WorldWideScience

Sample records for range dispersion forecasting

  1. ENSEMBLE methods to reconcile disparate national long range dispersion forecasts

    OpenAIRE

    Mikkelsen, Torben; Galmarini, S.; Bianconi, R.; French, S.

    2003-01-01

    ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparatenational forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an a...

  2. ENSEMBLE methods to reconcile disparate national long range dispersion forecasts

    DEFF Research Database (Denmark)

    Mikkelsen, Torben; Galmarini, S.; Bianconi, R.

    2003-01-01

    ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparatenational forecasts for long-range dispersion...... emergency and meteorological forecasting centres, which may choose to integrate them directly intooperational emergency information systems, or possibly use them as a basis for future system development.......ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparatenational forecasts for long-range dispersion....... ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidentalatmospheric release of radioactive material. A series of new decision-making “ENSEMBLE” procedures...

  3. ENSEMBLE methods to reconcile disparate national long range dispersion forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Mikkelsen, T; Galmarini, S; Bianconi, R; French, S [eds.

    2003-11-01

    ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparate national forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidental atmospheric release of radioactive material. A series of new decision-making 'ENSEMBLE' procedures and Web-based software evaluation and exchange tools have been created for real-time reconciliation and harmonisation of real-time dispersion forecasts from meteorological and emergency centres across Europe during an accident. The new ENSEMBLE software tools is available to participating national emergency and meteorological forecasting centres, which may choose to integrate them directly into operational emergency information systems, or possibly use them as a basis for future system development. (au)

  4. ENSEMBLE methods to reconcile disparate national long range dispersion forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Mikkelsen, T.; Galmarini, S.; Bianconi, R.; French, S. (eds.)

    2003-11-01

    ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparate national forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidental atmospheric release of radioactive material. A series of new decision-making 'ENSEMBLE' procedures and Web-based software evaluation and exchange tools have been created for real-time reconciliation and harmonisation of real-time dispersion forecasts from meteorological and emergency centres across Europe during an accident. The new ENSEMBLE software tools is available to participating national emergency and meteorological forecasting centres, which may choose to integrate them directly into operational emergency information systems, or possibly use them as a basis for future system development. (au)

  5. Uncertainty in dispersion forecasts using meteorological ensembles

    International Nuclear Information System (INIS)

    Chin, H N; Leach, M J

    1999-01-01

    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

  6. Pollen Forecast and Dispersion Modelling

    Science.gov (United States)

    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

  7. Medium Range Forecasts Representation (and Long Range Forecasts?)

    Science.gov (United States)

    Vincendon, J.-C.

    2009-09-01

    The progress of the numerical forecasts urges us to interest us in more and more distant ranges. We thus supply more and more forecasts with term of some days. Nevertheless, precautions of use are necessary to give the most reliable and the most relevant possible information. Available in a TV bulletin or on quite other support (Internet, mobile phone), the interpretation and the representation of a medium range forecast (5 - 15 days) must be different from those of a short range forecast. Indeed, the "foresee-ability” of a meteorological phenomenon decreases gradually in the course of the ranges, it decreases all the more quickly that the phenomenon is of small scale. So, at the end of some days, the probability character of a forecast becomes very widely dominating. That is why in Meteo-France the forecasts of D+4 to D+7 are accompanied with a confidence index since around ten years. It is a figure between 1 and 5: the more we approach 5, the more the confidence in the supplied forecast is good. In the practice, an indication is supplied for period D+4 / D+5, the other one for period D+6 / D+7, every day being able to benefit from a different forecast, that is be represented in a independent way. We thus supply a global tendency over 24 hours with less and less precise symbols as the range goes away. Concrete examples will be presented. From now on two years, we also publish forecasts to D+8 / J+9, accompanied with a sign of confidence (" good reliability " or " to confirm "). These two days are grouped together on a single map because for us, the described tendency to this term is relevant on a duration about 48 hours with a spatial scale slightly superior to the synoptic scale. So, we avoid producing more than two zones of types of weather over France and we content with giving an evolution for the temperatures (still, in increase or in decline). Newspapers began to publish this information, it should soon be the case of televisions. It is particularly

  8. Dispersion Modeling Using Ensemble Forecasts Compared to ETEX Measurements.

    Science.gov (United States)

    Straume, Anne Grete; N'dri Koffi, Ernest; Nodop, Katrin

    1998-11-01

    Numerous numerical models are developed to predict long-range transport of hazardous air pollution in connection with accidental releases. When evaluating and improving such a model, it is important to detect uncertainties connected to the meteorological input data. A Lagrangian dispersion model, the Severe Nuclear Accident Program, is used here to investigate the effect of errors in the meteorological input data due to analysis error. An ensemble forecast, produced at the European Centre for Medium-Range Weather Forecasts, is then used as model input. The ensemble forecast members are generated by perturbing the initial meteorological fields of the weather forecast. The perturbations are calculated from singular vectors meant to represent possible forecast developments generated by instabilities in the atmospheric flow during the early part of the forecast. The instabilities are generated by errors in the analyzed fields. Puff predictions from the dispersion model, using ensemble forecast input, are compared, and a large spread in the predicted puff evolutions is found. This shows that the quality of the meteorological input data is important for the success of the dispersion model. In order to evaluate the dispersion model, the calculations are compared with measurements from the European Tracer Experiment. The model manages to predict the measured puff evolution concerning shape and time of arrival to a fairly high extent, up to 60 h after the start of the release. The modeled puff is still too narrow in the advection direction.

  9. Resources and Long-Range Forecasts

    Science.gov (United States)

    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. Pollen Dispersion Forecast At Regional Scale

    Science.gov (United States)

    Mangin, A.; Asthma Forecast System Team

    The forecast of the pollen concentration is generally based on an identification of sim- ilar coincidence of measured pollen at given points and meteorological data that is searched in an archive and which, with the help of experts, allows building a predicted value. This may be classified under the family of statistical approaches for forecast- ing. While palynologists make these methods more and more accurate with the help of innovative techniques of regression against empirical rules and/or evolving mathe- matical structures (e.g. neural networks), the spatial dispersion of the pollen is not or poorly considered, mainly because it requires a lot of means and technique that are not familiar to this scientific discipline. The research on pollen forecasts are presently mainly focused on the problematic of modeling the behavior of pollen trends and sea- sons at one location regardless of the topography, the locations of emitters, the relative strengths of emitter, in one word the Sspatial backgroundT. This research work was a & cedil;successful attempt to go a step further combining this SlocalT approach with a trans- & cedil;port/dispersion modeling allowing the access to mapping of concentration. The areas of interest that were selected for the demonstration of feasibility were 200x200km zones centered on Cordoba, Barcelona and Bologna and four pollen types were ex- amined, namely: Cupressaceae, Olea europaea, Poaceae and Parietaria. At the end of this three-year European project in December 2001, the system was fully deployed and validated. The multidisciplinary team will present the original methodologies that were derived for modeling the numerous aspects of this problem and also some con- clusions regarding potential extent to other areas and taxa.

  11. Long-range forecasting of intermittent streamflow

    OpenAIRE

    F. F. van Ogtrop; R. W. Vervoort; G. Z. Heller; D. M. Stasinopoulos; R. A. Rigby

    2011-01-01

    Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine th...

  12. Long-range forecasting of intermittent streamflow

    OpenAIRE

    F. F. van Ogtrop; R. W. Vervoort; G. Z. Heller; D. M. Stasinopoulos; R. A. Rigby

    2011-01-01

    Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a probabilistic statistical model to forecast streamflow 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the probabil...

  13. Meteorology and dispersion forecast in nuclear emergency in Argentina

    International Nuclear Information System (INIS)

    Kunst, Juan J.; Boutet, Luis I.; Jordan, Osvaldo D.; Hernandez, Daniel G.; Guichandut, M.E.; Chiappesoni, H.

    2008-01-01

    The 'Nuclear Regulatory Authority (NRA) (ARN in Spanish)' and the 'National Meteorological Office (NMO) (SMN in Spanish)' of Argentine has been working together on the improvement of both meteorological forecasting and dispersion prediction. In the pre-release phase of a nuclear emergency, it is very important to know the wind direction and the forecast of it, to establish the area, around the installation, where the emergency state is declared and to foresee the modification of this area. Information is also needed about deterministic effects, to begin the evacuation. At this time, meteorological forecast of wind direction and speed, and the real time meteorological information is available in the nuclear power plant (NPP) and in the Nuclear Emergency Control Centre at the ARN headquarters, together with the short-range dose calculation provided by our dispersion code, SEDA. By means of the SEDA code, we can estimate the optimum place to measure the radioactive material concentration in air, needed do to reduce evaluation uncertainties due, among others, to poor knowledge of the source term. The SEDA code allows considering atmospheric condition, and the need to reduced doses of the measuring team in charge of the measurements. For the evaluation in the medium range, we participate in the project IXP, which provides four hours and about 50 kilometres forecast. In the long-range movement of air borne radioactivity, the World Meteorological Organization (WMO), whose contact point in Argentina is the SMN, can assist us. We have developed together, with the SMN, a detailed procedure to request assistance from the WMO. In this work, we describe the combined tasks that were carried out with the SMN to define the procedures and the concepts for their application during a real emergency. The results of an application exercise carried out in 2006 are also described. (author)

  14. Combining 2-m temperature nowcasting and short range ensemble forecasting

    Directory of Open Access Journals (Sweden)

    A. Kann

    2011-12-01

    Full Text Available During recent years, numerical ensemble prediction systems have become an important tool for estimating the uncertainties of dynamical and physical processes as represented in numerical weather models. The latest generation of limited area ensemble prediction systems (LAM-EPSs allows for probabilistic forecasts at high resolution in both space and time. However, these systems still suffer from systematic deficiencies. Especially for nowcasting (0–6 h applications the ensemble spread is smaller than the actual forecast error. This paper tries to generate probabilistic short range 2-m temperature forecasts by combining a state-of-the-art nowcasting method and a limited area ensemble system, and compares the results with statistical methods. The Integrated Nowcasting Through Comprehensive Analysis (INCA system, which has been in operation at the Central Institute for Meteorology and Geodynamics (ZAMG since 2006 (Haiden et al., 2011, provides short range deterministic forecasts at high temporal (15 min–60 min and spatial (1 km resolution. An INCA Ensemble (INCA-EPS of 2-m temperature forecasts is constructed by applying a dynamical approach, a statistical approach, and a combined dynamic-statistical method. The dynamical method takes uncertainty information (i.e. ensemble variance from the operational limited area ensemble system ALADIN-LAEF (Aire Limitée Adaptation Dynamique Développement InterNational Limited Area Ensemble Forecasting which is running operationally at ZAMG (Wang et al., 2011. The purely statistical method assumes a well-calibrated spread-skill relation and applies ensemble spread according to the skill of the INCA forecast of the most recent past. The combined dynamic-statistical approach adapts the ensemble variance gained from ALADIN-LAEF with non-homogeneous Gaussian regression (NGR which yields a statistical mbox{correction} of the first and second moment (mean bias and dispersion for Gaussian distributed continuous

  15. Long-range forecasting of intermittent streamflow

    Science.gov (United States)

    van Ogtrop, F. F.; Vervoort, R. W.; Heller, G. Z.; Stasinopoulos, D. M.; Rigby, R. A.

    2011-11-01

    Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the probability of flow occurring in any of the systems. We then use the same regression framework in combination with a right-skewed distribution, the Box-Cox t distribution, to model the intensity (depth) of the non-zero streamflows. Time, seasonality and climate indices, describing the Pacific and Indian Ocean sea surface temperatures, are tested as covariates in the GAMLSS model to make probabilistic 6 and 12-month forecasts of the occurrence and intensity of streamflow. The output reveals that in the study region the occurrence and variability of flow is driven by sea surface temperatures and therefore forecasts can be made with some skill.

  16. Long-range forecasting of intermittent streamflow

    Directory of Open Access Journals (Sweden)

    F. F. van Ogtrop

    2011-11-01

    Full Text Available Long-range forecasting of intermittent streamflow in semi-arid Australia poses a number of major challenges. One of the challenges relates to modelling zero, skewed, non-stationary, and non-linear data. To address this, a statistical model to forecast streamflow up to 12 months ahead is applied to five semi-arid catchments in South Western Queensland. The model uses logistic regression through Generalised Additive Models for Location, Scale and Shape (GAMLSS to determine the probability of flow occurring in any of the systems. We then use the same regression framework in combination with a right-skewed distribution, the Box-Cox t distribution, to model the intensity (depth of the non-zero streamflows. Time, seasonality and climate indices, describing the Pacific and Indian Ocean sea surface temperatures, are tested as covariates in the GAMLSS model to make probabilistic 6 and 12-month forecasts of the occurrence and intensity of streamflow. The output reveals that in the study region the occurrence and variability of flow is driven by sea surface temperatures and therefore forecasts can be made with some skill.

  17. Evaluating FOMC forecast ranges: an interval data approach

    OpenAIRE

    Henning Fischer; Marta García-Bárzana; Peter Tillmann; Peter Winker

    2012-01-01

    The Federal Open Market Committee (FOMC) of the U.S. Federal Reserve publishes the range of members' forecasts for key macroeconomic variables, but not the distribution of forecasts within this range. To evaluate these projections, previous papers compare the midpoint of the ranges with the realized outcome. This paper proposes a new approach to forecast evaluation that takes account of the interval nature of projections. It is shown that using the conventional Mincer-Zarnowitz approach to ev...

  18. Long Range Financial Forecasting for School Districts.

    Science.gov (United States)

    Baker, Michael E.

    Public school systems infrequently project their financial outlook beyond the coming year. Yet, financial projections over a multiyear period are necessary if the financial "crises" that frequently occur in public organizations are to be avoided. This paper discusses the importance of financial forecasting and planning, the development of…

  19. Meteorological perspective on intermediate range atmospheric dispersion

    International Nuclear Information System (INIS)

    Van der Hoven, I.

    1981-01-01

    The intermediate range of atmospheric transport and diffusion is defined as those dispersion processes which take place at downwind distances of 10 to 100 kilometers from pollutant sources. Meteorologists often define this range as the mesoscale. It is the range of distances where certain environmental assessments are of concern such as the determination of significant deterioration of visibility, the effect of effluent releases from tall stacks, and the effect of pollutant sources in rural settings upon the more distant urban centers. Atmospheric diffusion theory is based on steady state conditions and spatial homogeniety. Techniques must be developed to measure the inhomogenieties, models must be devised to account for the complexities, and a data base consisting of appropriate measured meteorological parameters concurrent with tracer gas concentrations should be collected

  20. Medium Range Forecast (MRF) and Nested Grid Model (NGM)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Nested Grid Model (NGM) and Medium Range Forecast (MRF) Archive is historical digital data set DSI-6140, archived at the NOAA National Centers for Environmental...

  1. Mountain range specific analog weather forecast model for ...

    Indian Academy of Sciences (India)

    used to draw weather forecast for that mountain range in operational weather forecasting mode, three days ... various road management activities and for better .... −0.8. 1.5. 0.0. Pir Panjal range (HP). 1989–90 to 2002–03. 14. Snow day. 2.2. −4.1 ..... ed days,. S. = snow day,. N. S. = no-snow day and. P. C. = per cent correct).

  2. Medium Range Flood Forecasting for Agriculture Damage Reduction

    Science.gov (United States)

    Fakhruddin, S. H. M.

    2014-12-01

    Early warning is a key element for disaster risk reduction. In recent decades, major advancements have been made in medium range and seasonal flood forecasting. This progress provides a great opportunity to reduce agriculture damage and improve advisories for early action and planning for flood hazards. This approach can facilitate proactive rather than reactive management of the adverse consequences of floods. In the agricultural sector, for instance, farmers can take a diversity of options such as changing cropping patterns, applying fertilizer, irrigating and changing planting timing. An experimental medium range (1-10 day) flood forecasting model has been developed for Bangladesh and Thailand. It provides 51 sets of discharge ensemble forecasts of 1-10 days with significant persistence and high certainty. This type of forecast could assist farmers and other stakeholders for differential preparedness activities. These ensembles probabilistic flood forecasts have been customized based on user-needs for community-level application focused on agriculture system. The vulnerabilities of agriculture system were calculated based on exposure, sensitivity and adaptive capacity. Indicators for risk and vulnerability assessment were conducted through community consultations. The forecast lead time requirement, user-needs, impacts and management options for crops were identified through focus group discussions, informal interviews and community surveys. This paper illustrates potential applications of such ensembles for probabilistic medium range flood forecasts in a way that is not commonly practiced globally today.

  3. Long-range dependence and sea level forecasting

    CERN Document Server

    Ercan, Ali; Abbasov, Rovshan K

    2013-01-01

    This study shows that the Caspian Sea level time series possess long range dependence even after removing linear trends, based on analyses of the Hurst statistic, the sample autocorrelation functions, and the periodogram of the series. Forecasting performance of ARMA, ARIMA, ARFIMA and Trend Line-ARFIMA (TL-ARFIMA) combination models are investigated. The forecast confidence bands and the forecast updating methodology, provided for ARIMA models in the literature, are modified for the ARFIMA models. Sample autocorrelation functions are utilized to estimate the differencing lengths of the ARFIMA

  4. Anthropogenic range contractions bias species climate change forecasts

    Science.gov (United States)

    Faurby, Søren; Araújo, Miguel B.

    2018-03-01

    Forecasts of species range shifts under climate change most often rely on ecological niche models, in which characterizations of climate suitability are highly contingent on the species range data used. If ranges are far from equilibrium under current environmental conditions, for instance owing to local extinctions in otherwise suitable areas, modelled environmental suitability can be truncated, leading to biased estimates of the effects of climate change. Here we examine the impact of such biases on estimated risks from climate change by comparing models of the distribution of North American mammals based on current ranges with ranges accounting for historical information on species ranges. We find that estimated future diversity, almost everywhere, except in coastal Alaska, is drastically underestimated unless the full historical distribution of the species is included in the models. Consequently forecasts of climate change impacts on biodiversity for many clades are unlikely to be reliable without acknowledging anthropogenic influences on contemporary ranges.

  5. Short-range quantitative precipitation forecasting using Deep Learning approaches

    Science.gov (United States)

    Akbari Asanjan, A.; Yang, T.; Gao, X.; Hsu, K. L.; Sorooshian, S.

    2017-12-01

    Predicting short-range quantitative precipitation is very important for flood forecasting, early flood warning and other hydrometeorological purposes. This study aims to improve the precipitation forecasting skills using a recently developed and advanced machine learning technique named Long Short-Term Memory (LSTM). The proposed LSTM learns the changing patterns of clouds from Cloud-Top Brightness Temperature (CTBT) images, retrieved from the infrared channel of Geostationary Operational Environmental Satellite (GOES), using a sophisticated and effective learning method. After learning the dynamics of clouds, the LSTM model predicts the upcoming rainy CTBT events. The proposed model is then merged with a precipitation estimation algorithm termed Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) to provide precipitation forecasts. The results of merged LSTM with PERSIANN are compared to the results of an Elman-type Recurrent Neural Network (RNN) merged with PERSIANN and Final Analysis of Global Forecast System model over the states of Oklahoma, Florida and Oregon. The performance of each model is investigated during 3 storm events each located over one of the study regions. The results indicate the outperformance of merged LSTM forecasts comparing to the numerical and statistical baselines in terms of Probability of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), RMSE and correlation coefficient especially in convective systems. The proposed method shows superior capabilities in short-term forecasting over compared methods.

  6. Ensemble dispersion forecasting - Part 1. Concept, approach and indicators

    DEFF Research Database (Denmark)

    Galmarini, S.; Bianconi, R.; Klug, W.

    2004-01-01

    and is based on the simultaneous analysis of several model simulations by means of ad-hoc statistical treatments and parameters. The models considered in this study are operational long-range transport and dispersion models used to support decision making in various countries in case of accidental releases...

  7. Medium Range Ensembles Flood Forecasts for Community Level Applications

    Science.gov (United States)

    Fakhruddin, S.; Kawasaki, A.; Babel, M. S.; AIT

    2013-05-01

    Early warning is a key element for disaster risk reduction. In recent decades, there has been a major advancement in medium range and seasonal forecasting. These could provide a great opportunity to improve early warning systems and advisories for early action for strategic and long term planning. This could result in increasing emphasis on proactive rather than reactive management of adverse consequences of flood events. This can be also very helpful for the agricultural sector by providing a diversity of options to farmers (e.g. changing cropping pattern, planting timing, etc.). An experimental medium range (1-10 days) flood forecasting model has been developed for Bangladesh which provides 51 set of discharge ensembles forecasts of one to ten days with significant persistence and high certainty. This could help communities (i.e. farmer) for gain/lost estimation as well as crop savings. This paper describe the application of ensembles probabilistic flood forecast at the community level for differential decision making focused on agriculture. The framework allows users to interactively specify the objectives and criteria that are germane to a particular situation, and obtain the management options that are possible, and the exogenous influences that should be taken into account before planning and decision making. risk and vulnerability assessment was conducted through community consultation. The forecast lead time requirement, users' needs, impact and management options for crops, livestock and fisheries sectors were identified through focus group discussions, informal interviews and questionnaire survey.

  8. Forecasting the consequences of accidental releases of radionuclides in the atmosphere from ensemble dispersion modelling

    International Nuclear Information System (INIS)

    Galmarini, S.; Bianconi, R.; Bellasio, R.; Graziani, G.

    2001-01-01

    The RTMOD system is presented as a tool for the intercomparison of long-range dispersion models as well as a system for support of decision making. RTMOD is an internet-based procedure that collects the results of more than 20 models used around the world to predict the transport and deposition of radioactive releases in the atmosphere. It allows the real-time acquisition of model results and their intercomparison. Taking advantage of the availability of several model results, the system can also be used as a tool to support decision making in case of emergency. The new concept of ensemble dispersion modelling is introduced which is the basis for the decision-making application of RTMOD. New statistical parameters are presented that allow gathering the results of several models to produce a single dispersion forecast. The devised parameters are presented and tested on the results of RTMOD exercises

  9. Towards a medium-range coastal station fog forecasting system

    CSIR Research Space (South Africa)

    Landman, S

    2013-09-01

    Full Text Available -1 29th Annual conference of South African Society for Atmospheric Sciences (SASAS) 2013 http://sasas.ukzn.ac.za/homepage.aspx Towards a Medium-Range Coastal Station Fog Forecasting System Stephanie Landman*1, Estelle Marx1, Willem A. Landman2...

  10. Spatio-temporal behaviour of medium-range ensemble forecasts

    Science.gov (United States)

    Kipling, Zak; Primo, Cristina; Charlton-Perez, Andrew

    2010-05-01

    Using the recently-developed mean-variance of logarithms (MVL) diagram, together with the TIGGE archive of medium-range ensemble forecasts from nine different centres, we present an analysis of the spatio-temporal dynamics of their perturbations, and show how the differences between models and perturbation techniques can explain the shape of their characteristic MVL curves. We also consider the use of the MVL diagram to compare the growth of perturbations within the ensemble with the growth of the forecast error, showing that there is a much closer correspondence for some models than others. We conclude by looking at how the MVL technique might assist in selecting models for inclusion in a multi-model ensemble, and suggest an experiment to test its potential in this context.

  11. Short-range solar radiation forecasts over Sweden

    Directory of Open Access Journals (Sweden)

    T. Landelius

    2018-04-01

    Full Text Available In this article the performance for short-range solar radiation forecasts by the global deterministic and ensemble models from the European Centre for Medium-Range Weather Forecasts (ECMWF is compared with an ensemble of the regional mesoscale model HARMONIE-AROME used by the national meteorological services in Sweden, Norway and Finland. Note however that only the control members and the ensemble means are included in the comparison. The models resolution differs considerably with 18 km for the ECMWF ensemble, 9 km for the ECMWF deterministic model, and 2.5 km for the HARMONIE-AROME ensemble.The models share the same radiation code. It turns out that they all underestimate systematically the Direct Normal Irradiance (DNI for clear-sky conditions. Except for this shortcoming, the HARMONIE-AROME ensemble model shows the best agreement with the distribution of observed Global Horizontal Irradiance (GHI and DNI values. During mid-day the HARMONIE-AROME ensemble mean performs best. The control member of the HARMONIE-AROME ensemble also scores better than the global deterministic ECMWF model. This is an interesting result since mesoscale models have so far not shown good results when compared to the ECMWF models.Three days with clear, mixed and cloudy skies are used to illustrate the possible added value of a probabilistic forecast. It is shown that in these cases the mesoscale ensemble could provide decision support to a grid operator in terms of forecasts of both the amount of solar power and its probabilities.

  12. Forecasting the poleward range expansion of an intertidal species driven by climate alterations

    Directory of Open Access Journals (Sweden)

    Raquel Xavier

    2010-11-01

    Full Text Available Accurate distributional models can be used to reliably predict the response of organisms to climatic changes. Though such models have been extensively applied to terrestrial organisms, they have hardly ever been applied to the marine environment. Recent changes in the distribution of the marine gastropod Patella rustica (L. were previously modelled with Classification and Regression Tree (CART and the results revealed that increases in temperature were the major driver of those changes. However, the accuracy scores during the validation of the model were unsatisfactory, preventing its use for forecasting purposes. To fulfil this objective, in the present study a more robust method, Artificial Neural Network (ANN, was employed to produce a model suited to forecasting changes in the distribution of P. rustica. Results confirmed that the ANN model behaved better than the CART, and that it could be used for forecasting future distributional scenarios. The model forecasts that by the 2020s P. rustica is likely to expand its range at least 1000 km northwards. These results should be interpreted with caution considering the dispersal limitations of this species, but if such an expansion took place, major changes in the colonized ecosystems are expected due to the key role of limpets in intertidal communities.

  13. DROUGHT FORECASTING BASED ON MACHINE LEARNING OF REMOTE SENSING AND LONG-RANGE FORECAST DATA

    Directory of Open Access Journals (Sweden)

    J. Rhee

    2016-06-01

    Full Text Available The reduction of drought impacts may be achieved through sustainable drought management and proactive measures against drought disaster. Accurate and timely provision of drought information is essential. In this study, drought forecasting models to provide high-resolution drought information based on drought indicators for ungauged areas were developed. The developed models predict drought indices of the 6-month Standardized Precipitation Index (SPI6 and the 6-month Standardized Precipitation Evapotranspiration Index (SPEI6. An interpolation method based on multiquadric spline interpolation method as well as three machine learning models were tested. Three machine learning models of Decision Tree, Random Forest, and Extremely Randomized Trees were tested to enhance the provision of drought initial conditions based on remote sensing data, since initial conditions is one of the most important factors for drought forecasting. Machine learning-based methods performed better than interpolation methods for both classification and regression, and the methods using climatology data outperformed the methods using long-range forecast. The model based on climatological data and the machine learning method outperformed overall.

  14. Applications of the PUFF model to forecasts of volcanic clouds dispersal from Etna and Vesuvio

    Science.gov (United States)

    Daniele, P.; Lirer, L.; Petrosino, P.; Spinelli, N.; Peterson, R.

