The shortcomings in representation of particulate matter formation in current atmospheric chemistry/transport models are presented based on analyses and detailed comparisons with me...

  14. 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.

  15. Ensemble approach for hydrological forecasting in ungauged catchments

    NASA Astrophysics Data System (ADS)

    Randrianasolo, Annie; Ramos, Maria-Helena; Andreassian, Vazken

    2013-04-01

    This study focuses on the application of ensemble approaches to forecast flows in ungauged catchments. The aim is to study the best strategy to search for information in gauged "donor" basins and to transfer it to the ungauged site. We investigate what information is needed to set up a rainfall-runoff model and to perform forecast updating in real time. These two components of a flood forecasting system are thus decoupled in our approach. The methodology adopted integrates the scenarios of regional transfer of information and the scenarios of ensemble weather forecasting together in a forecasting system. The approach of ensemble forecasting is thus generalised to the particular case of hydrological forecasting in ungauged basins. The study is based on 211 catchments in France and on an archive of about 4.5 years of ensemble forecasts of rainfall, which are used for hydrological modelling on a daily time step. Flow forecasts are evaluated with special attention paid to the attributes of reliability and accuracy of the forecasts. The results show that forecast reliability in ungauged sites can be improved by using several sets of parameters from neighbour catchments, while forecast accuracy is improved with the transfer of updating information from gauged neighbour catchments.

  16. 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...

  17. 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,…

  18. 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…

  19. 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.

  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. 14 CFR 135.213 - Weather reports and forecasts.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Weather reports and forecasts. 135.213... Operating Limitations and Weather Requirements § 135.213 Weather reports and forecasts. (a) Whenever a person operating an aircraft under this part is required to use a weather report or forecast, that...

  2. 14 CFR 135.213 - Weather reports and forecasts.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Weather reports and forecasts. 135.213... Operating Limitations and Weather Requirements § 135.213 Weather reports and forecasts. (a) Whenever a person operating an aircraft under this part is required to use a weather report or forecast, that...

  3. 14 CFR 135.213 - Weather reports and forecasts.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Weather reports and forecasts. 135.213... Operating Limitations and Weather Requirements § 135.213 Weather reports and forecasts. (a) Whenever a person operating an aircraft under this part is required to use a weather report or forecast, that...

  4. 14 CFR 135.213 - Weather reports and forecasts.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Weather reports and forecasts. 135.213... Operating Limitations and Weather Requirements § 135.213 Weather reports and forecasts. (a) Whenever a person operating an aircraft under this part is required to use a weather report or forecast, that...

  5. 14 CFR 135.213 - Weather reports and forecasts.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Weather reports and forecasts. 135.213... Operating Limitations and Weather Requirements § 135.213 Weather reports and forecasts. (a) Whenever a person operating an aircraft under this part is required to use a weather report or forecast, that...

  6. 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

  7. 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

  8. Comparing High Resolution Weather Forecasts to Observations

    NASA Astrophysics Data System (ADS)

    Foley, T. A.; Smith, J. A.; Raby, J. W.

    2013-12-01

    The Advanced Research version of the Weather Research and Forecasting model (WRF) is a mesoscale numerical weather prediction (NWP) system, with a horizontal grid spacing of several kilometers to several hundred kilometers. WRF can create forecasts of finer horizontal resolution by embedding a smaller domain inside the parent domain, a process called nesting. A nest may be embedded simultaneously within a coarser-resolution (parent) model run, or run independently as a separate model forecast. Army operations require weather forecasts on a scale of one kilometer or less, an area of weather modeling known as 'terra incognita' between which large eddy simulation and traditional mesoscale NWP models are applied with most confidence. Complex terrain leads to differences in surface temperature, moisture gradients, and wind speed /wind direction, and these differences are not always well-characterized by mesoscale WRF forecasts. Differences in land surface characteristics produce air flows such as mountain/valley breezes, and sea breezes that are of vital importance to Army and Air Force operations. Atmospheric effects on commercial as well as military air platforms and any associated subsystems is of critical concern, whether for commercial flight planning or for military mission execution. The traditional model verification techniques currently used aggregate the error statistics over an entire domain (such as on the order of 100km x 100km to 500km x 500km in size), techniques which produce results that often appear smoothed and may not show the value added of higher resolution WRF output at grid resolutions of 1km or less. Point verification methods can also be ineffective due to 'double counting' errors of phase and spatial nature, and failing to capture model skill in resolving mesoscale structure. More in-depth analysis of the forecast errors are needed to deduce the various sub-regimes and temporal and spatial trends which may govern the statistics in a way which

  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. Numerical weather forecasting with anelastic model

    NASA Astrophysics Data System (ADS)

    Wójcik, Damian; Kurowski, Marcin; Piotrowski, Zbigniew; Rosa, Bogdan; Ziemiański, Michał

    2013-04-01

    Research conducted at Polish Institute of Meteorology and Water Management, National Research Institute, in collaboration with Consortium for Small Scale Modeling (COSMO) are aimed at developing new conservative dynamical core for next generation operational weather prediction model. Within the frames of the project a new prototype model has been developed. The dynamical core of the model is based on anelastic set of equation and numerics adopted from the EULAG model. An employment of EULAG allowed to profit from its desirable conservative properties and numerical robustness confirmed in number of benchmark tests and widely documented in scientific literature. The first stage of the project has been already successfully completed. Its main achievement is a hybrid model capable to compute weather forecast. The model consists of EULAG dynamical core implemented into the software environment of the operational COSMO model and basic COSMO physical parameterizations involving turbulence, friction, radiation, moist processes and surface fluxes (COSMO-EULAG). The presentation shows the case studies comparing results of 24-hour forecasts calculated via the hybrid model with analogous results obtained with the Runge-Kutta dynamical core standard for the COSMO operational applications. The experiments are performed with 2.2 km resolution over Alpine domain of operational MeteoSwiss numerical forecasts. The results demonstrate that the short-term forecasts employing different dynamical cores are qualitatively and quantitatively similar, especially in the middle and upper troposphere. Near the surface the COSMO-EULAG results, while similar to the Runge-Kutta ones, show more small-scale variability. It is seen that the anelastic approximation does not impose measurable adverse affects on the forecast. The presentation shows also results of another class of experiments. They involve 24-hour forecast with COSMO-EULAG over realistic Alpine domain with the horizontal resolutions of

  12. Forecast quality and predictability of severe extra-tropical cyclones in operational forecasts

    NASA Astrophysics Data System (ADS)

    Owen, J. S. R.; Knippertz, P.; Trzeciak, T. M.

    2012-04-01

    Severe extratropical cyclones are the most damaging weather phenomena affecting Europe, frequently causing fatalities and severe economic losses. Reliable forecasts of such events on timescales of several days are crucial to warn the population and allow mitigating action to be taken. Funded by the AXA Research Fund, this study investigates how accurately eighteen historic damaging and/or intense storms over Europe were forecast by operational numerical weather prediction (NWP) models. An automatic tracking algorithm is used to identify the cyclones from gridded fields of mean-sea level pressure. As a first step, the evolution of the storms and the synoptic conditions in which they developed is examined based on re-analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The next step is to evaluate forecast performance by the ECMWF and the UK Met Office deterministic models looking at core pressure evolution and track for different forecast lead times. Finally, ECMWF ensemble predictions are used to investigate the predictability of the investigated storms through examining the forecast spread, again for different lead times. First results indicate that the quality of the forecasts varies widely across the storms; however, they confirm previous studies in that the cyclones' core pressures are generally less well predicted than their position. The extent to which these differences can be related to the type of storm and to the ensemble spread is currently under investigation. For example, are storms with a strong diabatic influence less well forecast than those where baroclinicity dominates? Are deterministic forecasts less reliable in situations with low predictability? Additionally, the magnitude of the forecast errors will be compared to those of less intense cyclones to see whether the most intense systems stand out in terms of their forecast quality and predictability. In the longer run, this work will feed into a broader project that

  13. 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.

  14. [Explanation and forecast: relapse of juvenile offenders].

    PubMed

    Giebel, S M

    2006-01-01

    On the basis of n=82 juvenile offenders from a prison for juvenile offenders in Rheinland Pfalz the model of the logistic regression is compared with a procedure from the family of the neural nets in its efficiency to explain and predict "relapse" in form of a renewed imprisonment or prosecution /police search after dismissal. The group which can be examined is limited by the population of the prison for juvenile offenders and the explaining variables for "relapse" as "addicted to drugs" present non-metric scaling. For the explanation only probabilities for "relapse" can be indicated in this connection. By means of this probability it is possible to classify the individual case. The forecast is simulated by coincidental dividing of the data: the first part of the data is used for the explanation, the second for the forecast. With the comparison of the logistic regression with the neural nets, the superiority of neural nets in the explanation of "relapse" can be shown, since the neural nets are able to consider dependence between the explaining variables and according to that they offer a differentiated explanation. Their efficiency to predict "relapse" depends on the comparability of the distribution in the two coincidentally provided samples, the training data record for determining the explanation and the test case for the use of the explanation regarding the forecast. For optimal explanation and forecast neural nets are to be preferred to the logistic regression, since in the model with the better explanation also includes the potential for a usable better forecast. Moreover the model of the logistic regression is in fact a special case of the neural net, with a reduced complexity of the net.

  15. 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.

  16. 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.

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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.

  3. Skill assessment for an operational algal bloom forecast system

    NASA Astrophysics Data System (ADS)

    Stumpf, Richard P.; Tomlinson, Michelle C.; Calkins, Julie A.; Kirkpatrick, Barbara; Fisher, Kathleen; Nierenberg, Kate; Currier, Robert; Wynne, Timothy T.

    2009-02-01

    An operational forecast system for harmful algal blooms (HABs) in southwest Florida is analyzed for forecasting skill. The HABs, caused by the toxic dinoflagellate, Karenia brevis, lead to shellfish toxicity and to respiratory irritation. In addition to predicting new blooms and their extent, HAB forecasts are made twice weekly during a bloom event, using a combination of satellite derived image products, wind predictions, and a rule-based model derived from previous observations and research. These forecasts include: identification, intensification, transport, extent, and impact; the latter being the most significant to the public. Identification involves identifying new blooms as HABs and is validated against an operational monitoring program involving water sampling. Intensification forecasts, which are much less frequently made, can only be evaluated with satellite data on mono-specific blooms. Extent and transport forecasts of HABs are also evaluated against the water samples. Due to the resolution of the forecasts and available validation data, skill cannot be resolved at scales finer than 30 km. Initially, respiratory irritation forecasts were analyzed using anecdotal information, the only available data, which had a bias toward major respiratory events leading to a forecast accuracy exceeding 90%. When a systematic program of twice-daily observations from lifeguards was implemented, the forecast could be meaningfully assessed. The results show that the forecasts identify the occurrence of respiratory events at all lifeguard beaches 70% of the time. However, a high rate (80%) of false positive forecasts occurred at any given beach. As the forecasts were made at half to whole county level, the resolution of the validation data was reduced to county level, reducing false positives to 22% (accuracy of 78%). The study indicates the importance of systematic sampling, even when using qualitative descriptors, the use of validation resolution to evaluate forecast