    2009-05-01

    PUFF is a numerical volcanic ash tracking model developed to simulate the behaviour of ash clouds in the atmosphere. The model uses wind field data provided by meteorological models and adds dispersion and sedimentation physics to predict the evolution of the cloud once it reaches thermodynamic equilibrium with the atmosphere. The software is intended for use in emergency response situations during an eruption to quickly forecast the position and trajectory of the ash cloud in the near (˜1-72 h) future. In this paper, we describe the first application of the PUFF model in forecasting volcanic ash dispersion from the Etna and Vesuvio volcanoes. We simulated the daily occurrence of an eruptive event of Etna utilizing ash cloud parameters describing the paroxysm of 22nd July 1998 and wind field data for the 1st September 2005-31st December 2005 time span from the Global Forecast System (GFS) model at the approximate location of the Etna volcano (38N 15E). The results show that volcanic ash particles are dispersed in a range of directions in response to changing wind field at various altitudes and that the ash clouds are mainly dispersed toward the east and southeast, although the exact trajectory is highly variable, and can change within a few hours. We tested the sensitivity of the model to the mean particle grain size and found that an increased concentration of ash particles in the atmosphere results when the mean grain size is decreased. Similarly, a dramatic variation in dispersion results when the logarithmic standard deviation of the particle-size distribution is changed. Additionally, we simulated the occurrence of an eruptive event at both Etna and Vesuvio, using the same parameters describing the initial volcanic plume, and wind field data recorded for 1st September 2005, at approximately 38N 15E for Etna and 41N 14E for Vesuvio. The comparison of the two simulations indicates that identical eruptions occurring at the same time at the two volcanic centres

  15. Dispersion Models to Forecast Traffic-related Emissions in Urban Areas

    Directory of Open Access Journals (Sweden)

    Davide Scannapieco

    2011-11-01

    Full Text Available Down the centuries, a direct link had been developed between increase in mobility and increase in wealth. On the other hand, air emission of greenhouse gases (GHG due to vehicles equipped with internal combustion engines can be regarded as a negative pressure over the environment. In the coming decades, road transport is likely to remain a significant contributor to air pollution in cities. Many urban trips cover distances of less than 6 km. Since the effectiveness of catalytic converters in the initial minutes of engine operation is small, the average emission per distance driven is very high in urban areas. Also, poorly maintained vehicles that lack exhaust aftertreatment systems are responsible for a major part of pollutant emissions. Therefore in urban areas, where higher concentrations of vehicles can be easily found, air pollution represents a critical issue, being it related with both environment and human health protection: in truth, research in recent decades consistently indicates the adverse effects of outdoor air pollution on human health, and the evidence points to air pollution stemming from transport as an important contributor to these effects. Several institutions (EEA, USEPA, etc. focused their interest in dispersion models because of their potential effectiveness to forecast atmospheric pollution. Furthermore, air micropollutants such as Polycyclic Aromatic Compounds (PAH and Metallic Trace Elements (MTE are traffic-related and although very low concentrations their dispersion is a serious issue. However, dispersion models are usefully implemented to better manage this estimation problem. Nonetheless, policy makers and land managers have to deal with model selection, taking into account that several dispersion models are available, each one of them focused on specific goals (e.g., wind transport of pollutants, land morphology implementation, evaluation of micropollutants transport, etc.; a further aspect to be considered is

  16. The Use of Principal Components in Long-Range Forecasting

    Science.gov (United States)

    Chern, Jonq-Gong

    Large-scale modes of the global sea surface temperatures and the Northern Hemisphere tropospheric circulation are described by principal component analysis. The first and the second SST components well describe the El Nino episodes, and the El Nino index (ENI), suggested in this study, is consistent with the winter Southern Oscillation index (SOI), where this ENI is a composite component of the weighted first and second SST components. The large-scale interactive modes of the coupling ocean-atmosphere system are identified by cross-correlation analysis The result shows that the first SST component is strongly correlated with the first component of geopotential height in lead time of 6 months. In the El Nino-Southern Oscillation (ENSO) evolution, the El Nino mode strongly influences the winter tropospheric circulation in the mid -latitudes for up to three leading seasons. The regional long-range variation of climate is investigated with these major components of the SST and the tropospheric circulation. In the mid-latitude, the climate of the central United States shows a weak linkage with these large-scale circulations, and the climate of the western United States appears to be consistently associated with the ENSO modes. These El Nino modes also show a dominant influence on Eastern Asia as evidenced in Taiwan Mei-Yu patterns. Possible regional long-range forecasting schemes, utilizing the complementary characteristics of the winter El Nino mode and SST anomalies, are examined with the Taiwan Mei-Yu.

  17. Ensemble dispersion forecasting - Part 2. Application and evaluation

    DEFF Research Database (Denmark)

    Galmarini, S.; Bianconi, R.; Addis, R.

    2004-01-01

    of the dispersion of ETEX release 1 and the model ensemble is compared with the monitoring data. The scope of the comparison is to estimate to what extent the ensemble analysis is an improvement with respect to the single model results and represents a superior analysis of the process evolution. (C) 2004 Elsevier...

  18. MAFALDA: An early warning modeling tool to forecast volcanic ash dispersal and deposition

    Science.gov (United States)

    Barsotti, S.; Nannipieri, L.; Neri, A.

    2008-12-01

    Forecasting the dispersal of ash from explosive volcanoes is a scientific challenge to modern volcanology. It also represents a fundamental step in mitigating the potential impact of volcanic ash on urban areas and transport routes near explosive volcanoes. To this end we developed a Web-based early warning modeling tool named MAFALDA (Modeling and Forecasting Ash Loading and Dispersal in the Atmosphere) able to quantitatively forecast ash concentrations in the air and on the ground. The main features of MAFALDA are the usage of (1) a dispersal model, named VOL-CALPUFF, that couples the column ascent phase with the ash cloud transport and (2) high-resolution weather forecasting data, the capability to run and merge multiple scenarios, and the Web-based structure of the procedure that makes it suitable as an early warning tool. MAFALDA produces plots for a detailed analysis of ash cloud dynamics and ground deposition, as well as synthetic 2-D maps of areas potentially affected by dangerous concentrations of ash. A first application of MAFALDA to the long-lasting weak plumes produced at Mt. Etna (Italy) is presented. A similar tool can be useful to civil protection authorities and volcanic observatories in reducing the impact of the eruptive events. MAFALDA can be accessed at http://mafalda.pi.ingv.it.

  19. Dispersion of aerosol particles in the free atmosphere using ensemble forecasts

    Directory of Open Access Journals (Sweden)

    T. Haszpra

    2013-10-01

    Full Text Available The dispersion of aerosol particle pollutants is studied using 50 members of an ensemble forecast in the example of a hypothetical free atmospheric emission above Fukushima over a period of 2.5 days. Considerable differences are found among the dispersion predictions of the different ensemble members, as well as between the ensemble mean and the deterministic result at the end of the observation period. The variance is found to decrease with the particle size. The geographical area where a threshold concentration is exceeded in at least one ensemble member expands to a 5–10 times larger region than the area from the deterministic forecast, both for air column "concentration" and in the "deposition" field. We demonstrate that the root-mean-square distance of any particle from its own clones in the ensemble members can reach values on the order of one thousand kilometers. Even the centers of mass of the particle cloud of the ensemble members deviate considerably from that obtained by the deterministic forecast. All these indicate that an investigation of the dispersion of aerosol particles in the spirit of ensemble forecast contains useful hints for the improvement of risk assessment.

  20. Use of medium-range numerical weather prediction model output to produce forecasts of streamflow

    Science.gov (United States)

    Clark, M.P.; Hay, L.E.

    2004-01-01

    This paper examines an archive containing over 40 years of 8-day atmospheric forecasts over the contiguous United States from the NCEP reanalysis project to assess the possibilities for using medium-range numerical weather prediction model output for predictions of streamflow. This analysis shows the biases in the NCEP forecasts to be quite extreme. In many regions, systematic precipitation biases exceed 100% of the mean, with temperature biases exceeding 3??C. In some locations, biases are even higher. The accuracy of NCEP precipitation and 2-m maximum temperature forecasts is computed by interpolating the NCEP model output for each forecast day to the location of each station in the NWS cooperative network and computing the correlation with station observations. Results show that the accuracy of the NCEP forecasts is rather low in many areas of the country. Most apparent is the generally low skill in precipitation forecasts (particularly in July) and low skill in temperature forecasts in the western United States, the eastern seaboard, and the southern tier of states. These results outline a clear need for additional processing of the NCEP Medium-Range Forecast Model (MRF) output before it is used for hydrologic predictions. Techniques of model output statistics (MOS) are used in this paper to downscale the NCEP forecasts to station locations. Forecasted atmospheric variables (e.g., total column precipitable water, 2-m air temperature) are used as predictors in a forward screening multiple linear regression model to improve forecasts of precipitation and temperature for stations in the National Weather Service cooperative network. This procedure effectively removes all systematic biases in the raw NCEP precipitation and temperature forecasts. MOS guidance also results in substantial improvements in the accuracy of maximum and minimum temperature forecasts throughout the country. For precipitation, forecast improvements were less impressive. MOS guidance increases

  1. Medium range forecasting of Hurricane Harvey flash flooding using ECMWF and social vulnerability data

    Science.gov (United States)

    Pillosu, F. M.; Jurlina, T.; Baugh, C.; Tsonevsky, I.; Hewson, T.; Prates, F.; Pappenberger, F.; Prudhomme, C.

    2017-12-01

    During hurricane Harvey the greater east Texas area was affected by extensive flash flooding. Their localised nature meant they were too small for conventional large scale flood forecasting systems to capture. We are testing the use of two real time forecast products from the European Centre for Medium-range Weather Forecasts (ECMWF) in combination with local vulnerability information to provide flash flood forecasting tools at the medium range (up to 7 days ahead). Meteorological forecasts are the total precipitation extreme forecast index (EFI), a measure of how the ensemble forecast probability distribution differs from the model-climate distribution for the chosen location, time of year and forecast lead time; and the shift of tails (SOT) which complements the EFI by quantifying how extreme an event could potentially be. Both products give the likelihood of flash flood generating precipitation. For hurricane Harvey, 3-day EFI and SOT products for the period 26th - 29th August 2017 were used, generated from the twice daily, 18 km, 51 ensemble member ECMWF Integrated Forecast System. After regridding to 1 km resolution the forecasts were combined with vulnerable area data to produce a flash flood hazard risk area. The vulnerability data were floodplains (EU Joint Research Centre), road networks (Texas Department of Transport) and urban areas (Census Bureau geographic database), together reflecting the susceptibility to flash floods from the landscape. The flash flood hazard risk area forecasts were verified using a traditional approach against observed National Weather Service flash flood reports, a total of 153 reported flash floods have been detected in that period. Forecasts performed best for SOT = 5 (hit ratio = 65%, false alarm ratio = 44%) and EFI = 0.7 (hit ratio = 74%, false alarm ratio = 45%) at 72 h lead time. By including the vulnerable areas data, our verification results improved by 5-15%, demonstrating the value of vulnerability information within

  2. Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts.

    Science.gov (United States)

    Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A

    2014-08-01

    Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate

  3. Extended-range forecasting of Chinese summer surface air temperature and heat waves

    Science.gov (United States)

    Zhu, Zhiwei; Li, Tim

    2018-03-01

    Because of growing demand from agricultural planning, power management and activity scheduling, extended-range (5-30-day lead) forecasting of summer surface air temperature (SAT) and heat waves over China is carried out in the present study via spatial-temporal projection models (STPMs). Based on the training data during 1960-1999, the predictability sources are found to propagate from Europe, Northeast Asia, and the tropical Pacific, to influence the intraseasonal 10-80 day SAT over China. STPMs are therefore constructed using the projection domains, which are determined by these previous predictability sources. For the independent forecast period (2000-2013), the STPMs can reproduce EOF-filtered 30-80 day SAT at all lead times of 5-30 days over most part of China, and observed 30-80 and 10-80 day SAT at 25-30 days over eastern China. Significant pattern correlation coefficients account for more than 50% of total forecasts at all 5-30-day lead times against EOF-filtered and observed 30-80 day SAT, and at a 20-day lead time against observed 10-80 day SAT. The STPMs perform poorly in reproducing 10-30 day SAT. Forecasting for the first two modes of 10-30 day SAT only shows useful skill within a 15-day lead time. Forecasting for the third mode of 10-30 day SAT is useless after a 10-day lead time. The forecasted heat waves over China are determined by the reconstructed SAT which is the summation of the forecasted 10-80 day SAT and the lower frequency (longer than 80-day) climatological SAT. Over a large part of China, the STPMs can forecast more than 30% of heat waves within a 15-day lead time. In general, the STPMs demonstrate the promising skill for extended-range forecasting of Chinese summer SAT and heat waves.

  4. Medium-Range Air Quality Forecast During the Beijing Olympic Games

    Science.gov (United States)

    Zhang, Y.; Smith, J.; Wang, Z.; Luo, L.; Wu, Q.

    2008-12-01

    Prior to the XXIX Olympiad in Beijing, air quality was a major concern for many athletes and visitors to the Games. In response to the need for enhanced air quality forecasts, we explored and tested the capability of medium-range air quality forecasting in a multimodel ensemble system. The system consists of the Weather Research and Forecasting Model with Chemistry module (WRF-Chem), the Fifth-Generation NCAR/PennState Mesoscale Model (MM5), and the Nested Air Quality Prediction Modeling System (NAQPMS) developed at the Institute of Atmospheric Physics (IAP). Both MM5 and NAQPMS have been in operational use to produce short-term air quality forecasts. WRFChem is the major addition to the multimodel system. Forced with the forecast from the NCEP Global Ensemble Forecast System (GENS) at the lateral boundary, the multimodel system makes ensemble air quality forecasts out to 16 days with emission scenarios that reflect measures for the Olympics, including the closing down of factories around the city and beyond, a traffic control program that reduced the number of automobiles around the city by about half and elimination of all construction activities. Analyses of two forecasts are presented in this study. They were made on 5 August 2008 and 8 August 2008, both covering the entire Olympic period. Each forecast consists of three ensemble members that were produced with the same regional model but were forced by the control and two 'extremes' of the GENS forecast. The two extreme members were hand-picked to represent the best and worst case scenarios. The forecasts are evaluated with observations taken during the Olympic Games that include satellite observations, in-situ meteorological stations, LIDAR and air quality observations at the IAP tower site, 1 km away from the 'Bird Nest'. The analyses show good model skill in the first 3 days and generally satisfactory after 96 hours, with a successful forecast of potential pollution episode on 20 August 2008. The challenge

  5. Dispersal Kernel Determines Symmetry of Spread and Geographical Range for an Insect

    International Nuclear Information System (INIS)

    Holland, J.D.

    2009-01-01

    The distance from a source patch that dispersing insects reach depends on the number of dispersers, or random draws from a probability density function called a dispersal kernel, and the shape of that kernel. This can cause asymmetrical dispersal between habitat patches that produce different numbers of dispersers. Spatial distributions based on these dynamics can explain several ecological patterns including mega populations and geographic range boundaries. I hypothesized that a locally extirpated long horned beetle, the sugar maple borer, has a new geographical range shaped primarily by probabilistic dispersal distances. I used data on occurrence from Ontario, Canada to construct a model of geographical range in Indiana, USA based on maximum dispersal distance scaled by habitat area. This model predicted the new range boundary within 500 m very accurately. This beetle may be an ideal organism for exploring spatial dynamics driven by dispersal.

  6. Study on The Extended Range Weather Forecast of Low Frequency Signal Based on Period Analysis Method

    Science.gov (United States)

    Li, X.

    2016-12-01

    Although many studies have explored the MJO and its application for weather forecasting, low-frequency oscillation has been insufficiently studied for the extend range weather forecasting over middle and high latitudes. In China, low-frequency synoptic map is a useful tool for meteorological operation department to forecast extend range weather. It is therefore necessary to develop objective methods to serve the need for finding low-frequency signal, interpretation and application of this signal in the extend range weather forecasting. In this paper, method of Butterworth band pass filter was applied to get low-frequency height field at 500hPa from 1980 to 2014 by using NCEP/NCAR daily grid data. Then period analysis and optimal subset regression methods were used to process the low frequency data of 150 days before the first forecast day and extend the low frequency signal of 500hPa low-frequency high field to future 30 days in the global from June to August during 2011-2014. Finally, the results were test. The main results are as follows: (1) In general, the fitting effect of low frequency signals of 500hPa low-frequency height field by period analysis in the northern hemisphere was better than that in the southern hemisphere, and was better in the low latitudes than that in the high latitudes. The fitting accuracy gradually reduced with the increase of forecast time length, which tended to be stable during the late forecasting period. (2) The fitting effects over the 6 key regions in China showed that except filtering result over Xinjiang area in the first 10 days and 30 days, filtering results over the other 5 key regions throughout the whole period have passed reliability test with level more than 95%. (3) The center and scope of low and high low frequency systems can be fitted well by using the methods mentioned above, which is consist with the corresponding use of the low-frequency synoptic map for the prediction of the extended period. Application of the

  7. The Art and Science of Long-Range Space Weather Forecasting

    Science.gov (United States)

    Hathaway, David H.; Wilson, Robert M.

    2006-01-01

    Long-range space weather forecasts are akin to seasonal forecasts of terrestrial weather. We don t expect to forecast individual events but we do hope to forecast the underlying level of activity important for satellite operations and mission pl&g. Forecasting space weather conditions years or decades into the future has traditionally been based on empirical models of the solar cycle. Models for the shape of the cycle as a function of its amplitude become reliable once the amplitude is well determined - usually two to three years after minimum. Forecasting the amplitude of a cycle well before that time has been more of an art than a science - usually based on cycle statistics and trends. Recent developments in dynamo theory -the theory explaining the generation of the Sun s magnetic field and the solar activity cycle - have now produced models with predictive capabilities. Testing these models with historical sunspot cycle data indicates that these predictions may be highly reliable one, or even two, cycles into the future.

  8. Meta-heuristic CRPS minimization for the calibration of short-range probabilistic forecasts

    Science.gov (United States)

    Mohammadi, Seyedeh Atefeh; Rahmani, Morteza; Azadi, Majid

    2016-08-01

    This paper deals with the probabilistic short-range temperature forecasts over synoptic meteorological stations across Iran using non-homogeneous Gaussian regression (NGR). NGR creates a Gaussian forecast probability density function (PDF) from the ensemble output. The mean of the normal predictive PDF is a bias-corrected weighted average of the ensemble members and its variance is a linear function of the raw ensemble variance. The coefficients for the mean and variance are estimated by minimizing the continuous ranked probability score (CRPS) during a training period. CRPS is a scoring rule for distributional forecasts. In the paper of Gneiting et al. (Mon Weather Rev 133:1098-1118, 2005), Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is used to minimize the CRPS. Since BFGS is a conventional optimization method with its own limitations, we suggest using the particle swarm optimization (PSO), a robust meta-heuristic method, to minimize the CRPS. The ensemble prediction system used in this study consists of nine different configurations of the weather research and forecasting model for 48-h forecasts of temperature during autumn and winter 2011 and 2012. The probabilistic forecasts were evaluated using several common verification scores including Brier score, attribute diagram and rank histogram. Results show that both BFGS and PSO find the optimal solution and show the same evaluation scores, but PSO can do this with a feasible random first guess and much less computational complexity.

  9. Dispersion-tailored, low-loss photonic crystal fibers for the THz range

    DEFF Research Database (Denmark)

    Nielsen, Kristian; Rasmussen, Henrik K.; Adam, Aurèle J.L.

    2009-01-01

    We have fabricated a new type of photonic crystal fibers based on a cyclic olefin copolymer, transparent in the THz range. We characterize the propagation loss, dispersion, and spatial beam profile in fibers designed for low and high dispersion.......We have fabricated a new type of photonic crystal fibers based on a cyclic olefin copolymer, transparent in the THz range. We characterize the propagation loss, dispersion, and spatial beam profile in fibers designed for low and high dispersion....

  10. Medium-range reference evapotranspiration forecasts for the contiguous United States based on multi-model numerical weather predictions

    Science.gov (United States)

    Medina, Hanoi; Tian, Di; Srivastava, Puneet; Pelosi, Anna; Chirico, Giovanni B.

    2018-07-01

    Reference evapotranspiration (ET0) plays a fundamental role in agronomic, forestry, and water resources management. Estimating and forecasting ET0 have long been recognized as a major challenge for researchers and practitioners in these communities. This work explored the potential of multiple leading numerical weather predictions (NWPs) for estimating and forecasting summer ET0 at 101 U.S. Regional Climate Reference Network stations over nine climate regions across the contiguous United States (CONUS). Three leading global NWP model forecasts from THORPEX Interactive Grand Global Ensemble (TIGGE) dataset were used in this study, including the single model ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (EC), the National Centers for Environmental Prediction Global Forecast System (NCEP), and the United Kingdom Meteorological Office forecasts (MO), as well as multi-model ensemble forecasts from the combinations of these NWP models. A regression calibration was employed to bias correct the ET0 forecasts. Impact of individual forecast variables on ET0 forecasts were also evaluated. The results showed that the EC forecasts provided the least error and highest skill and reliability, followed by the MO and NCEP forecasts. The multi-model ensembles constructed from the combination of EC and MO forecasts provided slightly better performance than the single model EC forecasts. The regression process greatly improved ET0 forecast performances, particularly for the regions involving stations near the coast, or with a complex orography. The performance of EC forecasts was only slightly influenced by the size of the ensemble members, particularly at short lead times. Even with less ensemble members, EC still performed better than the other two NWPs. Errors in the radiation forecasts, followed by those in the wind, had the most detrimental effects on the ET0 forecast performances.

  11. Prediction of kharif rice yield at Kharagpur using disaggregated extended range rainfall forecasts

    Science.gov (United States)

    Dhekale, B. S.; Nageswararao, M. M.; Nair, Archana; Mohanty, U. C.; Swain, D. K.; Singh, K. K.; Arunbabu, T.

    2017-08-01

    The Extended Range Forecasts System (ERFS) has been generating monthly and seasonal forecasts on real-time basis throughout the year over India since 2009. India is one of the major rice producer and consumer in South Asia; more than 50% of the Indian population depends on rice as staple food. Rice is mainly grown in kharif season, which contributed 84% of the total annual rice production of the country. Rice cultivation in India is rainfed, which depends largely on rains, so reliability of the rainfall forecast plays a crucial role for planning the kharif rice crop. In the present study, an attempt has been made to test the reliability of seasonal and sub-seasonal ERFS summer monsoon rainfall forecasts for kharif rice yield predictions at Kharagpur, West Bengal by using CERES-Rice (DSSATv4.5) model. These ERFS forecasts are produced as monthly and seasonal mean values and are converted into daily sequences with stochastic weather generators for use with crop growth models. The daily sequences are generated from ERFS seasonal (June-September) and sub-seasonal (July-September, August-September, and September) summer monsoon (June to September) rainfall forecasts which are considered as input in CERES-rice crop simulation model for the crop yield prediction for hindcast (1985-2008) and real-time mode (2009-2015). The yield simulated using India Meteorological Department (IMD) observed daily rainfall data is considered as baseline yield for evaluating the performance of predicted yields using the ERFS forecasts. The findings revealed that the stochastic disaggregation can be used to disaggregate the monthly/seasonal ERFS forecasts into daily sequences. The year to year variability in rice yield at Kharagpur is efficiently predicted by using the ERFS forecast products in hindcast as well as real time, and significant enhancement in the prediction skill is noticed with advancement in the season due to incorporation of observed weather data which reduces uncertainty of

  12. Using subseasonal-to-seasonal (S2S) extreme rainfall forecasts for extended-range flood prediction in Australia

    Science.gov (United States)

    White, C. J.; Franks, S. W.; McEvoy, D.

    2015-06-01

    Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal). Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S) forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR) activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

  13. Using subseasonal-to-seasonal (S2S extreme rainfall forecasts for extended-range flood prediction in Australia

    Directory of Open Access Journals (Sweden)

    C. J. White

    2015-06-01

    Full Text Available Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal. Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

  14. Application of a mesoscale forecasting model (NMM) coupled to the CALMET to develop forecast meteorology to use with the CALPUFF air dispersion model

    International Nuclear Information System (INIS)

    Radonjic, Z.; Telenta, B.; Kirklady, J.; Chambers, D.; Kleb, H.

    2006-01-01

    An air quality assessment was undertaken as part of the Environmental Assessment for the Port Hope Area Initiative. The assessment predicted potential effects associated with the remediation efforts for historic low-level radioactive wastes and construction of Long-Term Waste Management Facilities (LTWMFs) for both the Port Hope and Port Granby Projects. A necessary element of air dispersion modelling is the development of suitable meteorological data. For the Port Hope and Port Granby Projects, a meteorological station was installed in close proximity to the location of the recommended LTWMF in Port Hope. The recommended location for the Port Granby LTWMF is approximately 10 km west of the Port Hope LTWMF. Concerns were raised regarding the applicability of data collected for the Port Hope meteorological station to the Port Granby Site. To address this concern, a new method for processing meteorological data, which coupled mesoscale meteorological forecasting data the U.S. EPA CALMET meteorological data processor, was applied. This methodology is possible because a new and advanced mesoscale forecasting modelling system enables extensive numerical calculations on personal computers. As a result of this advancement, mesoscale forecasting systems can now be coupled with the CALMET meteorological data processor and the CALPUFF air dispersion modelling system to facilitate wind field estimations and air dispersion analysis. (author)

  15. On the skill of various ensemble spread estimators for probabilistic short range wind forecasting

    Science.gov (United States)

    Kann, A.

    2012-05-01

    A variety of applications ranging from civil protection associated with severe weather to economical interests are heavily dependent on meteorological information. For example, a precise planning of the energy supply with a high share of renewables requires detailed meteorological information on high temporal and spatial resolution. With respect to wind power, detailed analyses and forecasts of wind speed are of crucial interest for the energy management. Although the applicability and the current skill of state-of-the-art probabilistic short range forecasts has increased during the last years, ensemble systems still show systematic deficiencies which limit its practical use. This paper presents methods to improve the ensemble skill of 10-m wind speed forecasts by combining deterministic information from a nowcasting system on very high horizontal resolution with uncertainty estimates from a limited area ensemble system. It is shown for a one month validation period that a statistical post-processing procedure (a modified non-homogeneous Gaussian regression) adds further skill to the probabilistic forecasts, especially beyond the nowcasting range after +6 h.

  16. Evaluations of Extended-Range tropical Cyclone Forecasts in the Western North Pacific by using the Ensemble Reforecasts: Preliminary Results

    Science.gov (United States)

    Tsai, Hsiao-Chung; Chen, Pang-Cheng; Elsberry, Russell L.

    2017-04-01

    The objective of this study is to evaluate the predictability of the extended-range forecasts of tropical cyclone (TC) in the western North Pacific using reforecasts from National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System (GEFS) during 1996-2015, and from the Climate Forecast System (CFS) during 1999-2010. Tsai and Elsberry have demonstrated that an opportunity exists to support hydrological operations by using the extended-range TC formation and track forecasts in the western North Pacific from the ECMWF 32-day ensemble. To demonstrate this potential for the decision-making processes regarding water resource management and hydrological operation in Taiwan reservoir watershed areas, special attention is given to the skill of the NCEP GEFS and CFS models in predicting the TCs affecting the Taiwan area. The first objective of this study is to analyze the skill of NCEP GEFS and CFS TC forecasts and quantify the forecast uncertainties via verifications of categorical binary forecasts and probabilistic forecasts. The second objective is to investigate the relationships among the large-scale environmental factors [e.g., El Niño Southern Oscillation (ENSO), Madden-Julian Oscillation (MJO), etc.] and the model forecast errors by using the reforecasts. Preliminary results are indicating that the skill of the TC activity forecasts based on the raw forecasts can be further improved if the model biases are minimized by utilizing these reforecasts.