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. The forecaster's added value in QPF

    NASA Astrophysics Data System (ADS)

    Turco, M.; Milelli, M.

    2010-03-01

    To the authors' knowledge there are relatively few studies that try to answer this question: "Are humans able to add value to computer-generated forecasts and warnings?". Moreover, the answers are not always positive. In particular some postprocessing method is competitive or superior to human forecast. Within the alert system of ARPA Piemonte it is possible to study in an objective manner if the human forecaster is able to add value with respect to computer-generated forecasts. Every day the meteorology group of the Centro Funzionale of Regione Piemonte produces the HQPF (Human Quantitative Precipitation Forecast) in terms of an areal average and maximum value for each of the 13 warning areas, which have been created according to meteo-hydrological criteria. This allows the decision makers to produce an evaluation of the expected effects by comparing these HQPFs with predefined rainfall thresholds. Another important ingredient in this study is the very dense non-GTS (Global Telecommunication System) network of rain gauges available that makes possible a high resolution verification. In this work we compare the performances of the latest three years of QPF derived from the meteorological models COSMO-I7 (the Italian version of the COSMO Model, a mesoscale model developed in the framework of the COSMO Consortium) and IFS (the ECMWF global model) with the HQPF. In this analysis it is possible to introduce the hypothesis test developed by Hamill (1999), in which a confidence interval is calculated with the bootstrap method in order to establish the real difference between the skill scores of two competitive forecasts. It is important to underline that the conclusions refer to the analysis of the Piemonte operational alert system, so they cannot be directly taken as universally true. But we think that some of the main lessons that can be derived from this study could be useful for the meteorological community. In details, the main conclusions are the following

  9. 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.

  10. 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.

  11. Appraisal of Forecast Value for Groundwater Resources Management

    NASA Astrophysics Data System (ADS)

    Brown, C.; Rogers, P.

    2004-05-01

    Seasonal climate forecasts present an opportunity to increase the efficiency with which water resources are managed. However, the probabilistic nature of forecasts poses challenges to potential users and complicates evaluation of the forecasts' quality and value. In this study we use Bayesian decision modeling to evaluate the performance of a seasonal precipitation forecast. We generate an optimal decision map by which probabilistic categorical forecasts are re-categorized and evaluated. In this way, forecast performance is assessed not in terms of the observed climate state but rather in terms of the decision indicated by the forecast. Preposterior analysis via stochastic dynamic programming is used to determine the expected value of the forecast. The application setting is the Palar River basin in Tamil Nadu, India, where demand for water exceeds economically available resources leading to income loss, economic displacement and environmental degradation. Instead of targeting forecasts for use by farmers, we propose that water managers use forecasts to set economic parameters to signal the expected availability of water in the coming season. The economic signal promotes efficient use of water while mitigating the farmers' personal risk of forecast-based decisions.

  12. 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

  13. Real-time forecasting following a damaging earthquake

    NASA Astrophysics Data System (ADS)

    Marzocchi, Warner; Lombardi, Anna Maria

    2009-11-01

    We describe the results of a prospective, real-time earthquake forecast experiment made during a seismic emergency. A Mw 6.3 earthquake struck the city of L'Aquila, Italy on April 6, 2009, causing hundreds of deaths and vast damage. Immediately following this event, we began producing daily earthquake forecasts for the region, and we provided these forecasts to Civil Protection - the agency responsible for managing the emergency. The forecasts are based on a stochastic model that combines the Gutenberg-Richter distribution of earthquake magnitudes and power-law decay in space and time of triggered earthquakes. The results from the first month following the L'Aquila earthquake exhibit a good fit between forecasts and observations, indicating that accurate earthquake forecasting is now a realistic goal. Our experience with this experiment demonstrates an urgent need for a connection between probabilistic forecasts and decision-making in order to establish - before crises - quantitative and transparent protocols for decision support.

  14. Hourly load forecasting using artificial neural networks. Final report

    SciTech Connect

    Khotanzad, A.

    1995-09-01

    An artificial neural network short-term load forecaster (ANNSTLF) and an artificial neural network (ANN) based temperature forecaster have been developed by Southern Methodist University under contracts RP2473-44 and RP3573-4. ANNSTLF can produce hourly load forecasts for one to 168 hours ahead (one to seven days ahead) with errors ranging from 2 to 4% depending on utility size and characteristics. Implementation of ANNSTLF requires an initial training with historical hourly load and weather data. Two weather parameters, temperature and relative humidity, from either one or multiple locations can be utilized. In the operational phase, the previous day`s load and weather data and hourly weather forecasts are needed. The temperature forecaster can generate hourly temperature forecasts from the predicted values for high and low temperatures of future days. Both forecasters run on a PC platform under the MS-DOS operating system. The development of ANNSTLF is based on decomposition of the load-weather relationship into three distinct trends: Weekly, daily, and hourly. Each trend is modeled by a separate module containing several multi-layer feed-forward ANNs trained by the back-propagation learning rule. The forecasts produced by each module are combined by adaptive filters to arrive at the final forecast. During the forecasting phase, the parameters of the ANNs within each module are adoptively changed according to the latest forecast accuracy. The temperature forecaster consists of a single ANN that requires the previous day`s hourly temperatures and the next day`s predicted high and low temperatures as inputs. The resulting hourly forecasts are adoptively scaled to assure that the high and low temperatures match their respective predictions. The system is capable of forecasting up to seven days ahead. ANNSTLF has been implemented at twenty utilities across the nation and is being used on-Ene by several of them.

  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. Neural network based short term load forecasting

    SciTech Connect

    Lu, C.N.; Wu, H.T. . Dept. of Electrical Engineering); Vemuri, S. . Controls and Composition Div.)

    1993-02-01

    The artificial neural network (ANN) technique for short term load forecasting (STLF) has been proposed by several authors, and gained a lot of attention recently. In order to evaluate ANN as a viable technique for STLF, one has to evaluate the performance of ANN methodology for practical considerations of STLF problems. This paper makes an attempt to address these issues. The paper presents the results of a study to investigate whether the ANN model is system dependent, and/or case dependent. Data from two utilities were used in modeling and forecasting. In addition, the effectiveness of a next 24 hour ANN model is predicting 24 hour load profile at one time was compared with the traditional next one hour ANN model.

  17. Hurricane track forecast cones from fluctuations

    NASA Astrophysics Data System (ADS)

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

    2012-06-01

    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.

  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. 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.

  20. Hurricane track forecast cones from fluctuations

    PubMed Central

    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. PMID:22701776

  1. Sentinels of the Sun: Forecasting Space Weather

    NASA Astrophysics Data System (ADS)

    Poland, Arthur I.

    2006-08-01

    The story of humanity's interest in space weather may go back to prehistoric times when people at high latitudes noticed the northern lights. Interest became more acute after the development of electrical technologies such as the telegraph, and certainly during World War II when shortwave radio communication came into practical use. Solar observing actually began to be supported by the military, with the observatory at Climax, Colorado being established to monitor the Sun during the war. With the advent of satellites and manned space travel to the Moon, space weather became a seriously funded endeavor both for basic research and forecasting. In the book, Sentinels of the Sun: Forecasting Space Weather, Barbara Poppe does an excellent job of telling this story for the nonprofessional. Moreover, as a professional who has studied space weather since before humans landed on the Moon, I found the book to be a very enjoyable read.

  2. The forecaster's added value in QPF

    NASA Astrophysics Data System (ADS)

    Turco, M.; Milelli, M.

    2009-04-01

    To the authors' knowledge there are relatively few studies that try to answer this topic: "Are humans able to add value to computer-generated forecasts and warnings ?". Moreover, the answers are not always positive. In particular some postprocessing method is competitive or superior to human forecast (see for instance Baars et al., 2005, Charba et al., 2002, Doswell C., 2003, Roebber et al., 1996, Sanders F., 1986). Within the alert system of ARPA Piemonte it is possible to study in an objective manner if the human forecaster is able to add value with respect to computer-generated forecasts. Every day the meteorology group of the Centro Funzionale of Regione Piemonte produces the HQPF (Human QPF) in terms of an areal average for each of the 13 regional warning areas, which have been created according to meteo-hydrological criteria. This allows the decision makers to produce an evaluation of the expected effects by comparing these HQPFs with predefined rainfall thresholds. Another important ingredient in this study is the very dense non-GTS network of rain gauges available that makes possible a high resolution verification. In this context the most useful verification approach is the measure of the QPF and HQPF skills by first converting precipitation expressed as continuous amounts into ‘‘exceedance'' categories (yes-no statements indicating whether precipitation equals or exceeds selected thresholds) and then computing the performances for each threshold. In particular in this work we compare the performances of the latest three years of QPF derived from two meteorological models COSMO-I7 (the Italian version of the COSMO Model, a mesoscale model developed in the framework of the COSMO Consortium) and IFS (the ECMWF global model) with the HQPF. In this analysis it is possible to introduce the hypothesis test developed by Hamill (1999), in which a confidence interval is calculated with the bootstrap method in order to establish the real difference between the

  3. 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).

  4. 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.

  5. 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.

  6. Neural net forecasting for geomagnetic activity

    NASA Technical Reports Server (NTRS)

    Hernandez, J. V.; Tajima, T.; Horton, W.

    1993-01-01

    We use neural nets to construct nonlinear models to forecast the AL index given solar wind and interplanetary magnetic field (IMF) data. We follow two approaches: (1) the state space reconstruction approach, which is a nonlinear generalization of autoregressive-moving average models (ARMA) and (2) the nonlinear filter approach, which reduces to a moving average model (MA) in the linear limit. The database used here is that of Bargatze et al. (1985).

  7. Forecasting hotspots using predictive visual analytics approach

    DOEpatents

    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.

  8. 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.