  17. Fitness declines towards range limits and local adaptation to climate affect dispersal evolution during climate‐induced range shifts

    DEFF Research Database (Denmark)

    Hargreaves, Anna; Bailey, Susan; Laird, Robert

    2015-01-01

    Dispersal ability will largely determine whether species track their climatic niches during climate change, a process especially important for populations at contracting (low-latitude/low-elevation) range limits that otherwise risk extinction. We investigate whether dispersal evolution....... We simulate a species distributed continuously along a temperature gradient using a spatially explicit, individual-based model. We compare range-wide dispersal evolution during climate stability vs. directional climate change, with uniform fitness vs. fitness that declines towards range limits (RLs...... at contracting range limits is facilitated by two processes that potentially enable edge populations to experience and adjust to the effects of climate deterioration before they cause extinction: (i) climate-induced fitness declines towards range limits and (ii) local adaptation to a shifting climate gradient...

  18. The European tracer experiment ETEX: a real-time long range atmospheric dispersion model exercise in different weather conditions

    International Nuclear Information System (INIS)

    Graziani, G.; )

    1998-01-01

    Two long-range tracer experiments were conducted. An inert, non-depositing tracer was being released at Rennes in France for 12 hours. The 168 sampling ground stations were run by the National Meteorological Services. Twenty-four institutions took part in the real-time forecasting of the cloud evolution using 28 long-range dispersion models. The horizontal projection of the cloud evolution over Europe was combined with real-time aerial chemical analysis. The results of the comparison indicate that a limited group of models (7-8) were capable of obtaining a good reproduction of the cloud movement throughout Europe for the first release. Large differences were, however, found in the predicted tracer concentration at a particular location. For the second release, there were large differences between the measured and calculated cloud, particularly after a front passage, which indicates that some efforts have still to be spent before consensus on the model reliability is achieved. (P.A.)

  19. Long-range dispersion interactions. I. Formalism for two heteronuclear atoms

    International Nuclear Information System (INIS)

    Zhang, J.-Y.; Mitroy, J.

    2007-01-01

    A general procedure for systematically evaluating the long-range dispersion interaction between two heteronuclear atoms in arbitrary states is outlined. The C 6 dispersion parameter can always be written in terms of sum rules involving oscillator strengths only and formulas for a number of symmetry cases are given. The dispersion coefficients for excited alkali-metal atoms interacting with the ground-state H and He are tabulated

  20. Improving Short-Range Ensemble Kalman Storm Surge Forecasting Using Robust Adaptive Inflation

    KAUST Repository

    Altaf, Muhammad

    2013-08-01

    This paper presents a robust ensemble filtering methodology for storm surge forecasting based on the singular evolutive interpolated Kalman (SEIK) filter, which has been implemented in the framework of the H∞ filter. By design, an H∞ filter is more robust than the common Kalman filter in the sense that the estimation error in the H∞ filter has, in general, a finite growth rate with respect to the uncertainties in assimilation. The computational hydrodynamical model used in this study is the Advanced Circulation (ADCIRC) model. The authors assimilate data obtained from Hurricanes Katrina and Ike as test cases. The results clearly show that the H∞-based SEIK filter provides more accurate short-range forecasts of storm surge compared to recently reported data assimilation results resulting from the standard SEIK filter.

  1. Improving Short-Range Ensemble Kalman Storm Surge Forecasting Using Robust Adaptive Inflation

    KAUST Repository

    Altaf, Muhammad; Butler, T.; Luo, X.; Dawson, C.; Mayo, T.; Hoteit, Ibrahim

    2013-01-01

    This paper presents a robust ensemble filtering methodology for storm surge forecasting based on the singular evolutive interpolated Kalman (SEIK) filter, which has been implemented in the framework of the H∞ filter. By design, an H∞ filter is more robust than the common Kalman filter in the sense that the estimation error in the H∞ filter has, in general, a finite growth rate with respect to the uncertainties in assimilation. The computational hydrodynamical model used in this study is the Advanced Circulation (ADCIRC) model. The authors assimilate data obtained from Hurricanes Katrina and Ike as test cases. The results clearly show that the H∞-based SEIK filter provides more accurate short-range forecasts of storm surge compared to recently reported data assimilation results resulting from the standard SEIK filter.

  2. Long-range dispersion interactions. III: Method for two homonuclear atoms

    International Nuclear Information System (INIS)

    Mitroy, J.; Zhang, J.-Y.

    2007-01-01

    A procedure for systematically evaluating the long-range dispersion interaction between two homonuclear atoms in arbitrary LS coupled states is outlined. The method is then used to generate dispersion coefficients for a number of the low-lying states of the Na and Mg dimers

  3. Medium-Range Forecast Skill for Extraordinary Arctic Cyclones in Summer of 2008-2016

    Science.gov (United States)

    Yamagami, Akio; Matsueda, Mio; Tanaka, Hiroshi L.

    2018-05-01

    Arctic cyclones (ACs) are a severe atmospheric phenomenon that affects the Arctic environment. This study assesses the forecast skill of five leading operational medium-range ensemble forecasts for 10 extraordinary ACs that occurred in summer during 2008-2016. Average existence probability of the predicted ACs was >0.9 at lead times of ≤3.5 days. Average central position error of the predicted ACs was less than half of the mean radius of the 10 ACs (469.1 km) at lead times of 2.5-4.5 days. Average central pressure error of the predicted ACs was 5.5-10.7 hPa at such lead times. Therefore, the operational ensemble prediction systems generally predict the position of ACs within 469.1 km 2.5-4.5 days before they mature. The forecast skill for the extraordinary ACs is lower than that for midlatitude cyclones in the Northern Hemisphere but similar to that in the Southern Hemisphere.

  4. Determining the bounds of skilful forecast range for probabilistic prediction of system-wide wind power generation

    Directory of Open Access Journals (Sweden)

    Dirk Cannon

    2017-06-01

    Full Text Available State-of-the-art wind power forecasts beyond a few hours ahead rely on global numerical weather prediction models to forecast the future large-scale atmospheric state. Often they provide initial and boundary conditions for nested high resolution simulations. In this paper, both upper and lower bounds on forecast range are identified within which global ensemble forecasts provide skilful information for system-wide wind power applications. An upper bound on forecast range is associated with the limit of predictability, beyond which forecasts have no more skill than predictions based on climatological statistics. A lower bound is defined at the lead time beyond which the resolved uncertainty associated with estimating the future large-scale atmospheric state is larger than the unresolved uncertainty associated with estimating the system-wide wind power response to a given large-scale state.The bounds of skilful ensemble forecast range are quantified for three leading global forecast systems. The power system of Great Britain (GB is used as an example because independent verifying data is available from National Grid. The upper bound defined by forecasts of GB-total wind power generation at a specific point in time is found to be 6–8 days. The lower bound is found to be 1.4–2.4 days. Both bounds depend on the global forecast system and vary seasonally. In addition, forecasts of the probability of an extreme power ramp event were found to possess a shorter limit of predictability (4.5–5.5 days. The upper bound on this forecast range can only be extended by improving the global forecast system (outside the control of most users or by changing the metric used in the probability forecast. Improved downscaling and microscale modelling of the wind farm response may act to decrease the lower bound. The potential gain from such improvements have diminishing returns beyond the short-range (out to around 2 days.

  5. The effects of phenotypic plasticity and local adaptation on forecasts of species range shifts under climate change.

    Science.gov (United States)

    Valladares, Fernando; Matesanz, Silvia; Guilhaumon, François; Araújo, Miguel B; Balaguer, Luis; Benito-Garzón, Marta; Cornwell, Will; Gianoli, Ernesto; van Kleunen, Mark; Naya, Daniel E; Nicotra, Adrienne B; Poorter, Hendrik; Zavala, Miguel A

    2014-11-01

    Species are the unit of analysis in many global change and conservation biology studies; however, species are not uniform entities but are composed of different, sometimes locally adapted, populations differing in plasticity. We examined how intraspecific variation in thermal niches and phenotypic plasticity will affect species distributions in a warming climate. We first developed a conceptual model linking plasticity and niche breadth, providing five alternative intraspecific scenarios that are consistent with existing literature. Secondly, we used ecological niche-modeling techniques to quantify the impact of each intraspecific scenario on the distribution of a virtual species across a geographically realistic setting. Finally, we performed an analogous modeling exercise using real data on the climatic niches of different tree provenances. We show that when population differentiation is accounted for and dispersal is restricted, forecasts of species range shifts under climate change are even more pessimistic than those using the conventional assumption of homogeneously high plasticity across a species' range. Suitable population-level data are not available for most species so identifying general patterns of population differentiation could fill this gap. However, the literature review revealed contrasting patterns among species, urging greater levels of integration among empirical, modeling and theoretical research on intraspecific phenotypic variation. © 2014 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.

  6. Very-short range forecasting system for 2018 Pyeonchang Winter Olympic and Paralympic games

    Science.gov (United States)

    Nam, Ji-Eun; Park, Kyungjeen; Kim, Minyou; Kim, Changhwan; Joo, Sangwon

    2016-04-01

    The 23rd Olympic Winter and the 13th Paralympic Winter Games will be held in Pyeongchang, Republic of Korea respectively from 9 to 25 February 2018 and from 9 to 18 February 2018. The Korea Meteorological Administration (KMA) and the National Institute for Meteorological Science (NIMS) have the responsibility to provide weather information for the management of the Games and the safety of the public. NIMS will carry out a Forecast Demonstration Project (FDP) and a Research and Development Project (RDP) which will be called ICE-POP 2018. These projects will focus on intensive observation campaigns to understand severe winter weathers over the Pyeongchang region, and the research results from the RDP will be used to improve the accuracy of nowcasting and very short-range forecast systems during the Games. To support these projects, NIMS developed Very-short range Data Assimilation and Prediction System (VDAPS), which is run in real time with 1 hour cycling interval and up to 12 hour forecasts. The domain is covering Korean Peninsular and surrounding seas with 1.5km horizontal resolution. AWS, windprofiler, buoy, sonde, aircraft, scatwinds, and radar radial winds are assimilated by 3DVAR on 3km resolution inner domain. The rain rate is converted into latent heat and initialized via nudging. The visibility data are also assimilated with the addition of aerosol control variable. The experiments results show the improvement in rainfall over south sea of Korean peninsula. In order to reduce excessive rainfalls during first 2 hours due to the reduced cycling interval, the data assimilation algorithm is optimized.

  7. Application of data assimilation to improve the forecasting capability of an atmospheric dispersion model for a radioactive plume

    International Nuclear Information System (INIS)

    Jeong, H.J.; Han, M.H.; Hwang, W.T.; Kim, E.H.

    2008-01-01

    Modeling an atmospheric dispersion of a radioactive plume plays an influential role in assessing the environmental impacts caused by nuclear accidents. The performance of data assimilation techniques combined with Gaussian model outputs and measurements to improve forecasting abilities are investigated in this study. Tracer dispersion experiments are performed to produce field data by assuming a radiological emergency. Adaptive neuro-fuzzy inference system (ANFIS) and linear regression filter are considered to assimilate the Gaussian model outputs with measurements. ANFIS is trained so that the model outputs are likely to be more accurate for the experimental data. Linear regression filter is designed to assimilate measurements similar to the ANFIS. It is confirmed that ANFIS could be an appropriate method for an improvement of the forecasting capability of an atmospheric dispersion model in the case of a radiological emergency, judging from the higher correlation coefficients between the measured and the assimilated ones rather than a linear regression filter. This kind of data assimilation method could support a decision-making system when deciding on the best available countermeasures for public health from among emergency preparedness alternatives

  8. Impacts of Amazonia biomass burning aerosols assessed from short-range weather forecasts

    Directory of Open Access Journals (Sweden)

    S. R. Kolusu

    2015-11-01

    Full Text Available The direct radiative impacts of biomass burning aerosols (BBA on meteorology are investigated using short-range forecasts from the Met Office Unified Model (MetUM over South America during the South American Biomass Burning Analysis (SAMBBA. The impacts are evaluated using a set of three simulations: (i no aerosols, (ii with monthly mean aerosol climatologies and (iii with prognostic aerosols modelled using the Coupled Large-scale Aerosol Simulator for Studies In Climate (CLASSIC scheme. Comparison with observations show that the prognostic CLASSIC scheme provides the best representation of BBA. The impacts of BBA are quantified over central and southern Amazonia from the first and second day of 2-day forecasts during 14 September–3 October 2012. On average, during the first day of the forecast, including prognostic BBA reduces the clear-sky net radiation at the surface by 15 ± 1 W m−2 and reduces net top-of-atmosphere (TOA radiation by 8 ± 1 W m−2, with a direct atmospheric warming of 7 ± 1 W m−2. BBA-induced reductions in all-sky radiation are smaller in magnitude: 9.0 ± 1 W m−2 at the surface and 4.0 ± 1 W m−2 at TOA. In this modelling study the BBA therefore exert an overall cooling influence on the Earth–atmosphere system, although some levels of the atmosphere are directly warmed by the absorption of solar radiation. Due to the reduction of net radiative flux at the surface, the mean 2 m air temperature is reduced by around 0.1 ± 0.02 °C. The BBA also cools the boundary layer (BL but warms air above by around 0.2 °C due to the absorption of shortwave radiation. The overall impact is to reduce the BL depth by around 19 ± 8 m. These differences in heating lead to a more anticyclonic circulation at 700 hPa, with winds changing by around 0.6 m s−1. Inclusion of climatological or prognostic BBA in the MetUM makes a small but significant improvement in forecasts of temperature and relative humidity, but improvements were

  9. Home range size and breeding dispersal of a common buzzard (Buteo buteo

    Directory of Open Access Journals (Sweden)

    Väli Ülo

    2017-12-01

    Full Text Available Telemetric studies have provided ample information on threatened raptors, but still little is known about space use and dispersal of common species. Here I describe the home range and breeding dispersal of a GPS-tracked adult male common buzzard, studied in south-eastern Estonia in 2014–16. This buzzard’s home range covered 8.3 km2 (kernel 95% estimate with the core range being 2.1 km2 (kernel 50%. The home range increased in the course of the breeding season but decreased again before migration. Surprisingly, the nests in the two successive breeding years were located in the opposite margins of the home range, 1.7 km from each other.

  10. Probabilistic forecasts of wind power generation accounting for geographically dispersed information

    DEFF Research Database (Denmark)

    Tastu, Julija; Pinson, Pierre; Trombe, Pierre-Julien

    2014-01-01

    be optimized by accounting for spatio-temporal effects that are so far merely considered. The way these effects may be included in relevant models is described for the case of both parametric and nonparametric approaches to generating probabilistic forecasts. The resulting predictions are evaluated on the real...... of the first order moments of predictive densities. The best performing approach, based on adaptive quantile regression, using spatially corrected point forecasts as input, consistently outperforms the state-of-theartbenchmark based on local information only, by 1.5%-4.6%, depending upon the lead time....

  11. Development of the ClearSky smoke dispersion forecast system for agricultural field burning in the Pacific Northwest

    Science.gov (United States)

    Jain, Rahul; Vaughan, Joseph; Heitkamp, Kyle; Ramos, Charleston; Claiborn, Candis; Schreuder, Maarten; Schaaf, Mark; Lamb, Brian

    The post-harvest burning of agricultural fields is commonly used to dispose of crop residue and provide other desired services such as pest control. Despite careful regulation of burning, smoke plumes from field burning in the Pacific Northwest commonly degrade air quality, particularly for rural populations. In this paper, ClearSky, a numerical smoke dispersion forecast system for agricultural field burning that was developed to support smoke management in the Inland Pacific Northwest, is described. ClearSky began operation during the summer through fall burn season of 2002 and continues to the present. ClearSky utilizes Mesoscale Meteorological Model version 5 (MM5v3) forecasts from the University of Washington, data on agricultural fields, a web-based user interface for defining burn scenarios, the Lagrangian CALPUFF dispersion model and web-served animations of plume forecasts. The ClearSky system employs a unique hybrid source configuration, which treats the flaming portion of a field as a buoyant line source and the smoldering portion of the field as a buoyant area source. Limited field observations show that this hybrid approach yields reasonable plume rise estimates using source parameters derived from recent field burning emission field studies. The performance of this modeling system was evaluated for 2003 by comparing forecast meteorology against meteorological observations, and comparing model-predicted hourly averaged PM 2.5 concentrations against observations. Examples from this evaluation illustrate that while the ClearSky system can accurately predict PM 2.5 surface concentrations due to field burning, the overall model performance depends strongly on meteorological forecast error. Statistical evaluation of the meteorological forecast at seven surface stations indicates a strong relationship between topographical complexity near the station and absolute wind direction error with wind direction errors increasing from approximately 20° for sites in

  12. Tailoring of the free spectral range and geometrical cavity dispersion of a microsphere by a coating layer.

    Science.gov (United States)

    Ristić, Davor; Mazzola, Maurizio; Chiappini, Andrea; Rasoloniaina, Alphonse; Féron, Patrice; Ramponi, Roberta; Righini, Giancarlo C; Cibiel, Gilles; Ivanda, Mile; Ferrari, Maurizio

    2014-09-01

    The modal dispersion of a whispering gallery mode (WGM) resonator is a very important parameter for use in all nonlinear optics applications. In order to tailor the WGM modal dispersion of a microsphere, we have coated a silica microsphere with a high-refractive-index coating in order to study its effect on the WGM modal dispersion. We used Er(3+) ions as a probe for a modal dispersion assessment. We found that, by varying the coating thickness, the geometrical cavity dispersion can be used to shift overall modal dispersion in a very wide range in both the normal and anomalous dispersion regime.

  13. Switching between bistable states in a discrete nonlinear model with long-range dispersion

    DEFF Research Database (Denmark)

    Johansson, Magnus; Gaididei, Yuri B.; Christiansen, Peter Leth

    1998-01-01

    In the framework of a discrete nonlinear Schrodinger equation with long-range dispersion, we propose a general mechanism for obtaining a controlled switching between bistable localized excitations. We show that the application of a spatially symmetric kick leads to the excitation of an internal...

  14. Dispersal Range of Anopheles sinensis in Yongcheng City, China by Mark-Release-Recapture Methods

    Science.gov (United States)

    Guo, Yuhong; Ren, Dongsheng; Zheng, Canjun; Wu, Haixia; Yang, Shuran; Liu, Jingli; Li, Hongsheng; Li, Huazhong; Li, Qun; Yang, Weizhong; Chu, Cordia

    2012-01-01

    Background Studying the dispersal range of Anopheles sinensis is of major importance for understanding the transition from malaria control to elimination. However, no data are available regarding the dispersal range of An. sinensis in China. The aim of the present study was to study the dispersal range of An. sinensis and provide the scientific basis for the development of effective control measures for malaria elimination in China. Methodology/Principal Findings Mark-Release-Recapture (MRR) experiments were conducted with 3000 adult wild An. sinensis in 2010 and 3000 newly emerged wild An. sinensis in 2011 in two villages of Yongcheng City in Henan Province. Marked An. sinensis were recaptured daily for ten successive days using light traps. The overall recapture rates were 0.83% (95% CI, 0.50%∼1.16%) in 2010 and 1.33% (95% CI, 0.92%∼1.74%) in 2011. There was no significant difference in the recapture rates of wild An. sinensis and newly emerged An. sinensis. The majority of An. sinensis were captured due east at study site I compared with most in the west at study site II. Eighty percent and 90% of the marked An. sinensis were recaptured within a radius of 100 m from the release point in study site I and II, respectively, with a maximum dispersal range of 400 m within the period of this study. Conclusions/Significance Our results indicate that local An. sinensis may have limited dispersal ranges. Therefore, control efforts should target breeding and resting sites in proximity of the villages. PMID:23226489

  15. Range expansion drives dispersal evolution in an equatorial three-species symbiosis.

    Directory of Open Access Journals (Sweden)

    Guillaume Léotard

    Full Text Available Recurrent climatic oscillations have produced dramatic changes in species distributions. This process has been proposed to be a major evolutionary force, shaping many life history traits of species, and to govern global patterns of biodiversity at different scales. During range expansions selection may favor the evolution of higher dispersal, and symbiotic interactions may be affected. It has been argued that a weakness of climate fluctuation-driven range dynamics at equatorial latitudes has facilitated the persistence there of more specialized species and interactions. However, how much the biology and ecology of species is changed by range dynamics has seldom been investigated, particularly in equatorial regions.We studied a three-species symbiosis endemic to coastal equatorial rainforests in Cameroon, where the impact of range dynamics is supposed to be limited, comprised of two species-specific obligate mutualists--an ant-plant and its protective ant--and a species-specific ant parasite of this mutualism. We combined analyses of within-species genetic diversity and of phenotypic variation in a transect at the southern range limit of this ant-plant system. All three species present congruent genetic signatures of recent gradual southward expansion, a result compatible with available regional paleoclimatic data. As predicted, this expansion has been accompanied by the evolution of more dispersive traits in the two ant species. In contrast, we detected no evidence of change in lifetime reproductive strategy in the tree, nor in its investment in food resources provided to its symbiotic ants.Despite the decreasing investment in protective workers and the increasing investment in dispersing females by both the mutualistic and the parasitic ant species, there was no evidence of destabilization of the symbiosis at the colonization front. To our knowledge, we provide here the first evidence at equatorial latitudes that biological traits associated

  16. Range expansion drives dispersal evolution in an equatorial three-species symbiosis.

    Science.gov (United States)

    Léotard, Guillaume; Debout, Gabriel; Dalecky, Ambroise; Guillot, Sylvain; Gaume, Laurence; McKey, Doyle; Kjellberg, Finn

    2009-01-01

    Recurrent climatic oscillations have produced dramatic changes in species distributions. This process has been proposed to be a major evolutionary force, shaping many life history traits of species, and to govern global patterns of biodiversity at different scales. During range expansions selection may favor the evolution of higher dispersal, and symbiotic interactions may be affected. It has been argued that a weakness of climate fluctuation-driven range dynamics at equatorial latitudes has facilitated the persistence there of more specialized species and interactions. However, how much the biology and ecology of species is changed by range dynamics has seldom been investigated, particularly in equatorial regions. We studied a three-species symbiosis endemic to coastal equatorial rainforests in Cameroon, where the impact of range dynamics is supposed to be limited, comprised of two species-specific obligate mutualists--an ant-plant and its protective ant--and a species-specific ant parasite of this mutualism. We combined analyses of within-species genetic diversity and of phenotypic variation in a transect at the southern range limit of this ant-plant system. All three species present congruent genetic signatures of recent gradual southward expansion, a result compatible with available regional paleoclimatic data. As predicted, this expansion has been accompanied by the evolution of more dispersive traits in the two ant species. In contrast, we detected no evidence of change in lifetime reproductive strategy in the tree, nor in its investment in food resources provided to its symbiotic ants. Despite the decreasing investment in protective workers and the increasing investment in dispersing females by both the mutualistic and the parasitic ant species, there was no evidence of destabilization of the symbiosis at the colonization front. To our knowledge, we provide here the first evidence at equatorial latitudes that biological traits associated with dispersal are

  17. An evaluation of dry deposition from the long range atmospheric dispersion

    International Nuclear Information System (INIS)

    Suh, K.S.; Kim, E.H.; Hwang, W.T.; Han, M.H.; Lee, H.S.; Lee, C.W.

    2003-01-01

    The dry deposition of pollutants released into the atmosphere must be evaluated to estimate the radiological dose of terrestrial plants and foodstuffs in the ecosystem. Especially, the atmospheric dispersion and dry deposition models have been widely developed to predict and minimize the radiological damage for the surrounding environment after the TMI-2 and the Chernobyl accidents. A Lagrangian particle model for the evaluation the long-range dispersion has been firstly developed in Korea since 2001. The particle tracking method was used for the estimation of the concentration distribution of the radioactive materials released into the atmosphere. The model is designed to estimate air concentration and ground deposition at distances up to some thousands of kilometers from the source point in the horizontal direction. The turbulent motion is considered to separate the treatment of particles within the mixing layer and above the mixing layer. Also, the dispersion model is designed to receive the results of the MM5 model being operated by KMA (Korea Meteorological Administration). The test run of the long-range dispersion model has been performed in the area which covered extends from 102.47deg E to 173.34deg E and from 12.27deg N to 53.72deg N in Northeast Asia. The release point of Cs-137 assumed in the east part of the China. The long range dispersion model has been firstly developed to estimate the radiological consequences against a nuclear accident. The model will be supplemented by the comparative study using the data of the ETEX experiments. (author)

  18. Forecasting long-range atmospheric transport episodes of polychlorinated biphenyls using FLEXPART

    Science.gov (United States)

    Halse, Anne Karine; Eckhardt, Sabine; Schlabach, Martin; Stohl, Andreas; Breivik, Knut

    2013-06-01

    The analysis of concentrations of persistent organic pollutants (POPs) in ambient air is costly and can only be done for a limited number of samples. It is thus beneficial to maximize the information content of the samples analyzed via a targeted observation strategy. Using polychlorinated biphenyls (PCBs) as an example, a forecasting system to predict and evaluate long-range atmospheric transport (LRAT) episodes of POPs at a remote site in southern Norway has been developed. The system uses the Lagrangian particle transport model FLEXPART, and can be used for triggering extra ("targeted") sampling when LRAT episodes are predicted to occur. The system was evaluated by comparing targeted samples collected over 12-25 h during individual LRAT episodes with monitoring samples regularly collected over one day per week throughout a year. Measured concentrations in all targeted samples were above the 75th percentile of the concentrations obtained from the regular monitoring program and included the highest measured values of all samples. This clearly demonstrates the success of the targeted sampling strategy.

  19. Dispersal limitation at the expanding range margin of an evergreen tree in urban habitats?

    DEFF Research Database (Denmark)

    Møller, Linda Agerbo; Skou, Anne-Marie Thonning; Kollmann, Johannes Christian

    2012-01-01

    Dispersal limitations contribute to shaping plant distribution patterns and thus are significant for biodiversity conservation and urban ecology. In fleshy-fruited plants, for example, any preference of frugivorous birds affects dispersal capacities of certain fruit species. We conducted a removal...... landscapes. The results should be included in urban forestry and planting of potentially invasive ornamental species. © 2011 Elsevier GmbH. All rights reserved....... experiment with fruits of Ilex aquifolium, a species that is currently expanding its range margin in northern Europe in response to climate change. The species is also a popular ornamental tree and naturalization has been observed in many parts of its range. Fruits of native I. aquifolium and of three...

  20. Long-range dipolar order and dispersion forces in polar liquids

    Science.gov (United States)

    Besford, Quinn Alexander; Christofferson, Andrew Joseph; Liu, Maoyuan; Yarovsky, Irene

    2017-11-01

    Complex solvation phenomena, such as specific ion effects, occur in polar liquids. Interpretation of these effects in terms of structure and dispersion forces will lead to a greater understanding of solvation. Herein, using molecular dynamics, we probe the structure of polar liquids through specific dipolar pair correlation functions that contribute to the potential of mean force that is "felt" between thermally rotating dipole moments. It is shown that unique dipolar order exists at separations at least up to 20 Å for all liquids studied. When the structural order is compared with a dipolar dispersion force that arises from local co-operative enhancement of dipole moments, a strong agreement is found. Lifshitz theory of dispersion forces was compared with the structural order, where the theory is validated for all liquids that do not have significant local dipole correlations. For liquids that do have significant local dipole correlations, specifically liquid water, Lifshitz theory underestimates the dispersion force by a factor of 5-10, demonstrating that the force that leads to the increased structure in liquid water is missed by Lifshitz theory of van der Waals forces. We apply similar correlation functions to an ionic aqueous system, where long-range order between water's dipole moment and a single chloride ion is found to exist at 20 Å of separation, revealing a long-range perturbation of water's structure by an ion. Furthermore, we found that waters within the 1st, 2nd, and 3rd solvation shells of a chloride ion exhibit significantly enhanced dipolar interactions, particularly with waters at larger distances of separation. Our results provide a link between structures, dispersion forces, and specific ion effects, which may lead to a more robust understanding of solvation.