  9. Coastal Change Forecasting and Verification (Invited)

    NASA Astrophysics Data System (ADS)

    Plant, N. G.; Stockdon, H. F.; Sallenger, A. H.

    2009-12-01

    As with other recent hurricanes, Hurricane Ike, which made landfall near Galveston, TX in 2008 caused extensive change to coastal beach and dune topography near the landfall location. Forecasts of the expected coastal response to landfalling hurricanes are required for both short-term and long-term planning associated with the management of coastal resources. These forecasts can be supported by a combination of observations and models. During Hurricane Ike, pre-storm topographic observations of dune height and forecasts of water levels were used to predict the extents of dune inundation and severe dune erosion. Post-storm topographic observations showed that much of the coastal dunes responded catastrophically. That is, regardless of the initial dune height, dune heights after the storm were reduced to nearly the same elevation (about 1.5 m above mean sea level). Regions with the highest surge-induced water levels were more likely to experience catastrophic failure while regions with the lowest surge levels were more likely to experience partial failure or no change. These observations are consistent with previous observations of dune response to storms. A statistical model that predicts dune height changes given the initial dune height and storm surge elevations has been developed. We compared predictions from our statistical model to our observations. The statistical model was driven with storm surge elevations derived from both land-based water level measurements as well as using surge predictions from a numerical model (SLOSH). We found that both observed and modeled storm surge inputs yielded equally skillful predictions of dune erosion. This implies that existing pre-storm topographic data and numerical surge forecasts can be combined to make meaningful predictions of the impacts of future storms on coastal dune topography.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. Seasonal Climate Forecasts: Value to Hydropower Operations

    NASA Astrophysics Data System (ADS)

    Howard, C.

    2006-12-01

    Forecasts that directly affect society are produced by a cascade of natural processes time series models and water management decisions. Seasonal climate predictions are at the top of this cascade, but their importance is not obvious. At the bottom of the cascade are the models that influence water management and energy generation decisions -- this is the level at which the societal benefits are realized most directly. Climate predictions are stochastic and additional uncertainties and errors are introduced at each step in the cascade of models. Metrological parameters such as temperature, precipitation, wind, and solar radiation affect the loads on power systems, the thermal and hydro power generation schedules, and the consequent reservoir and river operations required to protect instream ecological systems. These outcomes are managed by predictive models of one type or another, each with limitations in model formulation and ancillary data. It is not obvious that water management might realize large benefits from seasonal climate forecasts. A suite of models is used to illustrate how decisions are made for hydroelectric operations and discusses the benefits that might be expected from improvements in hydrologic forecasting.

  15. 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

  16. Forecasting Urban Expansion Based on Night Lights

    NASA Astrophysics Data System (ADS)

    Stathakis, D.

    2016-06-01

    Forecasting urban expansion models are a very powerful tool in the hands of urban planners in order to anticipate and mitigate future urbanization pressures. In this paper, a linear regression forecasting urban expansion model is implemented based on the annual composite night lights time series available from National Oceanic and Atmospheric Administration (NOAA). The product known as 'stable lights' is used in particular, after it has been corrected with a standard intercalibration process to reduce artificial year-to-year fluctuations as much as possible. Forecasting is done for ten years after the end of the time series. Because the method is spatially explicit the predicted expansion trends are relatively accurately mapped. Two metrics are used to validate the process. The first one is the year-to-year Sum of Lights (SoL) variation. The second is the year-to-year image correlation coefficient. Overall it is evident that the method is able to provide an insight on future urbanization pressures in order to be taken into account in planning. The trends are quantified in a clear spatial manner.

  17. 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.

  18. 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.

  19. 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.

  20. Forecasting Social Unrest Using Activity Cascades.

    PubMed

    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.

  1. 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.

  2. Global disease monitoring and forecasting with Wikipedia

    DOE PAGES

    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: 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

  3. 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

  4. 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.

  5. Forecasting Social Unrest Using Activity Cascades.

    PubMed

    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

  6. 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.

  7. Forecast Skill Visualization in Climate Research

    NASA Astrophysics Data System (ADS)

    Boettinger, Michael; Roeber, Niklas; Spickermann, Dela; Polkova, Iuliia

    2015-04-01

    With ensemble simulation techniques, the uncertainty in climate simulations can be assessed, and the statistical robustness of the results is improved in comparison to single model realizations. Different ensemble generation schemes exist to represent sources of uncertainty relevant at certain timescales. In this project, we analyze near-term climate predictions, for which the initial condition uncertainty dominates the total uncertainty, and can be sampled by repeating forecasts several times with the same boundary condition, but with slightly varying initial conditions. Such experiments allow estimating the model specific ensemble spread. Ensemble simulations have added a new dimension to the data: for climate variables with a given spatial and temporal resolution, associated uncertainty (or certainty) measures can be derived. To make use of this new information, the data has to be visualized concurrently with its respective uncertainty information. For near-term climate predictions, the uncertainty is usually represented in terms of spread scores or the forecast skill. This information might have completely different spatial and temporal characteristics than the forecast variable. In this work, we show how geospatial uncertainty information is visualized today within the climate community. Furthermore, we present own approaches using state-of-the-art visualization systems like Avizo Green or Paraview. As example data set, we have used decadal climate predictions.

  8. 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.