  1. Long-Range Lightning Products for Short Term Forecasting of Tropical Cyclogenesis

    Science.gov (United States)

    Businger, S.; Pessi, A.; Robinson, T.; Stolz, D.

    2010-12-01

    This paper will describe innovative graphical products derived in real time from long-range lightning data. The products have been designed to aid in short-term forecasting of tropical cyclone development for the Tropical Cyclone Structure Experiment 2010 (TCS10) held over the western Pacific Ocean from 17 August to 17 October 2010 and are available online at http://www.soest.hawaii.edu/cgi-bin/pacnet/tcs10.pl. The long-range lightning data are from Vaisala’s Global Lightning Data 360 (GLD360) network and include time, location, current strength, polarity, and data quality indication. The products currently provided in real time include i. Infrared satellite imagery overlaid with lighting flash locations, with color indication of current strength and polarity (shades of blue for negative to ground and red for positive to ground). ii. A 15x15 degree storm-centered tile of IR imagery overlaid with lightning data as in i). iii. A pseudo reflectivity product showing estimates of radar reflectivity based on lightning rate - rain rate conversion derived from TRMM and PacNet data. iv. A lightning history product that plots each hour of lightning flash locations in a different color for a 12-hour period. v. Graphs of lightning counts within 50 or 300 km radius, respectively, of the storm center vs storm central sea-level pressure. vi. A 2-D graphic showing storm core lightning density along the storm track. The first three products above can be looped to gain a better understanding of the evolution of the lightning and storm structure. Examples of the graphics and their utility will be demonstrated and discussed. Histogram of lightning counts within 50 km of the storm center and graph of storm central pressure as a function of time.

  2. Diverse range dynamics and dispersal routes of plants on the Tibetan Plateau during the late Quaternary.

    Directory of Open Access Journals (Sweden)

    Haibin Yu

    Full Text Available Phylogeographical studies have suggested that several plant species on the Tibetan Plateau (TP underwent recolonization during the Quaternary and may have had distinct range dynamics in response to the last glacial. To further test this hypothesis and locate the possible historical dispersal routes, we selected 20 plant species from different parts of the TP and modeled their geographical distributions over four time periods using species distribution models (SDMs. Furthermore, we applied the least-cost path method together with SDMs and shared haplotypes to estimate their historical dispersal corridors. We identified three general scenarios of species distribution change during the late Quaternary: the 'contraction-expansion' scenario for species in the northeastern TP, the 'expansion-contraction' scenario for species in the southeast and the 'stable' scenario for widespread species. During the Quaternary, we identified that these species were likely to recolonize along the low-elevation valleys, huge mountain ranges and flat plateau platform (e.g. the Yarlung Zangbo Valley and the Himalaya. We inferred that Quaternary cyclic glaciations along with the various topographic and climatic conditions of the TP could have resulted in the diverse patterns of range shift and dispersal of Tibetan plant species. Finally, we believe that this study would provide valuable insights for the conservation of alpine species under future climate change.

  3. A model for short and medium range dispersion of radionuclides released to the atmosphere

    International Nuclear Information System (INIS)

    Clarke, R.H.

    1979-09-01

    A Working Group was established to give practical guidance on the estimation of the dispersion of radioactive releases to the atmosphere. The dispersion is estimated in the short and medium range, that is from about 100 m to a few tens of kilometres from the source, and is based upon a Gaussian plume model. A scheme is presented for categorising atmospheric conditions and values of the associated dispersion parameters are given. Typical results are presented for releases in specific meteorological conditions and a scheme is included to allow for durations of release of up to 24 hours. Consideration has also been given to predicting longer term average concentrations, typically annual averages, and results are presented which facilitate site specific calculations. The results of the models are extended to 100 km from the source, but the increasing uncertainty with which results may be predicted beyond a few tens of kilometres from the source is emphasised. Three technical appendices provide some of the rationale behind the decisions made in adopting the various models in the proposed dispersion scheme. (author)

  4. How Hydroclimate Influences the Effectiveness of Particle Filter Data Assimilation of Streamflow in Initializing Short- to Medium-range Streamflow Forecasts

    Science.gov (United States)

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

    2017-12-01

    Short- to medium-range (1- to 7-day) streamflow forecasts are important for flood control operations and in issuing potentially life-save flood warnings. In the U.S., the National Weather Service River Forecast Centers (RFCs) issue such forecasts in real time, depending heavily on a manual data assimilation (DA) approach. Forecasters adjust model inputs, states, parameters and outputs based on experience and consideration of a range of supporting real-time information. Achieving high-quality forecasts from new automated, centralized forecast systems will depend critically on the adequacy of automated DA approaches to make analogous corrections to the forecasting system. Such approaches would further enable systematic evaluation of real-time flood forecasting methods and strategies. Toward this goal, we have implemented a real-time Sequential Importance Resampling particle filter (SIR-PF) approach to assimilate observed streamflow into simulated initial hydrologic conditions (states) for initializing ensemble flood forecasts. Assimilating streamflow alone in SIR-PF improves simulated streamflow and soil moisture during the model spin up period prior to a forecast, with consequent benefits for forecasts. Nevertheless, it only consistently limits error in simulated snow water equivalent during the snowmelt season and in basins where precipitation falls primarily as snow. We examine how the simulated initial conditions with and without SIR-PF propagate into 1- to 7-day ensemble streamflow forecasts. Forecasts are evaluated in terms of reliability and skill over a 10-year period from 2005-2015. The focus of this analysis is on how interactions between hydroclimate and SIR-PF performance impact forecast skill. To this end, we examine forecasts for 5 hydroclimatically diverse basins in the western U.S. Some of these basins receive most of their precipitation as snow, others as rain. Some freeze throughout the mid-winter while others experience significant mid-winter melt

  5. Long-Range Corrected Hybrid Density Functionals with Damped Atom-Atom Dispersion Corrections

    Energy Technology Data Exchange (ETDEWEB)

    Chai, Jeng-Da; Head-Gordon, Martin

    2008-06-14

    We report re-optimization of a recently proposed long-range corrected (LC) hybrid density functionals [J.-D. Chai and M. Head-Gordon, J. Chem. Phys. 128, 084106 (2008)] to include empirical atom-atom dispersion corrections. The resulting functional, {omega}B97X-D yields satisfactory accuracy for thermochemistry, kinetics, and non-covalent interactions. Tests show that for non-covalent systems, {omega}B97X-D shows slight improvement over other empirical dispersion-corrected density functionals, while for covalent systems and kinetics, it performs noticeably better. Relative to our previous functionals, such as {omega}B97X, the new functional is significantly superior for non-bonded interactions, and very similar in performance for bonded interactions.

  6. Long-Range Socio-Economic Forecasting of World Development in the Works by IMEMO RAS

    Directory of Open Access Journals (Sweden)

    Suslov D. V.

    2011-12-01

    Full Text Available A brief overview is given of papers by the Institute of World Economy and International Relations, Russian Academy of Sciences (IMEMO RAS on long-term socio-economic forecasting of global development. The forecasting methodology is shown, its capabilities and limitations, as well as the structure, main results and characteristics of the forecasts made by IMEMO RAS since early 2000s. The «Strategic Global Outlook for 2030» has acquired features of an interdisciplinary research, and has been developed based on a system analysis of objective socio-economic indicators, long-term global and regional socio-demographic trends, and expert assessment of the future dynamics of the political situation in individual countries and in intergovernmental relations. This methodology allowed the focus to be placed primarily on the stable trends of development in the world economy and the system of international relations, their actors, structures and institutions

  7. Selfing ability and dispersal are positively related, but not affected by range position: a multispecies study on southern African Asteraceae.

    Science.gov (United States)

    de Waal, C; Rodger, J G; Anderson, B; Ellis, A G

    2014-05-01

    Dispersal and breeding system traits are thought to affect colonization success. As species have attained their present distribution ranges through colonization, these traits may vary geographically. Although several theories predict associations between dispersal ability, selfing ability and the relative position of a population within its geographic range, there is little theoretical or empirical consensus on exactly how these three variables are related. We investigated relationships between dispersal ability, selfing ability and range position across 28 populations of 13 annual, wind-dispersed Asteraceae species from the Namaqualand region of South Africa. Controlling for phylogeny, relative dispersal ability--assessed from vertical fall time of fruits--was positively related to an index of autofertility--determined from hand-pollination experiments. These findings support the existence of two discrete syndromes: high selfing ability associated with good dispersal and obligate outcrossing associated with lower dispersal ability. This is consistent with the hypothesis that selection for colonization success drives the evolution of an association between these traits. However, no general effect of range position on dispersal or breeding system traits was evident. This suggests selection on both breeding system and dispersal traits acts consistently across distribution ranges. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

  8. Objectives for next generation of practical short-range atmospheric dispersion models

    International Nuclear Information System (INIS)

    Olesen, H.R.; Mikkelsen, T.

    1992-01-01

    The proceedings contains papers from the workshop ''Objectives for Next Generation of Practical Short-Range Atmospheric Dispersion Models''. They deal with two types of models, namely models for regulatory purposes and models for real-time applications. The workshop was the result of an action started in 1991 for increased cooperation and harmonization within atmospheric dispersion modelling. The focus of the workshop was on the management of model development and the definition of model objectives, rather than on detailed model contents. It was the intention to identify actions that can be taken in order to improve the development and use of atmospheric dispersion models. The papers in the proceedings deal with various topics within the broad spectrum of matters related to up-to-date practical models, such as their scientific basis, requirements for model input and output, meteorological preprocessing, standardisation within modelling, electronic information exchange as a potentially useful tool, model evaluation and data bases for model evaluation. In addition to the papers, the proceedings contain summaries of the discussions at the workshop. These summaries point to a number of recommended actions which can be taken in order to improve ''modelling culture''. (AB)

  9. Overland movement in African clawed frogs (Xenopus laevis: empirical dispersal data from within their native range

    Directory of Open Access Journals (Sweden)

    F. André De Villiers

    2017-11-01

    Full Text Available Dispersal forms are an important component of the ecology of many animals, and reach particular importance for predicting ranges of invasive species. African clawed frogs (Xenopus laevis move overland between water bodies, but all empirical studies are from invasive populations with none from their native southern Africa. Here we report on incidents of overland movement found through a capture-recapture study carried out over a three year period in Overstrand, South Africa. The maximum distance moved was 2.4 km with most of the 91 animals, representing 5% of the population, moving ∼150 m. We found no differences in distances moved by males and females, despite the former being smaller. Fewer males moved overland, but this was no different from the sex bias found in the population. In laboratory performance trials, we found that males outperformed females, in both distance moved and time to exhaustion, when corrected for size. Overland movement occurred throughout the year, but reached peaks in spring and early summer when temporary water bodies were drying. Despite permanent impoundments being located within the study area, we found no evidence for migrations of animals between temporary and permanent water bodies. Our study provides the first dispersal kernel for X. laevis and suggests that it is similar to many non-pipid anurans with respect to dispersal.

  10. Underestimated risks of recurrent long-range ash dispersal from northern Pacific Arc volcanoes.

    Science.gov (United States)

    Bourne, A J; Abbott, P M; Albert, P G; Cook, E; Pearce, N J G; Ponomareva, V; Svensson, A; Davies, S M

    2016-07-21

    Widespread ash dispersal poses a significant natural hazard to society, particularly in relation to disruption to aviation. Assessing the extent of the threat of far-travelled ash clouds on flight paths is substantially hindered by an incomplete volcanic history and an underestimation of the potential reach of distant eruptive centres. The risk of extensive ash clouds to aviation is thus poorly quantified. New evidence is presented of explosive Late Pleistocene eruptions in the Pacific Arc, currently undocumented in the proximal geological record, which dispersed ash up to 8000 km from source. Twelve microscopic ash deposits or cryptotephra, invisible to the naked eye, discovered within Greenland ice-cores, and ranging in age between 11.1 and 83.7 ka b2k, are compositionally matched to northern Pacific Arc sources including Japan, Kamchatka, Cascades and Alaska. Only two cryptotephra deposits are correlated to known high-magnitude eruptions (Towada-H, Japan, ca 15 ka BP and Mount St Helens Set M, ca 28 ka BP). For the remaining 10 deposits, there is no evidence of age- and compositionally-equivalent eruptive events in regional volcanic stratigraphies. This highlights the inherent problem of under-reporting eruptions and the dangers of underestimating the long-term risk of widespread ash dispersal for trans-Pacific and trans-Atlantic flight routes.

  11. Improving short-range ensemble Kalman storm surge forecasting using robust adaptive inflation

    NARCIS (Netherlands)

    Altaf, M.U.; Butler, T.; Luo, X.; Dawson, C.; Mayo, T.; Hoteit, I.

    2013-01-01

    This paper presents a robust ensemble filtering methodology for storm surge forecasting based on the singular evolutive interpolated Kalman (SEIK) filter, which has been implemented in the framework of the H? filter. By design, an H? filter is more robust than the common Kalman filter in the sense

  12. Extended-range forecast for the temporal distribution of clustering tropical cyclogenesis over the western North Pacific

    Science.gov (United States)

    Zhu, Zhiwei; Li, Tim; Bai, Long; Gao, Jianyun

    2017-11-01

    Based on outgoing longwave radiation (OLR), an index for clustering tropical cyclogenesis (CTC) over the western North Pacific (WNP) was defined. Around 76 % of total CTC events were generated during the active phase of the CTC index, and 38 % of the total active phase was concurrent with CTC events. For its continuous property, the CTC index was used as the representative predictand for extended-range forecasting the temporal distribution of CTC events. The predictability sources for CTC events were detected via correlation analyses of the previous 35-5-day lead atmospheric fields against the CTC index. The results showed that the geopotential height at different levels and the 200 hPa zonal wind over the global tropics possessed large predictability sources, whereas the predictability sources of other variables, e.g., OLR, zonal wind, and relatively vorticity at 850 hPa and relatively humility at 700 hPa, were mainly confined to the tropical Indian Ocean and western Pacific Ocean. Several spatial-temporal projection model (STPM) sets were constructed to carry out the extended-range forecast for the CTC index. By combining the output of STPMs separately conducted for the two dominant modes of intraseasonal variability, e.g., the 10-30 and the 30-80 day mode, useful forecast skill could be achieved for a 30-day lead time. The combined output successfully captured both the 10-30 and 30-80 day mode at least 10 days in advance. With a relatively low rate of false alarm, the STPM achieved hits for 80 % (69 %) of 54 CTC events during 2003-2014 at the 10-day (20-day) lead time, suggesting a practical value of the STPM for real-time forecasting WNP CTC events at an extended range.

  13. Dispersal in the sub-Antarctic: king penguins show remarkably little population genetic differentiation across their range.

    Science.gov (United States)

    Clucas, Gemma V; Younger, Jane L; Kao, Damian; Rogers, Alex D; Handley, Jonathan; Miller, Gary D; Jouventin, Pierre; Nolan, Paul; Gharbi, Karim; Miller, Karen J; Hart, Tom

    2016-10-13

    Seabirds are important components of marine ecosystems, both as predators and as indicators of ecological change, being conspicuous and sensitive to changes in prey abundance. To determine whether fluctuations in population sizes are localised or indicative of large-scale ecosystem change, we must first understand population structure and dispersal. King penguins are long-lived seabirds that occupy a niche across the sub-Antarctic zone close to the Polar Front. Colonies have very different histories of exploitation, population recovery, and expansion. We investigated the genetic population structure and patterns of colonisation of king penguins across their current range using a dataset of 5154 unlinked, high-coverage single nucleotide polymorphisms generated via restriction site associated DNA sequencing (RADSeq). Despite breeding at a small number of discrete, geographically separate sites, we find only very slight genetic differentiation among colonies separated by thousands of kilometers of open-ocean, suggesting migration among islands and archipelagos may be common. Our results show that the South Georgia population is slightly differentiated from all other colonies and suggest that the recently founded Falkland Island colony is likely to have been established by migrants from the distant Crozet Islands rather than nearby colonies on South Georgia, possibly as a result of density-dependent processes. The observed subtle differentiation among king penguin colonies must be considered in future conservation planning and monitoring of the species, and demographic models that attempt to forecast extinction risk in response to large-scale climate change must take into account migration. It is possible that migration could buffer king penguins against some of the impacts of climate change where colonies appear panmictic, although it is unlikely to protect them completely given the widespread physical changes projected for their Southern Ocean foraging grounds

  14. Long-range transmission of pollutants simulated by a two-dimensional pseudospectral dispersion model

    International Nuclear Information System (INIS)

    Prahm, L.P.; Christensen, O.

    1977-01-01

    The pseudospectral dispersion model (Christensen and Prahm, 1976) is adapted for simulation of the long-range transmission of sulphur pollutants in the European region, covering an area of about 4000 km x 4000 km. Regional ''background'' concentrations of sulphur oxides are found to be highly dependent on distant sources and to correlate poorly with local source strength during the considered three- and four-day episodes. The simulation is based on emission data, given in squares of about 50 km x 50 km and on synoptic wind fields derived from observed wind velocities of the 850 mb level and the surface level. The two-dimensional model includes a constant vertical mixing depth. Appropriate values for the deposition and the transformation rates of SO 2 and SO/sup 4 are used. The concentration of pollutants computed from the two-dimensional pseudospectral dispersion model reflects the variable meteorological conditions. Computed concentrations are compared with measurements, giving spatial correlations between 0.4 and 0.8 for more than 400 ground-based 24 h mean values, and a spatial correlation of 0.9 for eight aircraft samples averaged over approx.30 min. A discussion of the influence of different sources of error in the model simulation is given. The high numerical accuracy of the pseudospectral model is combined with a modest consumption of CPU computer time. This study is the first application of the pseudospectral dispersion model which compares computed concentrations with measured field data. The model has possible applications as a tool for assessment of the impact of both national and international emission regulation strategies

  15. A non-dispersive infrared analyser for analysis of HF in the PPM range

    International Nuclear Information System (INIS)

    Kartha, V.B.; Patel, N.D.; Venkateswaran, S.

    1985-01-01

    The determination of trace amounts of HF is of importance in many industrial processes, and in nuclear industry in the production of UF 6 . Mass spectrometric and gas chromatographic methods are difficult to use for this purpose, because of the highly corrosive nature of the samples. Infrared Spectroscopy can be conveniently used with the required sensitivity and it has the added advantage that continuous non-destructive on-line monitoring can be conveniently done. A non-dispersive infrared analyser for determination of HF in UF 6 in the concentration range of 50-2000 ppm has been fabricated and tested. The instrument has been shown to possess high sensitivity and good long term stability, so that it can be used as on-line monitor for non-destructive, continuous analysis. (author)

  16. Error sensitivity analysis in 10-30-day extended range forecasting by using a nonlinear cross-prediction error model

    Science.gov (United States)

    Xia, Zhiye; Xu, Lisheng; Chen, Hongbin; Wang, Yongqian; Liu, Jinbao; Feng, Wenlan

    2017-06-01

    Extended range forecasting of 10-30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastrous meteorological events. The sensitivity of initial error, model parameter error, and random error in a nonlinear crossprediction error (NCPE) model, and their stability in the prediction validity period in 10-30-day extended range forecasting, are analyzed quantitatively. The associated sensitivity of precipitable water, temperature, and geopotential height during cases of heavy rain and hurricane is also discussed. The results are summarized as follows. First, the initial error and random error interact. When the ratio of random error to initial error is small (10-6-10-2), minor variation in random error cannot significantly change the dynamic features of a chaotic system, and therefore random error has minimal effect on the prediction. When the ratio is in the range of 10-1-2 (i.e., random error dominates), attention should be paid to the random error instead of only the initial error. When the ratio is around 10-2-10-1, both influences must be considered. Their mutual effects may bring considerable uncertainty to extended range forecasting, and de-noising is therefore necessary. Second, in terms of model parameter error, the embedding dimension m should be determined by the factual nonlinear time series. The dynamic features of a chaotic system cannot be depicted because of the incomplete structure of the attractor when m is small. When m is large, prediction indicators can vanish because of the scarcity of phase points in phase space. A method for overcoming the cut-off effect ( m > 4) is proposed. Third, for heavy rains, precipitable water is more sensitive to the prediction validity period than temperature or geopotential height; however, for hurricanes, geopotential height is most sensitive, followed by precipitable water.

  17. Statistical Short-Range Guidance for Peak Wind Speed Forecasts on Kennedy Space Center/Cape Canaveral Air Force Station: Phase I Results

    Science.gov (United States)

    Lambert, Winifred C.; Merceret, Francis J. (Technical Monitor)

    2002-01-01

    This report describes the results of the ANU's (Applied Meteorology Unit) Short-Range Statistical Forecasting task for peak winds. The peak wind speeds are an important forecast element for the Space Shuttle and Expendable Launch Vehicle programs. The Keith Weather Squadron and the Spaceflight Meteorology Group indicate that peak winds are challenging to forecast. The Applied Meteorology Unit was tasked to develop tools that aid in short-range forecasts of peak winds at tower sites of operational interest. A 7 year record of wind tower data was used in the analysis. Hourly and directional climatologies by tower and month were developed to determine the seasonal behavior of the average and peak winds. In all climatologies, the average and peak wind speeds were highly variable in time. This indicated that the development of a peak wind forecasting tool would be difficult. Probability density functions (PDF) of peak wind speed were calculated to determine the distribution of peak speed with average speed. These provide forecasters with a means of determining the probability of meeting or exceeding a certain peak wind given an observed or forecast average speed. The climatologies and PDFs provide tools with which to make peak wind forecasts that are critical to safe operations.

  18. Contrasting growth forecasts across the geographical range of Scots pine due to altitudinal and latitudinal differences in climatic sensitivity.

    Science.gov (United States)

    Matías, Luis; Linares, Juan C; Sánchez-Miranda, Ángela; Jump, Alistair S

    2017-10-01

    Ongoing changes in global climate are altering ecological conditions for many species. The consequences of such changes are typically most evident at the edge of a species' geographical distribution, where differences in growth or population dynamics may result in range expansions or contractions. Understanding population responses to different climatic drivers along wide latitudinal and altitudinal gradients is necessary in order to gain a better understanding of plant responses to ongoing increases in global temperature and drought severity. We selected Scots pine (Pinus sylvestris L.) as a model species to explore growth responses to climatic variability (seasonal temperature and precipitation) over the last century through dendrochronological methods. We developed linear models based on age, climate and previous growth to forecast growth trends up to year 2100 using climatic predictions. Populations were located at the treeline across a latitudinal gradient covering the northern, central and southernmost populations and across an altitudinal gradient at the southern edge of the distribution (treeline, medium and lower elevations). Radial growth was maximal at medium altitude and treeline of the southernmost populations. Temperature was the main factor controlling growth variability along the gradients, although the timing and strength of climatic variables affecting growth shifted with latitude and altitude. Predictive models forecast a general increase in Scots pine growth at treeline across the latitudinal distribution, with southern populations increasing growth up to year 2050, when it stabilizes. The highest responsiveness appeared at central latitude, and moderate growth increase is projected at the northern limit. Contrastingly, the model forecasted growth declines at lowland-southern populations, suggesting an upslope range displacement over the coming decades. Our results give insight into the geographical responses of tree species to climate change

  19. Pair-Wise and Many-Body Dispersive Interactions Coupled to an Optimally Tuned Range-Separated Hybrid Functional.

    Science.gov (United States)

    Agrawal, Piyush; Tkatchenko, Alexandre; Kronik, Leeor

    2013-08-13

    We propose a nonempirical, pair-wise or many-body dispersion-corrected, optimally tuned range-separated hybrid functional. This functional retains the advantages of the optimal-tuning approach in the prediction of the electronic structure. At the same time, it gains accuracy in the prediction of binding energies for dispersively bound systems, as demonstrated on the S22 and S66 benchmark sets of weakly bound dimers.

  20. A system for using the air radioactivity measurements in a long range model to forecast cloud evolution

    Energy Technology Data Exchange (ETDEWEB)

    Galmarini, S.; Graziani, G. (Commission of the European Communities, Ispra (Italy). Joint Research Centre); Grippa, G.; De Cort, M. (Maind srl, Milan (Italy))

    1993-01-01

    A procedure was developed in the past to reduce uncertainties in long range transport model predictions mainly due to inputing windfield data to atmospheric transport models which are the result of the forecasts of global or regional circulation models. Measurements available in real-time of the air concentrations from national monitoring grids have been used to reduce the uncertainties. The system is based on a long range transport model which can run using a limited amount of meteorological information, and an interpolation routine which generates a new area source from the air measurements, available in real-time, at ground level. The procedure has now been fully automated and is available on a PC, with graphical output, to ease its use in emergency situations. The system requires a connection to the ECMWF network for meteorological input data and to a radiological data bank (ECURIE) or national monitoring networks for monitoring data. (author).

  1. Long-range dispersion interactions. II. Alkali-metal and rare-gas atoms

    International Nuclear Information System (INIS)

    Mitroy, J.; Zhang, J.-Y.

    2007-01-01

    The dispersion coefficients for the van der Waals interactions between the rare gases Ne, Ar, Kr, and Xe and the low-lying states of Li, Na, K, and Rb are estimated using a combination of ab initio and semiempirical methods. The rare-gas oscillator strength distributions for the quadrupole and octupole transitions were derived by using high-quality calculations of rare-gas polarizabilities and dispersion coefficients to tune Hartree-Fock single-particle energies and expectation values

  2. Driving range estimation for electric vehicles based on driving condition identification and forecast

    Science.gov (United States)

    Pan, Chaofeng; Dai, Wei; Chen, Liao; Chen, Long; Wang, Limei

    2017-10-01

    With the impact of serious environmental pollution in our cities combined with the ongoing depletion of oil resources, electric vehicles are becoming highly favored as means of transport. Not only for the advantage of low noise, but for their high energy efficiency and zero pollution. The Power battery is used as the energy source of electric vehicles. However, it does currently still have a few shortcomings, noticeably the low energy density, with high costs and short cycle life results in limited mileage compared with conventional passenger vehicles. There is great difference in vehicle energy consumption rate under different environment and driving conditions. Estimation error of current driving range is relatively large due to without considering the effects of environmental temperature and driving conditions. The development of a driving range estimation method will have a great impact on the electric vehicles. A new driving range estimation model based on the combination of driving cycle identification and prediction is proposed and investigated. This model can effectively eliminate mileage errors and has good convergence with added robustness. Initially the identification of the driving cycle is based on Kernel Principal Component feature parameters and fuzzy C referring to clustering algorithm. Secondly, a fuzzy rule between the characteristic parameters and energy consumption is established under MATLAB/Simulink environment. Furthermore the Markov algorithm and BP(Back Propagation) neural network method is utilized to predict the future driving conditions to improve the accuracy of the remaining range estimation. Finally, driving range estimation method is carried out under the ECE 15 condition by using the rotary drum test bench, and the experimental results are compared with the estimation results. Results now show that the proposed driving range estimation method can not only estimate the remaining mileage, but also eliminate the fluctuation of the

  3. Universal dispersion model for characterization of optical thin films over wide spectral range: Application to magnesium fluoride

    Science.gov (United States)

    Franta, Daniel; Nečas, David; Giglia, Angelo; Franta, Pavel; Ohlídal, Ivan

    2017-11-01

    Optical characterization of magnesium fluoride thin films is performed in a wide spectral range from far infrared to extreme ultraviolet (0.01-45 eV) utilizing the universal dispersion model. Two film defects, i.e. random roughness of the upper boundaries and defect transition layer at lower boundary are taken into account. An extension of universal dispersion model consisting in expressing the excitonic contributions as linear combinations of Gaussian and truncated Lorentzian terms is introduced. The spectral dependencies of the optical constants are presented in a graphical form and by the complete set of dispersion parameters that allows generating tabulated optical constants with required range and step using a simple utility in the newAD2 software package.