    2014-08-01

    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 up-to-date and long series observations on burnt area and 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 area with several months lead time explaining at least 70% of the variance between rainfall and with burnt 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.

  9. 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.

  10. 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. PMID:25392913

  11. 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.

  12. 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

  13. 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.

  14. Vancouver 2010 Winter Olympics Land Surface Forecast System

    NASA Astrophysics Data System (ADS)

    Bernier, N. B.; Belair, S.; Tong, L.; Abrahamowicz, M.; Mailhot, J.

    2009-04-01

    Environment Canada's land surface forecast system developed for the Vancouver 2010 Winter Olympics is presented together with an evaluation of its performance for winters 2007-2008 and 2008-2009. The motivation for this work is threefold: it is i) application driven for the 2010 Vancouver Olympics, ii) a testbed for the panCanadian operational land surface forecast model being developed, and iii) the precursor to the fully coupled land-surface model to come. The new high resolution (100m grid size), 2D, and novel imbedded point-based land surface forecast model used to predict hourly snow and surface temperature conditions at Olympic and Paralympic Competition Sites are described. The surface systems are driven by atmospheric forcing provided by the center's operational regional forecast model for the first 48 hours and by the operational global forecast model for hours 49 to 96. The forcing fields are corrected for elevation discrepancies over the rapidly changing and complex mountainous settings of the Vancouver Olympics that arise from resolution differences. Daily 96h land surface forecasts for 2 winters and snow depth and surface air temperature observations collected at several specially deployed competition sites are used to validate the land surface model. We show that the newly implemented surface forecast model refines and improves snow depth and surface temperature forecast issued by the operational weather forecast system throughout the forecast period.

  15. 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.

  16. Verification of Medium Range Probabilistic Rainfall Forecasts Over India

    NASA Astrophysics Data System (ADS)

    Dube, Anumeha; Ashrit, Raghavendra; Singh, Harvir; Iyengar, Gopal; Rajagopal, E. N.

    2016-07-01

    Forecasting rainfall in the tropics is a challenging task further hampered by the uncertainty in the numerical weather prediction models. Ensemble prediction systems (EPSs) provide an efficient way of handling the inherent uncertainty of these models. Verification of forecasts obtained from an EPS is a necessity, to build confidence in using these forecasts. This study deals with the verification of the probabilistic rainfall forecast obtained from the National Centre for Medium Range Weather Forecasting (NCMRWF) Global Ensemble Forecast system (NGEFS) for three monsoon seasons, i.e., JJAS 2012, 2013 and 2014. Verification is done based on the Brier Score (BS) and its components (reliability, resolution and uncertainty), Brier Skill Score (BSS), reliability diagram, relative operating characteristic (ROC) curve and area under the ROC (AROC) curve. Three observation data sets are used (namely, NMSG, CPC-RFE2.0 and TRMM) for verification of forecasts and the statistics are compared. BS values for verification of NGEFS forecasts using NMSG data are the lowest, indicating that the forecasts have a better match with these observations as compared to both TRMM and CPC-RFE2.0. This is further strengthened by lower reliability, higher resolution and BSS values for verification against this data set. The ROC curve shows that lower rainfall amounts have a higher hit rate, which implies that the model has better skill in predicting these rainfall amounts. Th e reliability plots show that the events with lower probabilities were under forecasted and those with higher probabilities were over forecasted. From the current study it can be concluded that even though NGEFS is a coarse resolution EPS, the probabilistic forecast has good skill. This in turn leads to an increased confidence in issuing operational probabilistic forecasts based on NGEFS.

  17. 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.

  18. Test application of a semi-objective approach to wind forecasting for wind energy applications

    SciTech Connect

    Wegley, H.L.; Formica, W.J.

    1983-07-01

    The test application of the semi-objective (S-O) wind forecasting technique at three locations is described. The forecasting sites are described as well as site-specific forecasting procedures. Verification of the S-O wind forecasts is presented, and the observed verification results are interpreted. Comparisons are made between S-O wind forecasting accuracy and that of two previous forecasting efforts that used subjective wind forecasts and model output statistics. (LEW)

  19. The Value of Weather Forecast in Irrigation

    NASA Astrophysics Data System (ADS)

    Cai, X.; Wang, D.

    2007-12-01

    This paper studies irrigation scheduling (when and how much water to apply during the crop growth season) in the Havana Lowlands region, Illinois, using meteorological, agronomic and agricultural production data from 2002. Irrigation scheduling determines the timing and amount of water applied to an irrigated cropland during the crop growing season. In this study a hydrologic-agronomic simulation is coupled with an optimization algorithm to search for the optimal irrigation schedule under various weather forecast horizons. The economic profit of irrigated corn from an optimized scheduling is compared to that from and the actual schedule, which is adopted from a pervious study. Extended and reliable climate prediction and weather forecast are found to be significantly valuable. If a weather forecast horizon is long enough to include the critical crop growth stage, in which crop yield bears the maximum loss over all stages, much economic loss can be avoided. Climate predictions of one to two months, which can cover the critical period, might be even more beneficial during a dry year. The other purpose of this paper is to analyze farmers' behavior in irrigation scheduling by comparing the "actual" schedule to the "optimized" ones. The ultimate goal of irrigation schedule optimization is to provide information to farmers so that they may modify their behavior. In practice, farmers' decision may not follow an optimal irrigation schedule due to the impact of various factors such as natural conditions, policies, farmers' habits and empirical knowledge, and the uncertain or inexact information that they receive. In this study farmers' behavior in irrigation decision making is analyzed by comparing the "actual" schedule to the "optimized" ones. This study finds that the identification of the crop growth stage with the most severe water stress is critical for irrigation scheduling. For the case study site in the year of 2002, framers' response to water stress was found to be

  20. 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

  1. 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

  2. Forecasting Bz at Earth - an Operational Perspective

    NASA Astrophysics Data System (ADS)

    Pizzo, V. J.