  4. Long-range forecast of all India summer monsoon rainfall using adaptive neuro-fuzzy inference system: skill comparison with CFSv2 model simulation and real-time forecast for the year 2015

    Science.gov (United States)

    Chaudhuri, S.; Das, D.; Goswami, S.; Das, S. K.

    2016-11-01

    All India summer monsoon rainfall (AISMR) characteristics play a vital role for the policy planning and national economy of the country. In view of the significant impact of monsoon system on regional as well as global climate systems, accurate prediction of summer monsoon rainfall has become a challenge. The objective of this study is to develop an adaptive neuro-fuzzy inference system (ANFIS) for long range forecast of AISMR. The NCEP/NCAR reanalysis data of temperature, zonal and meridional wind at different pressure levels have been taken to construct the input matrix of ANFIS. The membership of the input parameters for AISMR as high, medium or low is estimated with trapezoidal membership function. The fuzzified standardized input parameters and the de-fuzzified target output are trained with artificial neural network models. The forecast of AISMR with ANFIS is compared with non-hybrid multi-layer perceptron model (MLP), radial basis functions network (RBFN) and multiple linear regression (MLR) models. The forecast error analyses of the models reveal that ANFIS provides the best forecast of AISMR with minimum prediction error of 0.076, whereas the errors with MLP, RBFN and MLR models are 0.22, 0.18 and 0.73 respectively. During validation with observations, ANFIS shows its potency over the said comparative models. Performance of the ANFIS model is verified through different statistical skill scores, which also confirms the aptitude of ANFIS in forecasting AISMR. The forecast skill of ANFIS is also observed to be better than Climate Forecast System version 2. The real-time forecast with ANFIS shows possibility of deficit (65-75 cm) AISMR in the year 2015.

  5. How disturbance, competition, and dispersal interact to prevent tree range boundaries from keeping pace with climate change

    Science.gov (United States)

    Yu Liang; Matthew J. Duveneck; Eric J. Gustafson; Josep M. Serra-Diaz; Jonathan R. Thompson

    2018-01-01

    Climate change is expected to cause geographic shifts in tree species' ranges, but such shifts may not keep pace with climate changes because seed dispersal distances are often limited and competition-induced changes in community composition can be relatively slow. Disturbances may speed changes in community composition, but the interactions among climate change,...

  6. Comparative toxicity of two oil dispersants, superdispersant-25 and corexit 9527, to a range of coastal species.

    Science.gov (United States)

    Scarlett, Alan; Galloway, Tamara S; Canty, Martin; Smith, Emma L; Nilsson, Johanna; Rowland, Steven J

    2005-05-01

    The acute toxicity of the oil dispersant Corexit 9527 reported in the literature is highly variable. No peer-reviewed data exist for Superdispersant-25 (SD-25). This study compares the toxicity of the two dispersants to a range of marine species representing different phyla occupying a wide range of niches: The marine sediment-dwelling amphipod Corophium volutator (Pallas), the common mussel Mytilus edulis (L.), the symbiotic snakelocks anemone Anemonia viridis (Forskål), and the seagrass Zostera marina (L.). Organisms were exposed to static dispersant concentrations for 48-h and median lethal concentration (LC50), median effect concentration (EC50), and lowest-observable-effect concentration (LOEC) values obtained. The sublethal effects of 48-h exposures and the ability of species to recover for up to 72 h after exposure were quantified relative to the 48-h endpoints. Results indicated that the anemone lethality test was the most sensitive with LOECs of 20 ppm followed by mussel feeding rate, seagrass photosynthetic index and amphipod lethality, with mussel lethality being the least sensitive with LOECs of 250 ppm for both dispersants. The results were consistent with current theory that dispersants act physically and irreversibly on the respiratory organs and reversibly, depending on exposure time, on the nervous system. Superdispersant-25 was found overall to be less toxic than Corexit 9527 and its sublethal effects more likely to be reversible following short-term exposure.

  7. Analysis of stable components in the extended-range forecast for the coming 10–30 days in winter 2010 and 2011

    International Nuclear Information System (INIS)

    Wang Kuo; Zeng Yu-Xing; Wang Xu-Jia; Feng Guo-Lin

    2013-01-01

    In this paper we try to extract stable components in the extended-range forecast for the coming 10–30 days by using empirical orthogonal function (EOF) analysis, similarity coefficient, and some other methods based on the National Center for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis daily data. The comparisons of the coefficient of variance of climatological background field and truth data in winter between 2010 and 2011 are made. The method of extracting stable components and climatological background field can be helpful to increase forecasting skill. The forecasting skill improvement of air temperature is better than geopotential height at 500 hPa. Moreover, this method improves the predictability better in the Pacific Ocean. In China, the forecast in winter in Northeast China is more uncertain than in the other parts. (geophysics, astronomy, and astrophysics)

  8. Medium-Range Dispersion Experiments Downwind from a Shoreline in Near Neutral Conditions

    DEFF Research Database (Denmark)

    Gryning, Sven-Erik; Lyck, E.

    1980-01-01

    Five atmospheric dispersion experiments, all assigned Pasquill stability class D, were performed at Risø National Laboratory. The tracer sulphurhexafluoride was released at a height of 60 m from the Risø meteorological tower, situated on a peninsula in the Roskilde Fjord, Denmark, and was sampled...

  9. 3D Printed Prisms with Tunable Dispersion for the THz Frequency Range

    Science.gov (United States)

    Busch, Stefan F.; Castro-Camus, Enrique; Beltran-Mejia, Felipe; Balzer, Jan C.; Koch, Martin

    2018-06-01

    Here, we present a 3D printed prism for THz waves made out of an artificial dielectric material in which the dispersion can be tuned by external compression. The artificial material consists of thin dielectric layers with variable air spacings which has been produced using a fused deposition molding process. The material properties are carefully characterized and the functionality of the prisms is in a good agreement with the underlying theory. These prisms are durable, lightweight, inexpensive, and easy to produce.

  10. 3D Printed Prisms with Tunable Dispersion for the THz Frequency Range

    Science.gov (United States)

    Busch, Stefan F.; Castro-Camus, Enrique; Beltran-Mejia, Felipe; Balzer, Jan C.; Koch, Martin

    2018-04-01

    Here, we present a 3D printed prism for THz waves made out of an artificial dielectric material in which the dispersion can be tuned by external compression. The artificial material consists of thin dielectric layers with variable air spacings which has been produced using a fused deposition molding process. The material properties are carefully characterized and the functionality of the prisms is in a good agreement with the underlying theory. These prisms are durable, lightweight, inexpensive, and easy to produce.

  11. Incorporating Medium-Range Weather Forecasts in Seasonal Crop Scenarios over the Greater Horn of Africa to Support National/Regional/Local Decision Makers

    Science.gov (United States)

    Shukla, S.; Husak, G. J.; Funk, C. C.; Verdin, J. P.

    2015-12-01

    The USAID's Famine Early Warning Systems Network (FEWS NET) provides seasonal assessments of crop conditions over the Greater Horn of Africa (GHA) and other food insecure regions. These assessments and current livelihood, nutrition, market conditions and conflicts are used to generate food security scenarios that help national, regional and local decision makers target their resources and mitigate socio-economic losses. Among the various tools that FEWS NET uses is the FAO's Water Requirement Satisfaction Index (WRSI). The WRSI is a simple yet powerful crop assessment model that incorporates current moisture conditions (at the time of the issuance of forecast), precipitation scenarios, potential evapotranspiration and crop parameters to categorize crop conditions into different classes ranging from "failure" to "very good". The WRSI tool has been shown to have a good agreement with local crop yields in the GHA region. At present, the precipitation scenarios used to drive the WRSI are based on either a climatological forecast (that assigns equal chances of occurrence to all possible scenarios and has no skill over the forecast period) or a sea-surface temperature anomaly based scenario (which at best have skill at the seasonal scale). In both cases, the scenarios fail to capture the skill that can be attained by initial atmospheric conditions (i.e., medium-range weather forecasts). During the middle of a cropping season, when a week or two of poor rains can have a devastating effect, two weeks worth of skillful precipitation forecasts could improve the skill of the crop scenarios. With this working hypothesis, we examine the value of incorporating medium-range weather forecasts in improving the skill of crop scenarios in the GHA region. We use the NCEP's Global Ensemble Forecast system (GEFS) weather forecasts and examine the skill of crop scenarios generated using the GEFS weather forecasts with respect to the scenarios based solely on the climatological forecast

  12. How disturbance, competition, and dispersal interact to prevent tree range boundaries from keeping pace with climate change.

    Science.gov (United States)

    Liang, Yu; Duveneck, Matthew J; Gustafson, Eric J; Serra-Diaz, Josep M; Thompson, Jonathan R

    2018-01-01

    Climate change is expected to cause geographic shifts in tree species' ranges, but such shifts may not keep pace with climate changes because seed dispersal distances are often limited and competition-induced changes in community composition can be relatively slow. Disturbances may speed changes in community composition, but the interactions among climate change, disturbance and competitive interactions to produce range shifts are poorly understood. We used a physiologically based mechanistic landscape model to study these interactions in the northeastern United States. We designed a series of disturbance scenarios to represent varied disturbance regimes in terms of both disturbance extent and intensity. We simulated forest succession by incorporating climate change under a high-emissions future, disturbances, seed dispersal, and competition using the landscape model parameterized with forest inventory data. Tree species range boundary shifts in the next century were quantified as the change in the location of the 5th (the trailing edge) and 95th (the leading edge) percentiles of the spatial distribution of simulated species. Simulated tree species range boundary shifts in New England over the next century were far below (usually change (usually more than 110 km over 100 years) under a high-emissions scenario. Simulated species` ranges shifted northward at both the leading edge (northern boundary) and trailing edge (southern boundary). Disturbances may expedite species' recruitment into new sites, but they had little effect on the velocity of simulated range boundary shifts. Range shifts at the trailing edge tended to be associated with photosynthetic capacity, competitive ability for light and seed dispersal ability, whereas shifts at the leading edge were associated only with photosynthetic capacity and competition for light. This study underscores the importance of understanding the role of interspecific competition and disturbance when studying tree range

  13. Inverse problems using ANN in long range atmospheric dispersion with signature analysis picked scattered numerical sensors from CFD

    International Nuclear Information System (INIS)

    Sharma, Pavan K.; Gera, B.; Ghosh, A.K.; Kushwaha, H.S.

    2010-01-01

    Scalar dispersion in the atmosphere is an important area wherein different approaches are followed in development of good analytical model. The analyses based on Computational Fluid Dynamics (CFD) codes offer an opportunity of model development based on first principles of physics and hence such models have an edge over the existing models. Both forward and backward calculation methods are being developed for atmospheric dispersion around NPPs at BARC Forward modeling methods, which describe the atmospheric transport from sources to receptors, use forward-running transport and dispersion models or computational fluid dynamics models which are run many times, and the resulting dispersion field is compared to observations from multiple sensors. Backward or inverse modeling methods use only one model run in the reverse direction from the receptors to estimate the upwind sources. Inverse modeling methods include adjoint and tangent linear models, Kalman filters, and variational data assimilation, and neural network. The present paper is aimed at developing a new approach where the identified specific signatures at receptor points form the basis for source estimation or inversions. This approach is expected to reduce the large transient data sets to reduced and meaningful data sets. In fact this reduces the inherently transient data set into a time independent mean data set. Forward computation were carried out with CFD code for various case to generate a large set of data to train the ANN. Specific signature analysis was carried out to find the parameters of interest for ANN training like peak concentration, time to reach peak concentration and time to fall, the ANN was trained with data and source strength and location were predicted from ANN. Inverse problem was performed using ANN approach in long range atmospheric dispersion. An illustration of application of CFD code for atmospheric dispersion studies for a hypothetical case is also included in the paper. (author)

  14. Adaptive Blending of Model and Observations for Automated Short-Range Forecasting: Examples from the Vancouver 2010 Olympic and Paralympic Winter Games

    Science.gov (United States)

    Bailey, Monika E.; Isaac, George A.; Gultepe, Ismail; Heckman, Ivan; Reid, Janti

    2014-01-01

    An automated short-range forecasting system, adaptive blending of observations and model (ABOM), was tested in real time during the 2010 Vancouver Olympic and Paralympic Winter Games in British Columbia. Data at 1-min time resolution were available from a newly established, dense network of surface observation stations. Climatological data were not available at these new stations. This, combined with output from new high-resolution numerical models, provided a unique and exciting setting to test nowcasting systems in mountainous terrain during winter weather conditions. The ABOM method blends extrapolations in time of recent local observations with numerical weather predictions (NWP) model predictions to generate short-range point forecasts of surface variables out to 6 h. The relative weights of the model forecast and the observation extrapolation are based on performance over recent history. The average performance of ABOM nowcasts during February and March 2010 was evaluated using standard scores and thresholds important for Olympic events. Significant improvements over the model forecasts alone were obtained for continuous variables such as temperature, relative humidity and wind speed. The small improvements to forecasts of variables such as visibility and ceiling, subject to discontinuous changes, are attributed to the persistence component of ABOM.

  15. How disturbance, competition and dispersal interact to prevent tree range boundaries from keeping pace with climate change

    Science.gov (United States)

    Liang, Y.; Duveneck, M.; Gustafson, E. J.; Serra-Diaz, J. M.; Thompson, J. R.

    2017-12-01

    Climate change is expected to cause geographic shifts in tree species' ranges, but such shifts may not keep pace with climate changes because seed dispersal distances are often limited and competition-induced changes in community composition can be relatively slow. Disturbances may speed changes in community composition, but the interactions among climate change, disturbance and competitive interactions to produce range shifts are poorly understood. We used a physiologically-based mechanistic landscape model to study these interactions in the northeastern United States. We designed a series of disturbance scenarios to represent varied disturbance regimes in terms of both disturbance extent and intensity. We simulated forest succession by incorporating climate change under a high emissions future, disturbances, seed dispersal, and competition using the landscape model parameterized with forest inventory data. Tree species range boundary shifts in the next century were quantified as the change in the location of the 5th (the trailing edge) and 95th (the leading edge) percentiles of the spatial distribution of simulated species. Simulated tree species range boundary shifts in New England over the next century were far below (usually Disturbances may expedite species` recruitment into new sites, but they had little effect on the velocity of simulated range boundary shifts. Range shifts at the trailing edge tended to be associated with photosynthetic capacity, competitive ability for light and seed dispersal ability, whereas shifts at the leading edge were associated only with photosynthetic capacity and competition for light. This study underscores the importance of understanding the role of interspecific competition and disturbance when studying tree range shifts.

  16. Forecasting inundation from debris flows that grow during travel, with application to the Oregon Coast Range, USA

    Science.gov (United States)

    Reid, Mark E.; Coe, Jeffrey A.; Brien, Dianne

    2016-01-01

    Many debris flows increase in volume as they travel downstream, enhancing their mobility and hazard. Volumetric growth can result from diverse physical processes, such as channel sediment entrainment, stream bank collapse, adjacent landsliding, hillslope erosion and rilling, and coalescence of multiple debris flows; incorporating these varied phenomena into physics-based debris-flow models is challenging. As an alternative, we embedded effects of debris-flow growth into an empirical/statistical approach to forecast potential inundation areas within digital landscapes in a GIS framework. Our approach used an empirical debris-growth function to account for the effects of growth phenomena. We applied this methodology to a debris-flow-prone area in the Oregon Coast Range, USA, where detailed mapping revealed areas of erosion and deposition along paths of debris flows that occurred during a large storm in 1996. Erosion was predominant in stream channels with slopes > 5°. Using pre- and post-event aerial photography, we derived upslope contributing area and channel-length growth factors. Our method reproduced the observed inundation patterns produced by individual debris flows; it also generated reproducible, objective potential inundation maps for entire drainage networks. These maps better matched observations than those using previous methods that focus on proximal or distal regions of a drainage network.

  17. One-level modeling for diagnosing surface winds over complex terrain. II - Applicability to short-range forecasting

    Science.gov (United States)

    Alpert, P.; Getenio, B.; Zak-Rosenthal, R.

    1988-01-01

    The Alpert and Getenio (1988) modification of the Mass and Dempsey (1985) one-level sigma-surface model was used to study four synoptic events that included two winter cases (a Cyprus low and a Siberian high) and two summer cases. Results of statistical verification showed that the model is not only capable of diagnosing many details of surface mesoscale flow, but might also be useful for various applications which require operative short-range prediction of the diurnal changes of high-resolution surface flow over complex terrain, for example, in locating wildland fires, determining the dispersion of air pollutants, and predicting changes in wind energy or of surface wind for low-level air flights.

  18. Cellular automata-based forecasting of the impact of accidental fire and toxic dispersion in process industries

    International Nuclear Information System (INIS)

    Sarkar, Chinmoy; Abbasi, S.A.

    2006-01-01

    The strategies to prevent accidents from occurring in a process industry, or to minimize the harm if an accident does take place, always revolve around forecasting the likely accidents and their impacts. Based on the likely frequency and severity of the accidents, resources are committed towards preventing the accidents. Nearly all techniques of ranking hazardous units, be it the hazard and operability studies, fault tree analysis, hazard indice, etc. - qualitative as well as quantitative - depend essentially on the assessment of the likely frequency and the likely harm accidents in different units may cause. This fact makes it exceedingly important that the forecasting the accidents and their likely impact is done as accurately as possible. In the present study we introduce a new approach to accident forecasting based on the discrete modeling paradigm of cellular automata. In this treatment an accident is modeled as a self-evolving phenomena, the impact of which is strongly influenced by the size, nature, and position of the environmental components which lie in the vicinity of the accident site. The outward propagation of the mass, energy and momentum from the accident epicenter is modeled as a fast diffusion process occurring in discrete space-time coordinates. The quantum of energy and material that would flow into each discrete space element (cell) due to the accidental release is evaluated and the degree of vulnerability posed to the receptors if present in the cell is measured at the end of each time element. This approach is able to effectively take into account the modifications in the flux of energy and material which occur as a result of the heterogeneous environment prevailing between the accident epicenter and the receptor. Consequently, more realistic accident scenarios are generated than possible with the prevailing techniques. The efficacy of the approach has been illustrated with case studies

  19. Evaluation of medium-range ensemble flood forecasting based on calibration strategies and ensemble methods in Lanjiang Basin, Southeast China

    Science.gov (United States)

    Liu, Li; Gao, Chao; Xuan, Weidong; Xu, Yue-Ping

    2017-11-01

    Ensemble flood forecasts by hydrological models using numerical weather prediction products as forcing data are becoming more commonly used in operational flood forecasting applications. In this study, a hydrological ensemble flood forecasting system comprised of an automatically calibrated Variable Infiltration Capacity model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated. The hydrological model is optimized by the parallel programmed ε-NSGA II multi-objective algorithm. According to the solutions by ε-NSGA II, two differently parameterized models are determined to simulate daily flows and peak flows at each of the three hydrological stations. Then a simple yet effective modular approach is proposed to combine these daily and peak flows at the same station into one composite series. Five ensemble methods and various evaluation metrics are adopted. The results show that ε-NSGA II can provide an objective determination on parameter estimation, and the parallel program permits a more efficient simulation. It is also demonstrated that the forecasts from ECMWF have more favorable skill scores than other Ensemble Prediction Systems. The multimodel ensembles have advantages over all the single model ensembles and the multimodel methods weighted on members and skill scores outperform other methods. Furthermore, the overall performance at three stations can be satisfactory up to ten days, however the hydrological errors can degrade the skill score by approximately 2 days, and the influence persists until a lead time of 10 days with a weakening trend. With respect to peak flows selected by the Peaks Over Threshold approach, the ensemble means from single models or multimodels are generally underestimated, indicating that the ensemble mean can bring overall improvement in forecasting of flows. For

  20. The long-term forecast of Pakistan's electricity supply and demand: An application of long range energy alternatives planning

    International Nuclear Information System (INIS)

    Perwez, Usama; Sohail, Ahmed; Hassan, Syed Fahad; Zia, Usman

    2015-01-01

    The long-term forecasting of electricity demand and supply has assumed significant importance in fundamental research to provide sustainable solutions to the electricity issues. In this article, we provide an overview of structure of electric power sector of Pakistan and a summary of historical electricity demand & supply data, current status of divergent set of energy policies as a framework for development and application of a LEAP (Long-range Energy Alternate Planning) model of Pakistan's electric power sector. Pakistan's LEAP model is used to analyze the supply policy selections and demand assumptions for future power generation system on the basis of economics, technicality and implicit environmental implications. Three scenarios are enacted over the study period (2011–2030) which include BAU (Business-As-Usual), NC (New Coal) & GF (Green Future). The results of these scenarios are compared in terms of projected electricity demand & supply, net present cost analysis (discount rate at 4%, 7% and 10%) and GHG (greenhouse gas) emission reductions, along with sensitivity analysis to study the effect of varying parameters on total cost. A concluding section illustrates the policy implications of model for futuristic power generation and environmental policies in Pakistan. - Highlights: • Pakistan-specific electricity demand model is presented. • None of the scenarios exceeded the price of 12 US Cents/kWh. • By 2030, fuel cost is the most dominant factor to influence electricity per unit cost. • By 2030, CO_2 emissions per unit electricity will increase significantly in coal scenario relative to others. • By 2030, the penetration of renewable energy and conservation policies can save 70.6 tWh electricity.

  1. Range of Attraction of Pheromone Lures and Dispersal Behavior of Cerambycid Beetles

    Science.gov (United States)

    E. Dunn; J. Hough-Goldstein; L. M. Hanks; J. G. Millar; V. D' Amico

    2016-01-01

    Cerambycid beetles (Coleoptera: Cerambycidae) can locate suitable hosts and mates by sensing pheromones and plant volatiles. Many cerambycid pheromone components have been identified and are now produced synthetically for trap lures. The range over which these lures attract cerambycids within a forest, and the tendency for cerambycids to move out of a forest in...

  2. Population Structure and Dispersal Patterns within and between Atlantic and Mediterranean Populations of a Large-Range Pelagic Seabird

    Science.gov (United States)

    Genovart, Meritxell; Thibault, Jean-Claude; Igual, José Manuel; Bauzà-Ribot, Maria del Mar; Rabouam, Corinne; Bretagnolle, Vincent

    2013-01-01

    Dispersal is critically linked to the demographic and evolutionary trajectories of populations, but in most seabird species it may be difficult to estimate. Using molecular tools, we explored population structure and the spatial dispersal pattern of a highly pelagic but philopatric seabird, the Cory's shearwater Calonectris diomedea. Microsatellite fragments were analysed from samples collected across almost the entire breeding range of the species. To help disentangle the taxonomic status of the two subspecies described, the Atlantic form C. d. borealis and the Mediterranean form C. d. diomedea, we analysed genetic divergence between subspecies and quantified both historical and recent migration rates between the Mediterranean and Atlantic basins. We also searched for evidence of isolation by distance (IBD) and addressed spatial patterns of gene flow. We found a low genetic structure in the Mediterranean basin. Conversely, strong genetic differentiation appeared in the Atlantic basin. Even if the species was mostly philopatric (97%), results suggest recent dispersal between basins, especially from the Atlantic to the Mediterranean (aprox. 10% of migrants/generation across the last two generations). Long-term gene flow analyses also suggested an historical exchange between basins (about 70 breeders/generation). Spatial analysis of genetic variation indicates that distance is not the main factor in shaping genetic structure in this species. Given our results we recommend gathering more data before concluded whether these taxa should be treated as two species or subspecies. PMID:23950986

  3. Northward dispersal of sea kraits (Laticauda semifasciata beyond their typical range.

    Directory of Open Access Journals (Sweden)

    Jaejin Park

    Full Text Available Marine reptiles are declining globally, and recent climate change may be a contributing factor. The study of sea snakes collected beyond their typical distribution range provides valuable insight on how climate change affects marine reptile populations. Recently, we collected 12 Laticauda semifasciata (11 females, 1 male from the waters around southern South Korea-an area located outside its typical distribution range (Japan, China including Taiwan, Philippines and Indonesia. We investigated the genetic origin of Korean specimens by analyzing mitochondrial cytochrome b gene (Cytb sequences. Six individuals shared haplotypes with a group found in Taiwan-southern Ryukyu Islands, while the remaining six individuals shared haplotypes with a group encompassing the entire Ryukyu Archipelago. These results suggest L. semifasciata moved into Korean waters from the Taiwan-Ryukyu region via the Taiwan Warm Current and/or the Kuroshio Current, with extended survival facilitated by ocean warming. We highlight several contributing factors that increase the chances that L. semifasciata establishes new northern populations beyond the original distribution range.

  4. Forecasting the Range-wide Status of Polar Bears at Selected Times in the 21st Century

    Science.gov (United States)

    Steven C. Amstrup; Bruce G. Marcot; David C. Douglas

    2007-01-01

    To inform the U.S. Fish and Wildlife Service decision whether or not to list polar bears as threatened under the Endangered Species Act (ESA), we forecast the status of the world's polar bear (Ursus maritimus) populations 45, 75 and 100 years into the future. We applied the best available information about predicted changes in sea ice in the...

  5. Extending to seasonal scales the current usage of short range weather forecasts and climate projections for water management in Spain

    Science.gov (United States)

    Rodriguez-Camino, Ernesto; Voces, José; Sánchez, Eroteida; Navascues, Beatriz; Pouget, Laurent; Roldan, Tamara; Gómez, Manuel; Cabello, Angels; Comas, Pau; Pastor, Fernando; Concepción García-Gómez, M.°; José Gil, Juan; Gil, Delfina; Galván, Rogelio; Solera, Abel

    2016-04-01

    This presentation, first, briefly describes the current use of weather forecasts and climate projections delivered by AEMET for water management in Spain. The potential use of seasonal climate predictions for water -in particular dams- management is then discussed more in-depth, using a pilot experience carried out by a multidisciplinary group coordinated by AEMET and DG for Water of Spain. This initiative is being developed in the framework of the national implementation of the GFCS and the European project, EUPORIAS. Among the main components of this experience there are meteorological and hydrological observations, and an empirical seasonal forecasting technique that provides an ensemble of water reservoir inflows. These forecasted inflows feed a prediction model for the dam state that has been adapted for this purpose. The full system is being tested retrospectively, over several decades, for selected water reservoirs located in different Spanish river basins. The assessment includes an objective verification of the probabilistic seasonal forecasts using standard metrics, and the evaluation of the potential social and economic benefits, with special attention to drought and flooding conditions. The methodology of implementation of these seasonal predictions in the decision making process is being developed in close collaboration with final users participating in this pilot experience.