    2014-12-01

    Forecasting the magnetic structure of an Earth-directed CME remains a difficult challenge, even with all the observational and modeling assets available today. Coronagraph and heliospheric imager data provide the only tangible information on CME structure near the Sun, but they specifically measure the mass distribution and offer only vague hints at the magnetic configuration. As input to models of the interplanetary medium, this information currently enables prediction of the arrival time at 1 AU within a statistical 8-hour or so window, but no forecast of the magnetic content of the CME. We discuss how the introduction of time-dependent ambient flows may impact the estimation of magnetic draping fields at the front of a CME, and we examine how the interplanetary evolution of a CME with an embedded magnetic cloud (MC) differs from that with a purely hydrodynamic driver, as in current operational models. In both cases the driver represents a localized injection of momentum, which dominates the dynamics. However, the MC case presents two additional dynamic elements: (1) the magnetic tension and high Alfven speeds in the cloud provide a rigidity that tends to preserve the initial shape of the driver; (2) the edges of the MC interact directly with the swept-up spiral magnetic ambient field, leading to erosion of the internal fields. In both cases, the hypersonic flow conditions and the geometric spreading of the predominantly radial motion tends to keep the interactions local, such that different parts of the structure may experience quite different evolution with heliocentric distance. The resulting localized deformations make the interpretation of the true configuration of such structures difficult to infer from in situ observations and severely complicate our ability to forecast accurately the magnetic structure expected at Earth. A key issue confronting any purported forecast scheme for CME magnetic content is the definition of a "good fit" between prediction and

  3. 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

  4. 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

  5. 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.

  6. 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

  7. Application of seasonal rainfall forecasts and satellite rainfall observations to crop yield forecasting for Africa

    NASA Astrophysics Data System (ADS)

    Greatrex, H. L.; Grimes, D. I. F.; Wheeler, T. R.

    2009-04-01

    Rain-fed agriculture is of utmost importance in sub-Saharan Africa; the FAO estimates that over 90% of food consumed in the region is grown in rain-fed farming systems. As the climate in sub-Saharan Africa has a high interannual variability, this dependence on rainfall can leave communities extremely vulnerable to food shortages, especially when coupled with a lack of crop management options. The ability to make a regional forecast of crop yield on a timescale of months would be of enormous benefit; it would enable both governmental and non-governmental organisations to be alerted in advance to crop failure and could facilitate national and regional economic planning. Such a system would also enable individual communities to make more informed crop management decisions, increasing their resilience to climate variability and change. It should be noted that the majority of crops in the region are rainfall limited, therefore the ability to create a seasonal crop forecast depends on the ability to forecast rainfall at a monthly or seasonal timescale and to temporally downscale this to a daily time-series of rainfall. The aim of this project is to develop a regional-scale seasonal forecast for sub-Saharan crops, utilising the General Large Area Model for annual crops (GLAM). GLAM would initially be driven using both dynamical and statistical seasonal rainfall forecasts to provide an initial estimate of crop yield. The system would then be continuously updated throughout the season by replacing the seasonal rainfall forecast with daily weather observations. TAMSAT satellite rainfall estimates are used rather than rain-gauge data due to the scarcity of ground based observations. An important feature of the system is the use of the geo-statistical method of sequential simulation to create an ensemble of daily weather inputs from both the statistical seasonal rainfall forecasts and the satellite rainfall estimates. This allows a range of possible yield outputs to be

  8. 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.

  9. 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.

  10. Short-term load forecasting with local ANN predictors

    SciTech Connect

    Drezga, I.; Rahman, S.

    1999-08-01

    A new technique for artificial neural network (ANN) based short-term load forecasting (STLF) is present in this paper. The technique implemented active selection of training data, employing the k-nearest neighbors concept. A novel concept of pilot simulation was used to determine the number of hidden units for the ANNs. The ensemble of local ANN predictors was used to produce the final forecast, whereby the iterative forecasting procedure used a simple average of ensemble ANNs. Results obtained using data from two US utilities showed forecasting accuracy comparable to those using similar techniques. Excellent forecasts for one-hour-ahead and five-days-ahead forecasting, robust behavior for sudden and large weather changes, low maximum errors and accurate peak-load predictions are some of the findings discussed in the paper.

  11. 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.