  6. NKS NordRisk II: Atlas of long-range atmospheric dispersion and deposition of radionuclides from selected risk sites in the Northern Hemisphere

    DEFF Research Database (Denmark)

    Smith Korsholm, Ulrik; Astrup, Poul; Lauritzen, Bent

    The present atlas has been developed within the NKS/NordRisk-II project "Nuclear risk from atmospheric dispersion in Northern Europe". The atlas describes risks from hypothetical long-range dispersion and deposition of radionuclides from 16 nuclear risk sites on the Northern Hemisphere...... spanning the climate variability associated with the North Atlantic Oscillation, and corresponding time evolution of the ensemble mean atmospheric dispersion....

  7. Thermal Diffusivity and Thermal Conductivity of Dispersed Glass Sphere Composites Over a Range of Volume Fractions

    Science.gov (United States)

    Carson, James K.

    2018-06-01

    Glass spheres are often used as filler materials for composites. Comparatively few articles in the literature have been devoted to the measurement or modelling of thermal properties of composites containing glass spheres, and there does not appear to be any reported data on the measurement of thermal diffusivities over a range of filler volume fractions. In this study, the thermal diffusivities of guar-gel/glass sphere composites were measured using a transient comparative method. The addition of the glass beads to the gel increased the thermal diffusivity of the composite, more than doubling the thermal diffusivity of the composite relative to the diffusivity of the gel at the maximum glass volume fraction of approximately 0.57. Thermal conductivities of the composites were derived from the thermal diffusivity measurements, measured densities and estimated specific heat capacities of the composites. Two approaches to modelling the effective thermal diffusivity were considered.

  8. Long- Range Forecasting Of The Onset Of Southwest Monsoon Winds And Waves Near The Horn Of Africa

    Science.gov (United States)

    2017-12-01

    conditions is also indicated ( S : strong, M: moderate, W: weak). ..............34 xi LIST OF TABLES Table 1. Table of correlation experiments conducted...2nd ed.). Essex, England: Pearson prentice hall, 317 pp. Saha, S ., and Coauthors, 2010: NCEP Climate Forecast System Reanalysis (CFSR) Selected...WAVES NEAR THE HORN OF AFRICA 5. FUNDING NUMBERS 6. AUTHOR( S ) Gary M. Vines 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) Naval Postgraduate

  9. Long Range River Discharge Forecasting Using the Gravity Recovery and Climate Experiment (GRACE) Satellite to Predict Conditions for Endemic Cholera

    Science.gov (United States)

    Jutla, A.; Akanda, A. S.; Colwell, R. R.

    2014-12-01

    Prediction of conditions of an impending disease outbreak remains a challenge but is achievable if the associated and appropriate large scale hydroclimatic process can be estimated in advance. Outbreaks of diarrheal diseases such as cholera, are related to episodic seasonal variability in river discharge in the regions where water and sanitation infrastructure are inadequate and insufficient. However, forecasting river discharge, few months in advance, remains elusive where cholera outbreaks are frequent, probably due to non-availability of geophysical data as well as transboundary water stresses. Here, we show that satellite derived water storage from Gravity Recovery and Climate Experiment Forecasting (GRACE) sensors can provide reliable estimates on river discharge atleast two months in advance over regional scales. Bayesian regression models predicted flooding and drought conditions, a prerequisite for cholera outbreaks, in Bengal Delta with an overall accuracy of 70% for upto 60 days in advance without using any other ancillary ground based data. Forecasting of river discharge will have significant impacts on planning and designing intervention strategies for potential cholera outbreaks in the coastal regions where the disease remain endemic and often fatal.

  10. Long range dependency and forecasting of housing price index and mortgage market rate: evidence of subprime crisis

    Directory of Open Access Journals (Sweden)

    Nadhem Selmi

    2015-05-01

    Full Text Available In this paper, we examine and forecast the House Price Index (HPI and mortgage market rate in terms of the description of the subprime crisis. We use a semi-parametric local polynomial Whittle estimator proposed by Shimotsu et al. (2005 [Shimotsu, K., & Phillips, P.C.B. (2005, Exact local Whittle estimation of fractional integration. The Annals of Statistics, 33(4, 1890-1933.] in a long memory parameter time series. Empirical investigation of HPI and mortgage market rate shows that these variables are more persistent when the d estimates are found on the Shimotsu method than on the one of Künsch (1987 [Künsch, H.R. (1987. Statistical aspects of self-similar processes. In Y. Prokhorov and V.V. Sazanov (eds., Proceedings of the First World Congress of the Bernoulli Society, VNU Science Press, Utrecht, 67-74.]. The estimating forecast values are more realistic and they strongly reflect the present US economy actuality in the two series as indicated by the forecast evaluation topics.

  11. Strategic Forecasting

    DEFF Research Database (Denmark)

    Duus, Henrik Johannsen

    2016-01-01

    Purpose: The purpose of this article is to present an overview of the area of strategic forecasting and its research directions and to put forward some ideas for improving management decisions. Design/methodology/approach: This article is conceptual but also informed by the author’s long contact...... and collaboration with various business firms. It starts by presenting an overview of the area and argues that the area is as much a way of thinking as a toolbox of theories and methodologies. It then spells out a number of research directions and ideas for management. Findings: Strategic forecasting is seen...... as a rebirth of long range planning, albeit with new methods and theories. Firms should make the building of strategic forecasting capability a priority. Research limitations/implications: The article subdivides strategic forecasting into three research avenues and suggests avenues for further research efforts...

  12. Improving long-range dispersion predictions with ETEX real-time and a-posteriori model evaluations

    International Nuclear Information System (INIS)

    Desiato, F.

    1997-01-01

    The Italian environmental Protection Agency (ANPA), which is responsible for the evaluation of the consequences of accidental releases into the atmosphere, has participated to both the real-time (phase-1) and a-posteriori (phase-2) ETEX model evaluations. The double benchmark actually constituted an invaluable experience for better understanding the skill and limits of the present long-range dispersion modelling capabilities. In particular, the strong difference between phase-1 and phase-2 model performance emphasised the opportunity to modify, improve or tune a number of specific aspects of the overall simulation. ETEX model runs were carried out with the Lagrangian particle model APOLLO. The meteorological input was constituted by ECMWF fields. Three-hourly average concentrations paired in space and time and time-integrated concentrations were used in the evaluation of the results, based on a set of statistical indexes and concentration contour lines and scatter diagrams

  13. Closure Report for Corrective Action Unit 412: Clean Slate I Plutonium Dispersion (TTR) Tonopah Test Range, Nevada, Revision 0

    International Nuclear Information System (INIS)

    Matthews, Patrick

    2016-01-01

    This Closure Report (CR) presents information supporting the clean closure of Corrective Action Unit (CAU) 412: Clean Slate I Plutonium Dispersion (TTR), located on the Tonopah Test Range, Nevada. CAU 412 consists of a release of radionuclides to the surrounding soil from a storage-transportation test conducted on May 25, 1963. Corrective action investigation (CAI) activities were performed in April and May 2015, as set forth in the Streamlined Approach for Environmental Restoration (SAFER) Plan for Corrective Action Unit 412: Clean Slate I Plutonium Dispersion (TTR), Tonopah Test Range, Nevada; and in accordance with the Soils Activity Quality Assurance Plan. The purpose of the CAI was to fulfill data needs as defined during the data quality objectives process. The CAU 412 dataset of investigation results was evaluated based on a data quality assessment. This assessment demonstrated the dataset is complete and acceptable for use in fulfilling the data needs identified by the data quality objectives process. This CR provides documentation and justification for the clean closure of CAU 412 under the FFACO without further corrective action. This justification is based on historical knowledge of the site, previous site investigations, implementation of the 1997 interim corrective action, and the results of the CAI. The corrective action of clean closure was confirmed as appropriate for closure of CAU 412 based on achievement of the following closure objectives: Radiological contamination at the site is less than the final action level using the ground troops exposure scenario (i.e., the radiological dose is less than the final action level): Removable alpha contamination is less than the high contamination area criterion: No potential source material is present at the site, and any impacted soil associated with potential source material has been removed so that remaining soil contains contaminants at concentrations less than the final action levels: and There is

  14. Closure Report for Corrective Action Unit 412: Clean Slate I Plutonium Dispersion (TTR) Tonopah Test Range, Nevada, Revision 0

    Energy Technology Data Exchange (ETDEWEB)

    Matthews, Patrick [Navarro, Las Vegas, NV (United States)

    2016-08-22

    This Closure Report (CR) presents information supporting the clean closure of Corrective Action Unit (CAU) 412: Clean Slate I Plutonium Dispersion (TTR), located on the Tonopah Test Range, Nevada. CAU 412 consists of a release of radionuclides to the surrounding soil from a storage–transportation test conducted on May 25, 1963. Corrective action investigation (CAI) activities were performed in April and May 2015, as set forth in the Streamlined Approach for Environmental Restoration (SAFER) Plan for Corrective Action Unit 412: Clean Slate I Plutonium Dispersion (TTR), Tonopah Test Range, Nevada; and in accordance with the Soils Activity Quality Assurance Plan. The purpose of the CAI was to fulfill data needs as defined during the data quality objectives process. The CAU 412 dataset of investigation results was evaluated based on a data quality assessment. This assessment demonstrated the dataset is complete and acceptable for use in fulfilling the data needs identified by the data quality objectives process. This CR provides documentation and justification for the clean closure of CAU 412 under the FFACO without further corrective action. This justification is based on historical knowledge of the site, previous site investigations, implementation of the 1997 interim corrective action, and the results of the CAI. The corrective action of clean closure was confirmed as appropriate for closure of CAU 412 based on achievement of the following closure objectives: Radiological contamination at the site is less than the final action level using the ground troops exposure scenario (i.e., the radiological dose is less than the final action level): Removable alpha contamination is less than the high contamination area criterion: No potential source material is present at the site, and any impacted soil associated with potential source material has been removed so that remaining soil contains contaminants at concentrations less than the final action levels: and There is

  15. NKS NordRisk. Atlas of long-range atmospheric dispersion and deposition of radionuclides from selected risk sites in the Northern Hemisphere

    International Nuclear Information System (INIS)

    Havskov Soerensen, J.; Baklanov, A.; Mahura, A.; Lauritzen, Bent; Mikkelsen, Torben

    2008-07-01

    Within the NKS NordRisk project, 'Nuclear risk from atmospheric dispersion in Northern Europe', the NKS NordRisk Atlas has been developed. The atlas describes risks from hypothetical long-range atmospheric dispersion and deposition of radionuclides from selected nuclear risk sites in the Northern Hemisphere. A number of case studies of long-term long-range atmospheric transport and deposition of radionuclides has been developed, based on two years of meteorological data. Radionuclide concentrations in air and radionuclide depositions have been evaluated and examples of long-term averages of the dispersion and deposition and of the variability around these mean values are provided. (au)

  16. NKS NordRisk. Atlas of long-range atmospheric dispersion and deposition of radionuclides from selected risk sites in the Northern Hemisphere

    Energy Technology Data Exchange (ETDEWEB)

    Havskov Soerensen, J.; Baklanov, A.; Mahura, A. (Danish Meteorological Institute, Copenhagen (Denmark)); Lauritzen, Bent; Mikkelsen, Torben (Technical Univ. of Denmark, Risoe National Lab. for Sustainable Energy, Roskilde (Denmark))

    2008-07-15

    Within the NKS NordRisk project, 'Nuclear risk from atmospheric dispersion in Northern Europe', the NKS NordRisk Atlas has been developed. The atlas describes risks from hypothetical long-range atmospheric dispersion and deposition of radionuclides from selected nuclear risk sites in the Northern Hemisphere. A number of case studies of long-term long-range atmospheric transport and deposition of radionuclides has been developed, based on two years of meteorological data. Radionuclide concentrations in air and radionuclide depositions have been evaluated and examples of long-term averages of the dispersion and deposition and of the variability around these mean values are provided. (au)

  17. Effects of an assimilation of radar and satellite data on a very-short range forecast of heavy convective rainfalls

    Czech Academy of Sciences Publication Activity Database

    Sokol, Zbyněk

    2009-01-01

    Roč. 93, 1-3 (2009), s. 188-206 ISSN 0169-8095. [European Conference on Severe Storms /4./. Miramare -Trieste, 10.09.2007-14.09.2007] R&D Projects: GA ČR GA205/07/0905; GA MŠk OC 112; GA MŠk 1P05ME748 Institutional research plan: CEZ:AV0Z30420517 Keywords : Precipitation forecast * NWP model * Assimilation of radar and satellite data * Local convective precipitation Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.811, year: 2009 http://www.sciencedirect.com/science/journal/01698095

  18. NKS NordRisk II: Atlas of long-range atmospheric dispersion and deposition of radionuclides from selected risk sites in the Northern Hemisphere

    International Nuclear Information System (INIS)

    Smith Korsholm, U.; Havskov Soerensen, J.; Astrup, P.; Lauritzen, B.

    2011-04-01

    The present atlas has been developed within the NKS/NordRisk-II project 'Nuclear risk from atmospheric dispersion in Northern Europe'. The atlas describes risks from hypothetical long-range dispersion and deposition of radionuclides from 16 nuclear risk sites on the Northern Hemisphere. The atmospheric dispersion model calculations cover a period of 30 days following each release to ensure almost complete deposition of the dispersed material. The atlas contains maps showing the total deposition and time-integrated air concentration of Cs-137 and I-131 based on three years of meteorological data spanning the climate variability associated with the North Atlantic Oscillation, and corresponding time evolution of the ensemble mean atmospheric dispersion. (Author)

  19. NKS NordRisk II: Atlas of long-range atmospheric dispersion and deposition of radionuclides from selected risk sites in the Northern Hemisphere

    Energy Technology Data Exchange (ETDEWEB)

    Smith Korsholm, U.; Havskov Soerensen, J. (Danish Meteorological Institute (DMI), Copenhagen (Denmark)); Astrup, P.; Lauritzen, B. (Technical Univ. of Denmark, Risoe National Lab. for Sustainable Energy. Radiation Research Div., Roskilde (Denmark))

    2011-04-15

    The present atlas has been developed within the NKS/NordRisk-II project 'Nuclear risk from atmospheric dispersion in Northern Europe'. The atlas describes risks from hypothetical long-range dispersion and deposition of radionuclides from 16 nuclear risk sites on the Northern Hemisphere. The atmospheric dispersion model calculations cover a period of 30 days following each release to ensure almost complete deposition of the dispersed material. The atlas contains maps showing the total deposition and time-integrated air concentration of Cs-137 and I-131 based on three years of meteorological data spanning the climate variability associated with the North Atlantic Oscillation, and corresponding time evolution of the ensemble mean atmospheric dispersion. (Author)

  20. Linking long-range weather forecasts and heat consumption as a determining factor when buying fuel chips for town heating plants

    International Nuclear Information System (INIS)

    Rolev, A.-M.

    1991-12-01

    The aim of this study is to test whether long-range weather forecasts from the meteorological services can be used as a determining factor when buying fuel chips. In the study the fuel consumption of heating plants and the factors determining the monthly consumption are mentioned. Degree-day statistics in Denmark for the last 30 years are explained as well as the difficulties in conjunction with the prediction of long-range weather conditions. This study compares degree days in 1989-1990 month by month with the actual and theoretic chip consumption in three different heating plants the same year. The theoretic chip consumption is calculated on the basis of degree days in a ''standard year'' and the annual chip consumption of the heating plant, among other things. Furthermore, on the basis of degree-day statistics the report makes it possible to estimate the monthly chip consumption of a heating plant in a ''standard year'', in an extremely cold year (maximum degree days), and in an extremely warm year (minimum degree days). However, not everything can be predicted, and it is not yet possible to predict reliable weather forecasts for more than 5 days ahead. The study concludes that long-range weather forecasts cannot be used as a determining factor when buying fuel chips for heating plants. When buying fuel chips one must still use statistics and degree days, supplimented by figures based on experience from actual chip consumption in the individual heating plant. These figures take into consideration the different types of heating plants, as well as heat supply, chip-supplier, storing facilities, other fuels, etc. (au)

  1. The ability to use FLEXPART in simulation of the long-range radioactive materials dispersed from nuclear power plants near Vietnam border

    International Nuclear Information System (INIS)

    Pham Kim Long; Pham Duy Hien; Nguyen Hao Quang; Do Xuan Anh; Duong Duc Thang; Doan Quang Tuyen

    2016-01-01

    FLEXPART is a Lagrangian transport and dispersion model suitable for the simulation of a large range of atmospheric transport processes. FLEXPART has been researched and applied in simulation of the long-range dispersion of radioactive materials. It can be applicable to the problem of radioactive materials released from the nuclear power plants impact on Vietnam. This report presents simulation of radioactive dispersion from the accident assumed Fangchenggang and Changjiang nuclear power plants in China with the FLEXPART, using meteorological data from the National Centers for Environmental Prediction (NCEP). The results of simulations and analyzing showed good applicability of FLEXPART for a long-range radioactive materials dispersion. The preliminary simulation results show that the impact of the radioactive material dispersion in Vietnam varies by the well-known characteristics of the monsoon of our country. Winter is the time when the dominant northeast winds up radioactive dispersion most towards our country, its sphere of influence extends from the Northeast (Quang Ninh) to North Central (Da Nang). (author)

  2. Modeling emerald ash borer dispersal using percolation theory: estimating the rate of range expansion in a fragmented landscape

    Science.gov (United States)

    Robin A. J. Taylor; Daniel A. Herms; Louis R. Iverson

    2008-01-01

    The dispersal of organisms is rarely random, although diffusion processes can be useful models for movement in approximately homogeneous environments. However, the environments through which all organisms disperse are far from uniform at all scales. The emerald ash borer (EAB), Agrilus planipennis, is obligate on ash (Fraxinus spp...

  3. Influence of dispersing technique and irradiation on the structure of polyethylene in polypropylene matrix in a wide temperature range

    International Nuclear Information System (INIS)

    Antipov, E.M.; Kuptsov, S.A.; Kuz'min, N.N.; Pavlov, S.A.; AN SSSR, Moscow. Inst. Neftekhimicheskogo Sinteza)

    1988-01-01

    The structure of PE dispersed into PP matrix through solution or melt has been studied by X-ray analysis method. In oriented composition melting of HDPE after action of ionizing irradiation is accompanied by transition of some crystallites into pseudohexagonal modification. The fraction of transformed chains depends on the irradiation dose, dispersion method and conditions of orientation

  4. Robust Approaches to Forecasting

    OpenAIRE

    Jennifer Castle; David Hendry; Michael P. Clements

    2014-01-01

    We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models. Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift. We derive the resulting forecast biases and error variances, and indicate when the methods ar...

  5. Are post-dispersed seeds of Eucalyptus globulus predated in the introduced range? Evidence from an experiment in Portugal

    Directory of Open Access Journals (Sweden)

    E. Deus

    2018-04-01

    Full Text Available Plantations of Eucalyptus globulus Labill. have been expanding rapidly worldwide. The species is considered invasive in several regions. While in the native range, post-dispersal seed predation is known to severely limit eucalypt recruitment, there is no experimental evidence of seed predation in the introduced range. We hypothesised that E. globulus seeds largely escape predation in Portugal, which may explain its prolific recruitment in some locations. We tested this hypothesis in central Portugal by exposing E. globulus seeds to the local fauna. For comparison purposes, we also used seeds from locally common species: Acacia dealbata Link (alien, larger, elaiosome-bearing seeds and Cistus salviifolius L. (native, similarly sized seeds. We installed 30 feeding stations across three study sites, each one dominated by one study species. Each feeding station featured four feeders with different animal-access treatments: invertebrates; vertebrates; full access; no access (control. We placed five seeds of each plant species every day in each feeder and registered the number of seeds missing, eaten and elaiosome detached over 9 summer days. Eucalyptus globulus seeds were highly attractive to fauna in the three sites. Nearly half of E. globulus seeds were predated or removed, thus contradicting our hypothesis. Surprisingly, E. globulus and A. dealbata seeds were used by animals in similar proportions and C. salviifolius seeds were the least preferred. Vertebrates were the predominant seed predators and preferred the alien seeds. Invertebrates used all seed species in similar proportions. We found spatial variation regarding the predominant type of seed predators and the levels of seed predation according to the following patterns: predominance of vertebrates; predominance of invertebrates; negligible seed predator activity. Locations with negligible seed predation were abundant and scattered across the study area. Such spatial variation may

  6. Short-range forecast of Shershnevskoie (South Ural) water-storage algal blooms: preliminary results of predictors' choosing and membership functions' construction

    Science.gov (United States)

    Gayazova, Anna; Abdullaev, Sanjar

    2014-05-01

    Short-range forecasting of algal blooms in drinking water reservoirs and other waterbodies is an actual element of water treatment system. Particularly, Shershnevskoie reservoir - the source of drinking water for Chelyabinsk city (South Ural region of Russia) - is exposed to interannual, seasonal and short-range fluctuations of blue-green alga Aphanizomenon flos-aquae and other dominant species abundance, which lead to technological problems and economic costs and adversely affect the water treatment quality. Whereas the composition, intensity and the period of blooms affected not only by meteorological seasonal conditions but also by ecological specificity of waterbody, that's important to develop object-oriented forecasting, particularly, search for an optimal number of predictors for such forecasting. Thereby, firstly fuzzy logic and fuzzy artificial neural network patterns for blue-green alga Microcystis aeruginosa (M. aeruginosa) blooms prediction in nearby undrained Smolino lake were developed. These results subsequently served as the base to derive membership functions for Shernevskoie reservoir forecasting patterns. Time series with the total lenght about 138-159 days of dominant species seasonal abundance, water temperature, cloud cover, wind speed, mineralization, phosphate and nitrate concentrations were obtained through field observations held at Lake Smolino (Chelyabinsk) in the warm season of 2009 and 2011 with time resolution of 2-7 days. The cross-correlation analysis of the data revealed the potential predictors of M. aeruginosa abundance quasi-periodic oscillations: green alga Pediastrum duplex (P. duplex) abundance and mineralization for 2009, P. duplex abundance, water temperature and concentration of nitrates for 2011. According to the results of cross-correlation analysis one membership function "P. duplex abundance" and one rule linking M. aeruginosa and P. duplex abundances were set up for database of 2009. Analogically, for database of 2011

  7. Energy dispersion of x-ray continua in the energy range 9kev to 19kev refraction on Si wafers

    International Nuclear Information System (INIS)

    Ebel, H.; Streli, C.; Pepponi, G.; Wobrauschek, P.

    2000-01-01

    Total reflection of x-rays in matter at given grazing incidence angle is characterized by the occurrence of an energy cut-off. Photons with energies greater than the cut-off energy penetrate into matter and are refracted according to a transition from the optically more dense to the optically less dense medium. Since the refractive index depends on photon energy, an energy dispersion of continuous x-radiation is observed. The present investigation is dedicated to the energy dispersion of continuous x-radiation (Mo, 45 kV) by Si wafers. Theory and experimental results are in excellent agreement. (author)

  8. The interplay of covalency, hydrogen bonding, and dispersion leads to a long range chiral network: The example of 2-butanol

    International Nuclear Information System (INIS)

    Liriano, Melissa L.; Lewis, Emily A.; Murphy, Colin J.; Lawton, Timothy J.; Marcinkowski, Matthew D.; Therrien, Andrew J.; Sykes, E. Charles H.; Carrasco, Javier; Michaelides, Angelos

    2016-01-01

    The assembly of complex structures in nature is driven by an interplay between several intermolecular interactions, from strong covalent bonds to weaker dispersion forces. Understanding and ultimately controlling the self-assembly of materials requires extensive study of how these forces drive local nanoscale interactions and how larger structures evolve. Surface-based self-assembly is particularly amenable to modeling and measuring these interactions in well-defined systems. This study focuses on 2-butanol, the simplest aliphatic chiral alcohol. 2-butanol has recently been shown to have interesting properties as a chiral modifier of surface chemistry; however, its mode of action is not fully understood and a microscopic understanding of the role non-covalent interactions play in its adsorption and assembly on surfaces is lacking. In order to probe its surface properties, we employed high-resolution scanning tunneling microscopy and density functional theory (DFT) simulations. We found a surprisingly rich degree of enantiospecific adsorption, association, chiral cluster growth and ultimately long range, highly ordered chiral templating. Firstly, the chiral molecules acquire a second chiral center when adsorbed to the surface via dative bonding of one of the oxygen atom lone pairs. This interaction is controlled via the molecule’s intrinsic chiral center leading to monomers of like chirality, at both chiral centers, adsorbed on the surface. The monomers then associate into tetramers via a cyclical network of hydrogen bonds with an opposite chirality at the oxygen atom. The evolution of these square units is surprising given that the underlying surface has a hexagonal symmetry. Our DFT calculations, however, reveal that the tetramers are stable entities that are able to associate with each other by weaker van der Waals interactions and tessellate in an extended square network. This network of homochiral square pores grows to cover the whole Au(111) surface. Our

  9. The interplay of covalency, hydrogen bonding, and dispersion leads to a long range chiral network: The example of 2-butanol

    Energy Technology Data Exchange (ETDEWEB)

    Liriano, Melissa L.; Lewis, Emily A.; Murphy, Colin J.; Lawton, Timothy J.; Marcinkowski, Matthew D.; Therrien, Andrew J.; Sykes, E. Charles H., E-mail: charles.sykes@tufts.edu [Department of Chemistry, Tufts University, Medford, Massachusetts 02155 (United States); Carrasco, Javier [CIC Energigune, Albert Einstein 48, 01510 Miñano, Álava (Spain); Michaelides, Angelos [Thomas Young Centre, London Centre for Nanotechnology and Department of Physics and Astronomy, University College London, London WC1E 6BT (United Kingdom)

    2016-03-07

    The assembly of complex structures in nature is driven by an interplay between several intermolecular interactions, from strong covalent bonds to weaker dispersion forces. Understanding and ultimately controlling the self-assembly of materials requires extensive study of how these forces drive local nanoscale interactions and how larger structures evolve. Surface-based self-assembly is particularly amenable to modeling and measuring these interactions in well-defined systems. This study focuses on 2-butanol, the simplest aliphatic chiral alcohol. 2-butanol has recently been shown to have interesting properties as a chiral modifier of surface chemistry; however, its mode of action is not fully understood and a microscopic understanding of the role non-covalent interactions play in its adsorption and assembly on surfaces is lacking. In order to probe its surface properties, we employed high-resolution scanning tunneling microscopy and density functional theory (DFT) simulations. We found a surprisingly rich degree of enantiospecific adsorption, association, chiral cluster growth and ultimately long range, highly ordered chiral templating. Firstly, the chiral molecules acquire a second chiral center when adsorbed to the surface via dative bonding of one of the oxygen atom lone pairs. This interaction is controlled via the molecule’s intrinsic chiral center leading to monomers of like chirality, at both chiral centers, adsorbed on the surface. The monomers then associate into tetramers via a cyclical network of hydrogen bonds with an opposite chirality at the oxygen atom. The evolution of these square units is surprising given that the underlying surface has a hexagonal symmetry. Our DFT calculations, however, reveal that the tetramers are stable entities that are able to associate with each other by weaker van der Waals interactions and tessellate in an extended square network. This network of homochiral square pores grows to cover the whole Au(111) surface. Our

  10. A preliminary study of the impact of the ERS 1 C band scatterometer wind data on the European Centre for Medium-Range Weather Forecasts global data assimilation system

    Science.gov (United States)

    Hoffman, Ross N.

    1993-01-01

    A preliminary assessment of the impact of the ERS 1 scatterometer wind data on the current European Centre for Medium-Range Weather Forecasts analysis and forecast system has been carried out. Although the scatterometer data results in changes to the analyses and forecasts, there is no consistent improvement or degradation. Our results are based on comparing analyses and forecasts from assimilation cycles. The two sets of analyses are very similar except for the low level wind fields over the ocean. Impacts on the analyzed wind fields are greater over the southern ocean, where other data are scarce. For the most part the mass field increments are too small to balance the wind increments. The effect of the nonlinear normal mode initialization on the analysis differences is quite small, but we observe that the differences tend to wash out in the subsequent 6-hour forecast. In the Northern Hemisphere, analysis differences are very small, except directly at the scatterometer locations. Forecast comparisons reveal large differences in the Southern Hemisphere after 72 hours. Notable differences in the Northern Hemisphere do not appear until late in the forecast. Overall, however, the Southern Hemisphere impacts are neutral. The experiments described are preliminary in several respects. We expect these data to ultimately prove useful for global data assimilation.

  11. Drivers and uncertainties of forecasted range shifts for warm-water fishes under climate and land cover change

    Science.gov (United States)

    Bouska, Kristen; Whitledge, Gregory W.; Lant, Christopher; Schoof, Justin

    2018-01-01

    Land cover is an important determinant of aquatic habitat and is projected to shift with climate changes, yet climate-driven land cover changes are rarely factored into climate assessments. To quantify impacts and uncertainty of coupled climate and land cover change on warm-water fish species’ distributions, we used an ensemble model approach to project distributions of 14 species. For each species, current range projections were compared to 27 scenario-based projections and aggregated to visualize uncertainty. Multiple regression and model selection techniques were used to identify drivers of range change. Novel, or no-analogue, climates were assessed to evaluate transferability of models. Changes in total probability of occurrence ranged widely across species, from a 63% increase to a 65% decrease. Distributional gains and losses were largely driven by temperature and flow variables and underscore the importance of habitat heterogeneity and connectivity to facilitate adaptation to changing conditions. Finally, novel climate conditions were driven by mean annual maximum temperature, which stresses the importance of understanding the role of temperature on fish physiology and the role of temperature-mitigating management practices.

  12. Fine-scale population genetic structure and short-range sex-biased dispersal in a solitary carnivore, Lutra lutra

    Czech Academy of Sciences Publication Activity Database

    Quaglietta, L.; Fonseca, V. C.; Hájková, Petra; Mira, A.; Boitani, L.

    2013-01-01

    Roč. 94, č. 3 (2013), s. 561-571 ISSN 0022-2372 Institutional support: RVO:68081766 Keywords : conservation genetics * dispersal distances * Eurasian otter * isolation by distance * radiotracking * restricted gene flow * spatial relatedness structure * spatiotemporal scale Subject RIV: EG - Zoology Impact factor: 2.225, year: 2013

  13. Storm Identification, Tracking and Forecasting Using High-Resolution Images of Short-Range X-Band Radar

    Directory of Open Access Journals (Sweden)

    Sajid Shah

    2015-05-01

    Full Text Available Rain nowcasting is an essential part of weather monitoring. It plays a vital role in human life, ranging from advanced warning systems to scheduling open air events and tourism. A nowcasting system can be divided into three fundamental steps, i.e., storm identification, tracking and nowcasting. The main contribution of this work is to propose procedures for each step of the rain nowcasting tool and to objectively evaluate the performances of every step, focusing on two-dimension data collected from short-range X-band radars installed in different parts of Italy. This work presents the solution of previously unsolved problems in storm identification: first, the selection of suitable thresholds for storm identification; second, the isolation of false merger (loosely-connected storms; and third, the identification of a high reflectivity sub-storm within a large storm. The storm tracking step of the existing tools, such as TITANand SCIT, use only up to two storm attributes, i.e., center of mass and area. It is possible to use more attributes for tracking. Furthermore, the contribution of each attribute in storm tracking is yet to be investigated. This paper presents a novel procedure called SALdEdA (structure, amplitude, location, eccentricity difference and areal difference for storm tracking. This work also presents the contribution of each component of SALdEdA in storm tracking. The second order exponential smoothing strategy is used for storm nowcasting, where the growth and decay of each variable of interest is considered to be linear. We evaluated the major steps of our method. The adopted techniques for automatic threshold calculation are assessed with a 97% goodness. False merger and sub-storms within a cluster of storms are successfully handled. Furthermore, the storm tracking procedure produced good results with an accuracy of 99.34% for convective events and 100% for stratiform events.

  14. Flood forecasting and uncertainty of precipitation forecasts

    International Nuclear Information System (INIS)

    Kobold, Mira; Suselj, Kay

    2004-01-01

    The timely and accurate flood forecasting is essential for the reliable flood warning. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual rainfall - runoff models enable the estimation of these parameters and lead to useful operational forecasts. The accurate rainfall is the most important input into hydrological models. The input for the rainfall can be real time rain-gauges data, or weather radar data, or meteorological forecasted precipitation. The torrential nature of streams and fast runoff are characteristic for the most of the Slovenian rivers. Extensive damage is caused almost every year- by rainstorms affecting different regions of Slovenia' The lag time between rainfall and runoff is very short for Slovenian territory and on-line data are used only for now casting. Forecasted precipitations are necessary for hydrological forecast for some days ahead. ECMWF (European Centre for Medium-Range Weather Forecasts) gives general forecast for several days ahead while more detailed precipitation data with limited area ALADIN/Sl model are available for two days ahead. There is a certain degree of uncertainty using such precipitation forecasts based on meteorological models. The variability of precipitation is very high in Slovenia and the uncertainty of ECMWF predicted precipitation is very large for Slovenian territory. ECMWF model can predict precipitation events correctly, but underestimates amount of precipitation in general The average underestimation is about 60% for Slovenian region. The predictions of limited area ALADIN/Si model up to; 48 hours ahead show greater applicability in hydrological forecasting. The hydrological models are sensitive to precipitation input. The deviation of runoff is much bigger than the rainfall deviation. Runoff to rainfall error fraction is about 1.6. If spatial and time distribution

  15. Forecasting Kp from solar wind data: input parameter study using 3-hour averages and 3-hour range values

    Science.gov (United States)

    Wintoft, Peter; Wik, Magnus; Matzka, Jürgen; Shprits, Yuri

    2017-11-01

    We have developed neural network models that predict Kp from upstream solar wind data. We study the importance of various input parameters, starting with the magnetic component Bz, particle density n, and velocity V and then adding total field B and the By component. As we also notice a seasonal and UT variation in average Kp we include functions of day-of-year and UT. Finally, as Kp is a global representation of the maximum range of geomagnetic variation over 3-hour UT intervals we conclude that sudden changes in the solar wind can have a big effect on Kp, even though it is a 3-hour value. Therefore, 3-hour solar wind averages will not always appropriately represent the solar wind condition, and we introduce 3-hour maxima and minima values to some degree address this problem. We find that introducing total field B and 3-hour maxima and minima, derived from 1-minute solar wind data, have a great influence on the performance. Due to the low number of samples for high Kp values there can be considerable variation in predicted Kp for different networks with similar validation errors. We address this issue by using an ensemble of networks from which we use the median predicted Kp. The models (ensemble of networks) provide prediction lead times in the range 20-90 min given by the time it takes a solar wind structure to travel from L1 to Earth. Two models are implemented that can be run with real time data: (1) IRF-Kp-2017-h3 uses the 3-hour averages of the solar wind data and (2) IRF-Kp-2017 uses in addition to the averages, also the minima and maxima values. The IRF-Kp-2017 model has RMS error of 0.55 and linear correlation of 0.92 based on an independent test set with final Kp covering 2 years using ACE Level 2 data. The IRF-Kp-2017-h3 model has RMSE = 0.63 and correlation = 0.89. We also explore the errors when tested on another two-year period with real-time ACE data which gives RMSE = 0.59 for IRF-Kp-2017 and RMSE = 0.73 for IRF-Kp-2017-h3. The errors as function

  16. Potential spread of highly pathogenic avian influenza H5N1 by wildfowl: dispersal ranges and rates determined from large-scale satellite telemetry

    Science.gov (United States)

    Gaidet, Nicolas; Cappelle, Julien; Takekawa, John Y.; Prosser, Diann J.; Iverson, Samuel A.; Douglas, David C.; Perry, William M.; Mundkur, Taej; Newman, Scott H.

    2010-01-01

    1. Migratory birds are major candidates for long-distance dispersal of zoonotic pathogens. In recent years, wildfowl have been suspected of contributing to the rapid geographic spread of the highly pathogenic avian influenza (HPAI) H5N1 virus. Experimental infection studies reveal that some wild ducks, geese and swans shed this virus asymptomatically and hence have the potential to spread it as they move. 2. We evaluate the dispersive potential of HPAI H5N1 viruses by wildfowl through an analysis of the movement range and movement rate of birds monitored by satellite telemetry in relation to the apparent asymptomatic infection duration (AID) measured in experimental studies. We analysed the first large-scale data set of wildfowl movements, including 228 birds from 19 species monitored by satellite telemetry in 2006–2009, over HPAI H5N1 affected regions of Asia, Europe and Africa. 3. Our results indicate that individual migratory wildfowl have the potential to disperse HPAI H5N1 over extensive distances, being able to perform movements of up to 2900 km within timeframes compatible with the duration of asymptomatic infection. 4. However, the likelihood of such virus dispersal over long distances by individual wildfowl is low: we estimate that for an individual migratory bird there are, on average, only 5–15 days per year when infection could result in the dispersal of HPAI H5N1 virus over 500 km. 5. Staging at stopover sites during migration is typically longer than the period of infection and viral shedding, preventing birds from dispersing a virus over several consecutive but interrupted long-distance movements. Intercontinental virus dispersion would therefore probably require relay transmission between a series of successively infected migratory birds. 6. Synthesis and applications. Our results provide a detailed quantitative assessment of the dispersive potential of HPAI H5N1 virus by selected migratory birds. Such dispersive potential rests on the

  17. Ensemble atmospheric dispersion calculations for decision support systems

    International Nuclear Information System (INIS)

    Borysiewicz, M.; Potempski, S.; Galkowski, A.; Zelazny, R.

    2003-01-01

    This document describes two approaches to long-range atmospheric dispersion of pollutants based on the ensemble concept. In the first part of the report some experiences related to the exercises undertaken under the ENSEMBLE project of the European Union are presented. The second part is devoted to the implementation of mesoscale numerical prediction models RAMS and atmospheric dispersion model HYPACT on Beowulf cluster and theirs usage for ensemble forecasting and long range atmospheric ensemble dispersion calculations based on available meteorological data from NCEO, NOAA (USA). (author)

  18. Precipitable water and surface humidity over global oceans from special sensor microwave imager and European Center for Medium Range Weather Forecasts

    Science.gov (United States)

    Liu, W. T.; Tang, Wenqing; Wentz, Frank J.

    1992-01-01

    Global fields of precipitable water W from the special sensor microwave imager were compared with those from the European Center for Medium Range Weather Forecasts (ECMWF) model. They agree over most ocean areas; both data sets capture the two annual cycles examined and the interannual anomalies during an ENSO episode. They show significant differences in the dry air masses over the eastern tropical-subtropical oceans, particularly in the Southern Hemisphere. In these regions, comparisons with radiosonde data indicate that overestimation by the ECMWF model accounts for a large part of the differences. As a check on the W differences, surface-level specific humidity Q derived from W, using a statistical relation, was compared with Q from the ECMWF model. The differences in Q were found to be consistent with the differences in W, indirectly validating the Q-W relation. In both W and Q, SSMI was able to discern clearly the equatorial extension of the tongues of dry air in the eastern tropical ocean, while both ECMWF and climatological fields have reduced spatial gradients and weaker intensity.

  19. Forecast Combinations

    OpenAIRE

    Timmermann, Allan G

    2005-01-01

    Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the d...

  20. Forecast combinations

    OpenAIRE

    Aiolfi, Marco; Capistrán, Carlos; Timmermann, Allan

    2010-01-01

    We consider combinations of subjective survey forecasts and model-based forecasts from linear and non-linear univariate specifications as well as multivariate factor-augmented models. Empirical results suggest that a simple equal-weighted average of survey forecasts outperform the best model-based forecasts for a majority of macroeconomic variables and forecast horizons. Additional improvements can in some cases be gained by using a simple equal-weighted average of survey and model-based fore...

  1. Short range forecasting of sea breeze generated thunderstorms at the Kennedy Space Center: A real-time experiment using a primitive equation mesoscale numerical model

    Science.gov (United States)

    Lyons, Walter A.; Schuh, Jerome A.; Moon, Dennis; Pielke, Roger A.; Cotton, William; Arritt, Raymond

    1987-01-01

    The operational efficiency of using guidance from a mesoscale numerical model to improve sea breeze thunderstorm forecasts at and around the Shuttle landing strip was assessed. The Prognostic Three-Dimensional Mesoscale (P3DM) model, developed as a sea breeze model, reveals a strong correlation between regions of mesoscale convergence and the triggering of sea breeze convection thunderstorms. The P3DM was modified to generate stability parameters familiar to the operational forecaster. In addition to the mesoscale fields of wind, vertical motion, moisture, temperature, a stability indicator, a combination of model-predicted K and Lifted Indices and the maximum grid cell vertical motion, were proposed and tested. Results of blind tests indicate that a forecaster, provided with guidance derived from model output, could improve local thunderstorm forecasts.

  2. Natural versus anthropogenic dispersion of metals to the environment in the Wulik River area, western Brooks Range, northern Alaska

    Science.gov (United States)

    Kelley, K.D.; Hudson, T.

    2007-01-01

    Zinc-lead-silver mineral deposits in the Wulik River region, Alaska, contain an enormous accumulation of Zn. In addition to the giant deposits at Red Dog, at least nine other deposits are known. Natural weathering of these deposits has dispersed metals over a wide region over a long period of time (c. 10 000 years) through transport by stream and groundwater, stream sediments, formation of soils, and perhaps wind-blown atmospheric deposition from weathering of naturally enriched Pb-Zn surface deposits. Anthropogenic input also contributes metals to the environment. Mining of the Red Dog deposit, which began in 1989, produces fine-grained galena and sphalerite concentrates that are transported from the mine site by truck to a storage port facility. Wind-blown dispersion of concentrate dust along the road and around the port facility has been a source of local metal-rich surficial materials. Geochemical and mineralogical characteristics provide a means of distinguishing the natural versus anthropogenic metal sources. Soils over deposits have patterns of increasing metal contents with depth and proximity to the metal-bearing source, whereas ore concentrate dust is localized at the surface. The acidity produced by weathering of the sulphide deposits creates an environment in which elements such as Se and Mo are stable whereas Ca is not. Consequently, high Mo (up to 29 ppm) and Se (up to 17 ppm) and low Ca (<0.4%) concentrations characterize surficial materials near natural deposits. Acidic conditions also yield high Pb-Zn ratios (up to 70) because sphalerite is preferentially dissolved and Zn is mobilized during chemical weathering. In natural materials, secondary jarosite and anglesite are developed, and minor galena is etched and rounded due to a history of chemical and mechanical weathering. In contrast, dust-bearing samples have Pb/Zn ratios that are 0.4 or less, Ca contents are higher (0.2 to 3.6%), and Mo (<10 ppm) and Se (not detected) concentrations are low

  3. Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

    Science.gov (United States)

    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be

  4. A probabilistic dispersion model applied to the long-range transport of radionuclides from the Chernobyl accident

    DEFF Research Database (Denmark)

    Lauritzen, B.; Mikkelsen, T.

    1999-01-01

    Long-range atmospheric transport of radionuclides from the Chernobyl accident is modelled as an Eulerian diffusion process. From observations of the gross deposition pattern of particulate radiocaesium an effective long-range Eddy diffusivity K of the order of 10(6) m(2) s(-1) is inferred....... A corresponding effective deposition length for caesium, R-Cs, defined las the effective distance from Chernobyl to where the aerosols have been deposited, is found to be R-Cs approximate to 1000 km. From the observations of the regional variability of the Chernobyl fallout a simple probabilistic assessment...

  5. Dispersion of the intrinsic neuronal periods affects the relationship of the entrainment range to the coupling strength in the suprachiasmatic nucleus

    Science.gov (United States)

    Gu, Changgui; Yang, Huijie; Wang, Man

    2017-11-01

    Living beings on the Earth are subjected to and entrained (synchronized) to the natural 24-h light-dark cycle. Interestingly, they can also be entrained to an external artificial cycle of non-24-h periods. The range of these periods is called the entrainment range and it differs among species. In mammals, the entrainment range is regulated by a main clock located in the suprachiasmatic nucleus (SCN) which is composed of 10 000 neurons in the brain. Previous works have found that the entrainment range depends on the cellular coupling strength in the SCN. In particular, the entrainment range decreases with the increase of the cellular coupling strength, provided that all the neuronal oscillators are identical. However, the SCN neurons differ in the intrinsic periods that follow a normal distribution in a range from 22 to 28 h. In the present study, taking the dispersion of the intrinsic neuronal periods into account, we examined the relationship between the entrainment range and the coupling strength. Results from numerical simulations and theoretical analyses both show that the relationship is altered to be paraboliclike if the intrinsic neuronal periods are nonidentical, and the maximal entrainment range is obtained with a suitable coupling strength. Our results shed light on the role of the cellular coupling in the entrainment ability of the SCN network.

  6. Mean field for the p + 90Zr system in the energy range -60 MeV 90Zr from a dispersive optical-model analysis

    International Nuclear Information System (INIS)

    Romanovsky, E.A.; Bespalova, O.V.; Goncharov, S.A.; Pleshkov, D.V.; Spasskaya, T.I.

    2000-01-01

    Data on the scattering of protons with energies 5 MeV 90 Zr nuclei and data on the energies of proton particle and hole levels in the A + 1 and A - 1 systems with A = 90 are analyzed within the dispersive optical model. The parameters of the mean proton field for 90 Zr are determined in the energy range -60 MeV 3 He), ( 3 He, d), (n, d), and (d, n) reactions for levels near the Fermi surface and in (e, e'p) and (p, 2p) reactions for deep levels

  7. How do low dispersal species establish large range sizes? The case of the water beetle Graphoderus bilineatus

    DEFF Research Database (Denmark)

    Iversen, Lars Lønsmann; Rannap, Riinu; Thomsen, Philip Francis

    2013-01-01

    important than species phylogeny or local spatial attributes. In this study we used the water beetle Graphoderus bilineatus a philopatric species of conservation concern in Europe as a model to explain large range size and to support effective conservation measures for such species that also have limited...... systems and wetlands which used to be highly connected throughout the central plains of Europe. Our data suggest that a broad habitat niche can prevent landscape elements from becoming barriers for species like G. bilineatus. Therefore, we question the usefulness of site protection as conservation...... measures for G. bilineatus and similar philopatric species. Instead, conservation actions should be focused at the landscape level to ensure a long-term viability of such species across their range....

  8. Forecasting Skill

    Science.gov (United States)

    1981-01-01

    for the third and fourth day precipitation forecasts. A marked improvement was shown for the consensus 24 hour precipitation forecast, and small... Zuckerberg (1980) found a small long term skill increase in forecasts of heavy snow events for nine eastern cities. Other National Weather Service...and maximum temperature) are each awarded marks 2, 1, or 0 according to whether the forecast is correct, 8 - *- -**■*- ———"—- - -■ t0m 1 MM—IB I

  9. Recent developments in the applications of the Regional Atmospheric Modeling System (RAMS) for emergency response planning and operational forecasting at the Kennedy Space Center

    International Nuclear Information System (INIS)

    Lyons, W.A.; Tremback, C.J.

    1996-01-01

    The authors will summarize ten years of developing and applying the Regional Atmospheric Modeling System (RAMS) to emergency response and operational dispersion forecasting at the Kennedy Space Center (KSC). RAMS forms the core of two workstation-based operational systems, ERDAS (the Emergency Response Dose Assessment System) and PROWESS (Parallelized RAMS Operational Weather Simulation System) which are undergoing extensive operational testing prior to potential deployment as part of the range forecasting system at KSC. RAMS has been interfaced with HYPACT (the Hybrid Particle and Concentration Transport Model) to produce detailed 3-D dispersion forecasts from a variety of sources including cold spills, routine launch operations, and explosive conflagrations of launch vehicles

  10. Closure Report for Corrective Action Unit 415: Project 57 No. 1 Plutonium Dispersion (NTTR) Nevada Test and Training Range, Nevada, Revision 0 with ROTC-1

    Energy Technology Data Exchange (ETDEWEB)

    Sloop, Christina

    2017-12-01

    This Closure Report (CR) presents information supporting the closure of Corrective Action Unit (CAU) 415: Project 57 No. 1 Plutonium Dispersion, which is located on Range 4808A of the Nevada Test and Training Range (NTTR). This CR complies with the requirements of the Federal Facility Agreement and Consent Order (FFACO) that was agreed to by the State of Nevada; U.S. Department of Energy (DOE), Environmental Management; U.S. Department of Defense; and DOE, Legacy Management. CAU 415 comprises one corrective action site (CAS): NAFR-23-02, Pu Contaminated Soil. The purpose of this CR is to provide justification and documentation supporting the recommendation that no further corrective action is needed for CAU 415 based on the implementation of the corrective action of Closure in Place.

  11. Should we use seasonnal meteorological ensemble forecasts for hydrological forecasting? A case study for nordic watersheds in Canada.

    Science.gov (United States)

    Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert; Guay, Catherine

    2017-04-01

    Hydro-electricity is a major source of energy for many countries throughout the world, including Canada. Long lead-time streamflow forecasts are all the more valuable as they help decision making and dam management. Different techniques exist for long-term hydrological forecasting. Perhaps the most well-known is 'Extended Streamflow Prediction' (ESP), which considers past meteorological scenarios as possible, often equiprobable, future scenarios. In the ESP framework, those past-observed meteorological scenarios (climatology) are used in turn as the inputs of a chosen hydrological model to produce ensemble forecasts (one member corresponding to each year in the available database). Many hydropower companies, including Hydro-Québec (province of Quebec, Canada) use variants of the above described ESP system operationally for long-term operation planning. The ESP system accounts for the hydrological initial conditions and for the natural variability of the meteorological variables. However, it cannot consider the current initial state of the atmosphere. Climate models can help remedy this drawback. In the context of a changing climate, dynamical forecasts issued from climate models seem to be an interesting avenue to improve upon the ESP method and could help hydropower companies to adapt their management practices to an evolving climate. Long-range forecasts from climate models can also be helpful for water management at locations where records of past meteorological conditions are short or nonexistent. In this study, we compare 7-month hydrological forecasts obtained from climate model outputs to an ESP system. The ESP system mimics the one used operationally at Hydro-Québec. The dynamical climate forecasts are produced by the European Center for Medium range Weather Forecasts (ECMWF) System4. Forecasts quality is assessed using numerical scores such as the Continuous Ranked Probability Score (CRPS) and the Ignorance score and also graphical tools such as the

  12. Corrective Action Investigation Plan for Corrective Action Unit 414: Clean Slate III Plutonium Dispersion (TTR) Tonopah Test Range, Nevada, Revision 1

    International Nuclear Information System (INIS)

    Matthews, Patrick

    2016-01-01

    Corrective Action Unit (CAU) 414 is located on the Tonopah Test Range, which is approximately 130 miles northwest of Las Vegas, Nevada, and approximately 40 miles southeast of Tonopah, Nevada. The CAU 414 site consists of the release of radionuclides to the surface and shallow subsurface from the conduct of the Clean Slate III (CSIII) storage transportation test conducted on June 9, 1963. CAU 414 includes one corrective action site (CAS), TA-23-03CS (Pu Contaminated Soil). The known releases at CAU 414 are the result of the atmospheric dispersal of contamination from the 1963 CSIII test. The CSIII test was a nonnuclear detonation of a nuclear device located inside a reinforced concrete bunker covered with 8 feet of soil. This test dispersed radionuclides, primarily uranium and plutonium, on the ground surface. The presence and nature of contamination at CAU 414 will be evaluated based on information collected from a corrective action investigation (CAI). The investigation is based on the data quality objectives (DQOs) developed on June 7, 2016, by representatives of the Nevada Division of Environmental Protection; the U.S. Air Force; and the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office. The DQO process was used to identify and define the type, amount, and quality of data needed to develop and evaluate appropriate corrective action alternatives for CAU 414.

  13. Corrective Action Investigation Plan for Corrective Action Unit 414: Clean Slate III Plutonium Dispersion (TTR) Tonopah Test Range, Nevada, Revision 1

    Energy Technology Data Exchange (ETDEWEB)

    Matthews, Patrick [Navarro, Las Vegas, NV (United States)

    2016-09-01

    Corrective Action Unit (CAU) 414 is located on the Tonopah Test Range, which is approximately 130 miles northwest of Las Vegas, Nevada, and approximately 40 miles southeast of Tonopah, Nevada. The CAU 414 site consists of the release of radionuclides to the surface and shallow subsurface from the conduct of the Clean Slate III (CSIII) storage–transportation test conducted on June 9, 1963. CAU 414 includes one corrective action site (CAS), TA-23-03CS (Pu Contaminated Soil). The known releases at CAU 414 are the result of the atmospheric dispersal of contamination from the 1963 CSIII test. The CSIII test was a nonnuclear detonation of a nuclear device located inside a reinforced concrete bunker covered with 8 feet of soil. This test dispersed radionuclides, primarily uranium and plutonium, on the ground surface. The presence and nature of contamination at CAU 414 will be evaluated based on information collected from a corrective action investigation (CAI). The investigation is based on the data quality objectives (DQOs) developed on June 7, 2016, by representatives of the Nevada Division of Environmental Protection; the U.S. Air Force; and the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office. The DQO process was used to identify and define the type, amount, and quality of data needed to develop and evaluate appropriate corrective action alternatives for CAU 414.

  14. Load forecasting

    International Nuclear Information System (INIS)

    Mak, H.

    1995-01-01

    Slides used in a presentation at The Power of Change Conference in Vancouver, BC in April 1995 about the changing needs for load forecasting were presented. Technological innovations and population increase were said to be the prime driving forces behind the changing needs in load forecasting. Structural changes, market place changes, electricity supply planning changes, and changes in planning objectives were other factors discussed. It was concluded that load forecasting was a form of information gathering, that provided important market intelligence

  15. Dispersion Forces

    CERN Document Server

    Buhmann, Stefan Yoshi

    2012-01-01

    In this book, a modern unified theory of dispersion forces on atoms and bodies is presented which covers a broad range of advanced aspects and scenarios. Macroscopic quantum electrodynamics is shown to provide a powerful framework for dispersion forces which allows for discussing general properties like their non-additivity and the relation between microscopic and macroscopic interactions. It is demonstrated how the general results can be used to obtain dispersion forces on atoms in the presence of bodies of various shapes and materials. Starting with a brief recapitulation of volume I, this volume II deals especially with bodies of irregular shapes, universal scaling laws, dynamical forces on excited atoms, enhanced forces in cavity quantum electrodynamics, non-equilibrium forces in thermal environments and quantum friction. The book gives both the specialist and those new to the field a thorough overview over recent results in the field. It provides a toolbox for studying dispersion forces in various contex...

  16. Climate Envelope Modeling and Dispersal Simulations Show Little Risk of Range Extension of the Shipworm, Teredo navalis (L.), in the Baltic Sea

    Science.gov (United States)

    Appelqvist, Christin; Al-Hamdani, Zyad K.; Jonsson, Per R.; Havenhand, Jon N.