  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. Support vector regression for real-time flood stage forecasting

    NASA Astrophysics Data System (ADS)

    Yu, Pao-Shan; Chen, Shien-Tsung; Chang, I.-Fan

    2006-09-01

    SummaryFlood forecasting is an important non-structural approach for flood mitigation. The flood stage is chosen as the variable to be forecasted because it is practically useful in flood forecasting. The support vector machine, a novel artificial intelligence-based method developed from statistical learning theory, is adopted herein to establish a real-time stage forecasting model. The lags associated with the input variables are determined by applying the hydrological concept of the time of response, and a two-step grid search method is applied to find the optimal parameters, and thus overcome the difficulties in constructing the learning machine. Two structures of models used to perform multiple-hour-ahead stage forecasts are developed. Validation results from flood events in Lan-Yang River, Taiwan, revealed that the proposed models can effectively predict the flood stage forecasts one-to-six-hours ahead. Moreover, a sensitivity analysis was conducted on the lags associated with the input variables.

  14. Assessment of Tropical Cyclone Track Forecast Errors using GDAPS (UM)

    NASA Astrophysics Data System (ADS)

    Kim, D.; Kim, J.; Chang, K.; Byun, K.; Lee, J.

    2013-12-01

    After the Joint Typhoon Warning Center (JTWC) began issuing official five-day tropical cyclone (TC) forecasts in 2003, the Korea Meteorological Administration (KMA) started issuing official five-day forecasts of TCs in May 2012 after 2 year of beta test. Forming a selective consensus (SCON) by proper removal of a likely erroneous track forecast is hypothesized to be more accurate than the non-selective consensus (NCON) of all model tracks that are used for the five-day forecasts. Conceptual models describing large track error mechanisms, which are related to known tropical cyclone motion processes being misrepresented in the dynamical models, are applied to forecasts during the 2012 western North Pacific typhoon season by the Global Data Assimilation and Prediction System (GDAPS (UM N512 L70)) which is KMA's main operational model. GDAPS (UM) is one of consensus members used in making KMA's five-day forecasts and thus analysis of its track error tendencies would be useful for forming a SCON forecast. All 72-h track errors greater than 320 km are examined on the basis of the approach developed by Carr and Elsberry (2000a, b). Tropical-influenced error sources caused 37% (47 times / 126 erroneous forecasts) of the GDAPS (UM) large track forecast errors primarily because an incorrect beta effect-related process depicted by the model contributed to the erroneous forecasts. Midlatitude-influenced error sources accounted for 63% (79 times / 126 error cases) in the GDAPS (UM) erroneous forecasts mainly due to an incorrect forecast of the midlatitude system evolutions. It is proposed that KMA will be able to issue more reliable TC track information if a likely model track error is recognized by optimum use of conceptual models by Carr and Elsberry (2000a, b) and a selective consensus track is then the basis for an improved warning.

  15. 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.

  16. Energy forecasting: the troubled past of looking the future

    SciTech Connect

    Kutler, E.

    1986-01-01

    Energy forecasts have hardly been distinguished by their accuracy. Why forecasts go awry, and the impact these prominent tools have, is explored. A brief review of the record is given. Because of their allure, their popularity in he media, and their usefulness as tools in political battles, forecasts have played a significant role so far. The danger is that they represent and enhance a fix 'em up, tinkering approach, to the detriment of more efficient free-market policies.

  17. 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

  18. Hydroclimate Forecasts in Ethiopia: Benefits, Impediments, and Ways Forward

    NASA Astrophysics Data System (ADS)

    Block, P. J.

    2014-12-01

    Numerous hydroclimate forecast models, tools, and guidance exist for application across Ethiopia and East Africa in the agricultural, water, energy, disasters, and economic sectors. This has resulted from concerted local and international interdisciplinary efforts, yet little evidence exists of rapid forecast uptake and use. We will review projected benefits and gains of seasonal forecast application, impediments, and options for the way forward. Specific case studies regarding floods, agricultural-economic links, and hydropower will be reviewed.

  19. 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.

  20. Staged decision making based on probabilistic forecasting

    NASA Astrophysics Data System (ADS)

    Booister, Nikéh; Verkade, Jan; Werner, Micha; Cranston, Michael; Cumiskey, Lydia; Zevenbergen, Chris

    2016-04-01

    Flood forecasting systems reduce, but cannot eliminate uncertainty about the future. Probabilistic forecasts explicitly show that uncertainty remains. However, as - compared to deterministic forecasts - a dimension is added ('probability' or 'likelihood'), with this added dimension decision making is made slightly more complicated. A technique of decision support is the cost-loss approach, which defines whether or not to issue a warning or implement mitigation measures (risk-based method). With the cost-loss method a warning will be issued when the ratio of the response costs to the damage reduction is less than or equal to the probability of the possible flood event. This cost-loss method is not widely used, because it motivates based on only economic values and is a technique that is relatively static (no reasoning, yes/no decision). Nevertheless it has high potential to improve risk-based decision making based on probabilistic flood forecasting because there are no other methods known that deal with probabilities in decision making. The main aim of this research was to explore the ways of making decision making based on probabilities with the cost-loss method better applicable in practice. The exploration began by identifying other situations in which decisions were taken based on uncertain forecasts or predictions. These cases spanned a range of degrees of uncertainty: from known uncertainty to deep uncertainty. Based on the types of uncertainties, concepts of dealing with situations and responses were analysed and possible applicable concepts where chosen. Out of this analysis the concepts of flexibility and robustness appeared to be fitting to the existing method. Instead of taking big decisions with bigger consequences at once, the idea is that actions and decisions are cut-up into smaller pieces and finally the decision to implement is made based on economic costs of decisions and measures and the reduced effect of flooding. The more lead-time there is in