    2015-01-01

    The shipworm, Teredo navalis, is absent from most of the Baltic Sea. In the last 20 years, increased frequency of T. navalis has been reported along the southern Baltic Sea coasts of Denmark, Germany, and Sweden, indicating possible range-extensions into previously unoccupied areas. We evaluated the effects of historical and projected near-future changes in salinity, temperature, and oxygen on the risk of spread of T. navalis in the Baltic. Specifically, we developed a simple, GIS-based, mechanistic climate envelope model to predict the spatial distribution of favourable conditions for adult reproduction and larval metamorphosis of T. navalis, based on published environmental tolerances to these factors. In addition, we used a high-resolution three-dimensional hydrographic model to simulate the probability of spread of T. navalis larvae within the study area. Climate envelope modeling showed that projected near-future climate change is not likely to change the overall distribution of T. navalis in the region, but will prolong the breeding season and increase the risk of shipworm establishment at the margins of the current range. Dispersal simulations indicated that the majority of larvae were philopatric, but those that spread over a wider area typically spread to areas unfavourable for their survival. Overall, therefore, we found no substantive evidence for climate-change related shifts in the distribution of T. navalis in the Baltic Sea, and no evidence for increased risk of spread in the near-future. PMID:25768305

  17. Climate envelope modeling and dispersal simulations show little risk of range extension of the Shipworm, Teredo navalis (L., in the Baltic sea.

    Directory of Open Access Journals (Sweden)

    Christin Appelqvist

    Full Text Available The shipworm, Teredo navalis, is absent from most of the Baltic Sea. In the last 20 years, increased frequency of T. navalis has been reported along the southern Baltic Sea coasts of Denmark, Germany, and Sweden, indicating possible range-extensions into previously unoccupied areas. We evaluated the effects of historical and projected near-future changes in salinity, temperature, and oxygen on the risk of spread of T. navalis in the Baltic. Specifically, we developed a simple, GIS-based, mechanistic climate envelope model to predict the spatial distribution of favourable conditions for adult reproduction and larval metamorphosis of T. navalis, based on published environmental tolerances to these factors. In addition, we used a high-resolution three-dimensional hydrographic model to simulate the probability of spread of T. navalis larvae within the study area. Climate envelope modeling showed that projected near-future climate change is not likely to change the overall distribution of T. navalis in the region, but will prolong the breeding season and increase the risk of shipworm establishment at the margins of the current range. Dispersal simulations indicated that the majority of larvae were philopatric, but those that spread over a wider area typically spread to areas unfavourable for their survival. Overall, therefore, we found no substantive evidence for climate-change related shifts in the distribution of T. navalis in the Baltic Sea, and no evidence for increased risk of spread in the near-future.

  18. A robust method to forecast volcanic ash clouds

    Science.gov (United States)

    Denlinger, Roger P.; Pavolonis, Mike; Sieglaff, Justin

    2012-01-01

    Ash clouds emanating from volcanic eruption columns often form trails of ash extending thousands of kilometers through the Earth's atmosphere, disrupting air traffic and posing a significant hazard to air travel. To mitigate such hazards, the community charged with reducing flight risk must accurately assess risk of ash ingestion for any flight path and provide robust forecasts of volcanic ash dispersal. In response to this need, a number of different transport models have been developed for this purpose and applied to recent eruptions, providing a means to assess uncertainty in forecasts. Here we provide a framework for optimal forecasts and their uncertainties given any model and any observational data. This involves random sampling of the probability distributions of input (source) parameters to a transport model and iteratively running the model with different inputs, each time assessing the predictions that the model makes about ash dispersal by direct comparison with satellite data. The results of these comparisons are embodied in a likelihood function whose maximum corresponds to the minimum misfit between model output and observations. Bayes theorem is then used to determine a normalized posterior probability distribution and from that a forecast of future uncertainty in ash dispersal. The nature of ash clouds in heterogeneous wind fields creates a strong maximum likelihood estimate in which most of the probability is localized to narrow ranges of model source parameters. This property is used here to accelerate probability assessment, producing a method to rapidly generate a prediction of future ash concentrations and their distribution based upon assimilation of satellite data as well as model and data uncertainties. Applying this method to the recent eruption of Eyjafjallajökull in Iceland, we show that the 3 and 6 h forecasts of ash cloud location probability encompassed the location of observed satellite-determined ash cloud loads, providing an

  19. Submesoscale dispersion in the vicinity of the Deepwater Horizon spill

    OpenAIRE

    Poje, Andrew C.; Özgökmen, Tamay M.; Lipphardt, Bruce L.; Haus, Brian K.; Ryan, Edward H.; Haza, Angelique C.; Jacobs, Gregg A.; Reniers, A. J. H. M.; Olascoaga, Maria Josefina; Novelli, Guillaume; Griffa, Annalisa; Beron-Vera, Francisco J.; Chen, Shuyi S.; Coelho, Emanuel; Hogan, Patrick J.

    2014-01-01

    Reliable forecasts for the dispersion of oceanic contamination are important for coastal ecosystems, society and the economy as evidenced by the Deepwater Horizon oil spill in the Gulf of Mexico in 2010 and the Fukushima nuclear plant incident in the Pacific Ocean in 2011. Accurate prediction of pollutant pathways and concentrations at the ocean surface requires understanding ocean dynamics over a broad range of spatial scales. Fundamental questions concerning the structure of the velocity fi...

  20. Dispersed hydroxyapatite and modified bioglass 45S5 composites: sintering behavior of glass matrix ranging from 20 to 30 wt% in calcium oxide investigation

    Energy Technology Data Exchange (ETDEWEB)

    Silva, A.C.; Parra-Silva, J.; Santos, S.C.; Mello-Castanho, S.R.H, E-mail: dasilva.ac@uol.com.br [Instituto de Pesquisas Enegeticas e Nucleares (IPEN/CNEN-SP), DP (Brazil); Braga, F.J.C. [Consulmat Materiais de Referencia, Solucoes e Servicos, Sao Carlos, SP (Brazil); Setz, L.F.G. [Universidade Federal do ABC (UFABC), Santo Andre, SP (Brazil)

    2014-07-01

    Biomaterial technology plays an important role in cell-based tissue proliferation environment creation. The hydroxyapatite (HA) bioceramics are reference materials to employment as a bone substitute, however, their slow rate of degradation and its low rate of bioactivity (Ib) are presented as limiting factors for application as bone graft. In contrast, the bioglass (BG) is a resorbable and osteoinductive material and can act as fluxing in HA/BG composites. The present work objective the development of HA/BG (40/70wt%) composites, Three compositions of the 45S5 bioglass derived ranging from 20-30wt% in CaO were used in order to study the sintering behavior of these materials with hydroxyapatite 30wt% dispersed. The composites were uniaxially pressed in the form of cylinders and sinterized at (1100°C/1h). The characterization was made employing scanning electron microscopy, Infra-Red Spectrometry, X-ray diffraction and hydrolytic resistance test. The results indicate the potential use of the materials developed for applications like bone graft.(author)

  1. Dispersed hydroxyapatite and modified bioglass 45S5 composites: sintering behavior of glass matrix ranging from 20 to 30 wt% in calcium oxide investigation

    International Nuclear Information System (INIS)

    Silva, A.C.; Parra-Silva, J.; Santos, S.C.; Mello-Castanho, S.R.H; Braga, F.J.C.; Setz, L.F.G.

    2014-01-01

    Biomaterial technology plays an important role in cell-based tissue proliferation environment creation. The hydroxyapatite (HA) bioceramics are reference materials to employment as a bone substitute, however, their slow rate of degradation and its low rate of bioactivity (Ib) are presented as limiting factors for application as bone graft. In contrast, the bioglass (BG) is a resorbable and osteoinductive material and can act as fluxing in HA/BG composites. The present work objective the development of HA/BG (40/70wt%) composites, Three compositions of the 45S5 bioglass derived ranging from 20-30wt% in CaO were used in order to study the sintering behavior of these materials with hydroxyapatite 30wt% dispersed. The composites were uniaxially pressed in the form of cylinders and sinterized at (1100°C/1h). The characterization was made employing scanning electron microscopy, Infra-Red Spectrometry, X-ray diffraction and hydrolytic resistance test. The results indicate the potential use of the materials developed for applications like bone graft.(author)

  2. Effect of dispersive long-range corrections to the pressure tensor: The vapour-liquid interfacial properties of the Lennard-Jones system revisited

    Energy Technology Data Exchange (ETDEWEB)

    Martínez-Ruiz, F. J.; Blas, F. J., E-mail: felipe@uhu.es [Departamento de Física Aplicada, Universidad de Huelva, 21071 Huelva (Spain); Centro de Investigación de Física Teórica y Matemática, Universidad de Huelva, 21071 Huelva (Spain); Mendiboure, B. [Laboratoire des Fluides Complexes et leurs Réservoirs, UMR5150, Université de Pau et des Pays de l’Adour, B. P. 1155, Pau Cedex 64014 (France); Moreno-Ventas Bravo, A. I. [Centro de Investigación de Física Teórica y Matemática, Universidad de Huelva, 21071 Huelva (Spain); Departamento de Geología, Facultad de Ciencias Experimentales, Universidad de Huelva, 21071 Huelva (Spain)

    2014-11-14

    We propose an extension of the improved version of the inhomogeneous long-range corrections of Janeček [J. Phys. Chem. B 110, 6264–6269 (2006)], presented recently by MacDowell and Blas [J. Chem. Phys. 131, 074705 (2009)] to account for the intermolecular potential energy of spherical, rigid, and flexible molecular systems, to deal with the contributions to the microscopic components of the pressure tensor due to the dispersive long-range corrections. We have performed Monte Carlo simulations in the canonical ensemble to obtain the interfacial properties of spherical Lennard-Jones molecules with different cutoff distances, r{sub c} = 2.5, 3, 4, and 5σ. In addition, we have also considered cutoff distances r{sub c} = 2.5 and 3σ in combination with the inhomogeneous long-range corrections proposed in this work. The normal and tangential microscopic components of the pressure tensor are obtained using the mechanical or virial route in combination with the recipe of Irving and Kirkwood, while the macroscopic components are calculated using the Volume Perturbation thermodynamic route proposed by de Miguel and Jackson [J. Chem. Phys. 125, 164109 (2006)]. The vapour-liquid interfacial tension is evaluated using three different procedures, the Irving-Kirkwood method, the difference between the macroscopic components of the pressure tensor, and the Test-Area methodology. In addition to the pressure tensor and the surface tension, we also obtain density profiles, coexistence densities, vapour pressure, critical temperature and density, and interfacial thickness as functions of temperature, paying particular attention to the effect of the cutoff distance and the long-range corrections on these properties. According to our results, the main effect of increasing the cutoff distance (at fixed temperature) is to sharpen the vapour-liquid interface, to decrease the vapour pressure, and to increase the width of the biphasic coexistence region. As a result, the interfacial

  3. Effect of dispersive long-range corrections to the pressure tensor: The vapour-liquid interfacial properties of the Lennard-Jones system revisited

    International Nuclear Information System (INIS)

    Martínez-Ruiz, F. J.; Blas, F. J.; Mendiboure, B.; Moreno-Ventas Bravo, A. I.

    2014-01-01

    We propose an extension of the improved version of the inhomogeneous long-range corrections of Janeček [J. Phys. Chem. B 110, 6264–6269 (2006)], presented recently by MacDowell and Blas [J. Chem. Phys. 131, 074705 (2009)] to account for the intermolecular potential energy of spherical, rigid, and flexible molecular systems, to deal with the contributions to the microscopic components of the pressure tensor due to the dispersive long-range corrections. We have performed Monte Carlo simulations in the canonical ensemble to obtain the interfacial properties of spherical Lennard-Jones molecules with different cutoff distances, r c = 2.5, 3, 4, and 5σ. In addition, we have also considered cutoff distances r c = 2.5 and 3σ in combination with the inhomogeneous long-range corrections proposed in this work. The normal and tangential microscopic components of the pressure tensor are obtained using the mechanical or virial route in combination with the recipe of Irving and Kirkwood, while the macroscopic components are calculated using the Volume Perturbation thermodynamic route proposed by de Miguel and Jackson [J. Chem. Phys. 125, 164109 (2006)]. The vapour-liquid interfacial tension is evaluated using three different procedures, the Irving-Kirkwood method, the difference between the macroscopic components of the pressure tensor, and the Test-Area methodology. In addition to the pressure tensor and the surface tension, we also obtain density profiles, coexistence densities, vapour pressure, critical temperature and density, and interfacial thickness as functions of temperature, paying particular attention to the effect of the cutoff distance and the long-range corrections on these properties. According to our results, the main effect of increasing the cutoff distance (at fixed temperature) is to sharpen the vapour-liquid interface, to decrease the vapour pressure, and to increase the width of the biphasic coexistence region. As a result, the interfacial thickness

  4. Exposure Forecaster

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Exposure Forecaster Database (ExpoCastDB) is EPA's database for aggregating chemical exposure information and can be used to help with chemical exposure...

  5. Meteorological uncertainty of atmospheric dispersion model results (MUD)

    Energy Technology Data Exchange (ETDEWEB)

    Havskov Soerensen, J.; Amstrup, B.; Feddersen, H. [Danish Meteorological Institute, Copenhagen (Denmark)] [and others

    2013-08-15

    The MUD project addresses assessment of uncertainties of atmospheric dispersion model predictions, as well as possibilities for optimum presentation to decision makers. Previously, it has not been possible to estimate such uncertainties quantitatively, but merely to calculate the 'most likely' dispersion scenario. However, recent developments in numerical weather prediction (NWP) include probabilistic forecasting techniques, which can be utilised also for long-range atmospheric dispersion models. The ensemble statistical methods developed and applied to NWP models aim at describing the inherent uncertainties of the meteorological model results. These uncertainties stem from e.g. limits in meteorological observations used to initialise meteorological forecast series. By perturbing e.g. the initial state of an NWP model run in agreement with the available observational data, an ensemble of meteorological forecasts is produced from which uncertainties in the various meteorological parameters are estimated, e.g. probabilities for rain. Corresponding ensembles of atmospheric dispersion can now be computed from which uncertainties of predicted radionuclide concentration and deposition patterns can be derived. (Author)

  6. Meteorological uncertainty of atmospheric dispersion model results (MUD)

    International Nuclear Information System (INIS)

    Havskov Soerensen, J.; Amstrup, B.; Feddersen, H.

    2013-08-01

    The MUD project addresses assessment of uncertainties of atmospheric dispersion model predictions, as well as possibilities for optimum presentation to decision makers. Previously, it has not been possible to estimate such uncertainties quantitatively, but merely to calculate the 'most likely' dispersion scenario. However, recent developments in numerical weather prediction (NWP) include probabilistic forecasting techniques, which can be utilised also for long-range atmospheric dispersion models. The ensemble statistical methods developed and applied to NWP models aim at describing the inherent uncertainties of the meteorological model results. These uncertainties stem from e.g. limits in meteorological observations used to initialise meteorological forecast series. By perturbing e.g. the initial state of an NWP model run in agreement with the available observational data, an ensemble of meteorological forecasts is produced from which uncertainties in the various meteorological parameters are estimated, e.g. probabilities for rain. Corresponding ensembles of atmospheric dispersion can now be computed from which uncertainties of predicted radionuclide concentration and deposition patterns can be derived. (Author)

  7. Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

    Science.gov (United States)

    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    In Bavaria, operational flood forecasting has been established since the disastrous flood of 1999. Nowadays, forecasts based on rainfall information from about 700 raingauges and 600 rivergauges are calculated and issued for nearly 100 rivergauges. With the added experience of the 2002 and 2005 floods, awareness grew that the standard deterministic forecast, neglecting the uncertainty associated with each forecast is misleading, creating a false feeling of unambiguousness. As a consequence, a system to identify, quantify and communicate the sources and magnitude of forecast uncertainty has been developed, which will be presented in part I of this study. In this system, the use of ensemble meteorological forecasts plays a key role which will be presented in part II. Developing the system, several constraints stemming from the range of hydrological regimes and operational requirements had to be met: Firstly, operational time constraints obviate the variation of all components of the modeling chain as would be done in a full Monte Carlo simulation. Therefore, an approach was chosen where only the most relevant sources of uncertainty were dynamically considered while the others were jointly accounted for by static error distributions from offline analysis. Secondly, the dominant sources of uncertainty vary over the wide range of forecasted catchments: In alpine headwater catchments, typically of a few hundred square kilometers in size, rainfall forecast uncertainty is the key factor for forecast uncertainty, with a magnitude dynamically changing with the prevailing predictability of the atmosphere. In lowland catchments encompassing several thousands of square kilometers, forecast uncertainty in the desired range (usually up to two days) is mainly dependent on upstream gauge observation quality, routing and unpredictable human impact such as reservoir operation. The determination of forecast uncertainty comprised the following steps: a) From comparison of gauge

  8. Streamlined Approach for Environmental Restoration (SAFER) Plan for Corrective Action Unit 411. Double Tracks Plutonium Dispersion (Nellis), Nevada Test and Training Range, Nevada, Revision 0

    Energy Technology Data Exchange (ETDEWEB)

    Matthews, Patrick K. [Navarro-Intera, LLC (N-I), Las Vegas, NV (United States)

    2015-03-01

    This Streamlined Approach for Environmental Restoration (SAFER) Plan addresses the actions needed to achieve closure for Corrective Action Unit (CAU) 411, Double Tracks Plutonium Dispersion (Nellis). CAU 411 is located on the Nevada Test and Training Range and consists of a single corrective action site (CAS), NAFR-23-01, Pu Contaminated Soil. There is sufficient information and historical documentation from previous investigations and the 1996 interim corrective action to recommend closure of CAU 411 using the SAFER process. Based on existing data, the presumed corrective action for CAU 411 is clean closure. However, additional data will be obtained during a field investigation to document and verify the adequacy of existing information, and to determine whether the CAU 411 closure objectives have been achieved. This SAFER Plan provides the methodology to gather the necessary information for closing the CAU. The results of the field investigation will be presented in a closure report that will be prepared and submitted to the Nevada Division of Environmental Protection (NDEP) for review and approval. The site will be investigated based on the data quality objectives (DQOs) developed on November 20, 2014, by representatives of NDEP, the U.S. Air Force (USAF), and the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office. The DQO process was used to identify and define the type, amount, and quality of data needed to determine whether CAU 411 closure objectives have been achieved. The following text summarizes the SAFER activities that will support the closure of CAU 411; Collect environmental samples from designated target populations to confirm or disprove the presence of contaminants of concern (COCs) as necessary to supplement existing information; If COCs are no longer present, establish clean closure as the corrective action; If COCs are present, the extent of contamination will be defined and further corrective actions

  9. Corrective Action Investigation Plan for Corrective Action Unit 413: Clean Slate II Plutonium Dispersion (TTR) Tonopah Test Range, Nevada, Revision 1

    Energy Technology Data Exchange (ETDEWEB)

    Matthews, Patrick; Burmeister, Mark; Gallo, Patricia

    2016-04-21

    Corrective Action Unit (CAU) 413 is located on the Tonopah Test Range, which is approximately 130 miles northwest of Las Vegas, Nevada, and approximately 40 miles southeast of Tonopah, Nevada. The CAU 413 site consists of the release of radionuclides to the surface and shallow subsurface from the conduct of the Clean Slate II (CSII) storage–transportation test conducted on May 31, 1963. CAU 413 includes one corrective action site (CAS), TA-23-02CS (Pu Contaminated Soil). The known releases at CAU 413 are the result of the atmospheric deposition of contamination from the 1963 CSII test. The CSII test was a non-nuclear detonation of a nuclear device located inside a reinforced concrete bunker covered with 2 feet of soil. This test dispersed radionuclides, primarily plutonium, on the ground surface. The presence and nature of contamination at CAU 413 will be evaluated based on information collected from a corrective action investigation (CAI). The investigation is based on the data quality objectives (DQOs) developed on June 17, 2015, by representatives of the Nevada Division of Environmental Protection; the U.S. Air Force; and the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office. The DQO process was used to identify and define the type, amount, and quality of data needed to develop and evaluate appropriate corrective actions for CAU 413. The CAI will include radiological surveys, geophysical surveys, collection and analyses of soil samples, and assessment of investigation results. The collection of soil samples will be accomplished using both probabilistic and judgmental sampling approaches. To facilitate site investigation and the evaluation of DQO decisions, the releases at CAU 413 have been divided into seven study groups.

  10. Forecasting metal prices: Do forecasters herd?

    DEFF Research Database (Denmark)

    Pierdzioch, C.; Rulke, J. C.; Stadtmann, G.

    2013-01-01

    We analyze more than 20,000 forecasts of nine metal prices at four different forecast horizons. We document that forecasts are heterogeneous and report that anti-herding appears to be a source of this heterogeneity. Forecaster anti-herding reflects strategic interactions among forecasters...

  11. Forecast of auroral activity

    International Nuclear Information System (INIS)

    Lui, A.T.Y.

    2004-01-01

    A new technique is developed to predict auroral activity based on a sample of over 9000 auroral sites identified in global auroral images obtained by an ultraviolet imager on the NASA Polar satellite during a 6-month period. Four attributes of auroral activity sites are utilized in forecasting, namely, the area, the power, and the rates of change in area and power. This new technique is quite accurate, as indicated by the high true skill scores for forecasting three different levels of auroral dissipation during the activity lifetime. The corresponding advanced warning time ranges from 22 to 79 min from low to high dissipation levels

  12. Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate

    Science.gov (United States)

    Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert

    2017-11-01

    Hydropower production requires optimal dam and reservoir management to prevent flooding damage and avoid operation losses. In a northern climate, where spring freshet constitutes the main inflow volume, seasonal forecasts can help to establish a yearly strategy. Long-term hydrological forecasts often rely on past observations of streamflow or meteorological data. Another alternative is to use ensemble meteorological forecasts produced by climate models. In this paper, those produced by the ECMWF (European Centre for Medium-Range Forecast) System 4 are examined and bias is characterized. Bias correction, through the linear scaling method, improves the performance of the raw ensemble meteorological forecasts in terms of continuous ranked probability score (CRPS). Then, three seasonal ensemble hydrological forecasting systems are compared: (1) the climatology of simulated streamflow, (2) the ensemble hydrological forecasts based on climatology (ESP) and (3) the hydrological forecasts based on bias-corrected ensemble meteorological forecasts from System 4 (corr-DSP). Simulated streamflow computed using observed meteorological data is used as benchmark. Accounting for initial conditions is valuable even for long-term forecasts. ESP and corr-DSP both outperform the climatology of simulated streamflow for lead times from 1 to 5 months depending on the season and watershed. Integrating information about future meteorological conditions also improves monthly volume forecasts. For the 1-month lead time, a gain exists for almost all watersheds during winter, summer and fall. However, volume forecasts performance for spring varies from one watershed to another. For most of them, the performance is close to the performance of ESP. For longer lead times, the CRPS skill score is mostly in favour of ESP, even if for many watersheds, ESP and corr-DSP have comparable skill. Corr-DSP appears quite reliable but, in some cases, under-dispersion or bias is observed. A more complex bias

  13. Hazard assessment of long-range tephra dispersal for a Plinian eruptive scenario at Popocatépetl volcano (Mexico). Inplications on civil aviation

    Science.gov (United States)

    Bonasia, R.; Scaini, C.; Capra, L.; Nathenson, M.; Siebe, C.; Arana-Salinas, L.; Folch, A.

    2013-12-01

    Popocatépetl is one of the most active volcanoes in Mexico threatening a densely populated area that includes Mexico City with more than 20 million inhabitants. The destructive potential of this volcano is demonstrated by its Late Pleistocene-Holocene eruptive activity, which has been characterized by recurrent Plinian eruptions of large magnitude. The current volcanic hazards map, reconstructed after the crisis occurred in 1994, considers the potential occurrence of different volcanic phenomena, including pyroclastic density currents and lahars. However, no quantitative assessment of the tephra dispersal hazard, especially related to atmospheric dispersal, has been performed. Given the high number of important airports in the surroundings of Popocatépetl volcano and considering the potential threat posed to civil aviation in Mexico and adjacent regions in case of a Plinian eruption, a hazard assessment for tephra dispersal is strongly required. In this work we present the first probabilistic tephra dispersal hazard assessment for Popocatépetl volcano. We compute probabilistic hazard maps for critical thresholds of airborne ash concentrations at different flight levels. Tephra dispersal modelling is performed using the FALL3D numerical model. Probabilistic hazard maps are built for a Plinian eruptive scenario defined on the basis of geological field data for the 'Ochre Pumice' Plinian eruption (4965 14C yrBP). FALL3D model input eruptive parameters are constrained through an inversion method carried out with the semi-analytical HAZMAP model and are varied sampling them on the base of a Probability Density Function. We analyze the influence of seasonal variations on ash dispersal and estimate the average persistence of critical ash concentrations at relevant locations and airports. This study assesses the impact that a Plinian eruption similar to the Ochre Pumice eruption would have on the main airports of Mexico and adjacent areas. The hazard maps presented here

  14. Corrective Action Decision Document/Corrective Action Plan for Corrective Action Unit 413: Clean Slate II Plutonium Dispersion (TTR) Tonopah Test Range, Nevada. Revision 0

    Energy Technology Data Exchange (ETDEWEB)

    Matthews, Patrick [Navarro, Las Vegas, NV (United States)

    2017-05-01

    This Corrective Action Decision Document/Corrective Action Plan provides the rationale and supporting information for the selection and implementation of corrective actions at Corrective Action Unit (CAU) 413, Clean Slate II Plutonium Dispersion (TTR). CAU 413 is located on the Tonopah Test Range and includes one corrective action site, TA-23-02CS. CAU 413 consists of the release of radionuclides to the surface and shallow subsurface from the Clean Slate II (CSII) storage–transportation test conducted on May 31, 1963. The CSII test was a non-nuclear detonation of a nuclear device located inside a concrete bunker covered with 2 feet of soil. To facilitate site investigation and the evaluation of data quality objectives decisions, the releases at CAU 413 were divided into seven study groups: 1 Undisturbed Areas 2 Disturbed Areas 3 Sedimentation Areas 4 Former Staging Area 5 Buried Debris 6 Potential Source Material 7 Soil Mounds Corrective action investigation (CAI) activities, as set forth in the CAU 413 Corrective Action Investigation Plan, were performed from June 2015 through May 2016. Radionuclides detected in samples collected during the CAI were used to estimate total effective dose using the Construction Worker exposure scenario. Corrective action was required for areas where total effective dose exceeded, or was assumed to exceed, the radiological final action level (FAL) of 25 millirem per year. The results of the CAI and the assumptions made in the data quality objectives resulted in the following conclusions: The FAL is exceeded in surface soil in SG1, Undisturbed Areas; The FAL is assumed to be exceeded in SG5, Buried Debris, where contaminated debris and soil were buried after the CSII test; The FAL is not exceeded at SG2, SG3, SG4, SG6, or SG7. Because the FAL is exceeded at CAU 413, corrective action is required and corrective action alternatives (CAAs) must be evaluated. For CAU 413, three CAAs were evaluated: no further action, clean closure, and

  15. Structural properties of small Lin (n = 5-8) atomic clusters via ab initio random structure searching: A look into the role of different implementations of long-range dispersion corrections

    Science.gov (United States)

    Putungan, Darwin Barayang; Lin, Shi-Hsin

    2018-01-01

    In this work, we looked into the lowest energy structures of small lithium clusters (Lin, n = 5, 6, 7, 8) utilizing conventional PBE exchange-correlation functional, PBE with D2 dispersion correction and PBE with Tkatchenko and Scheffler (TS) dispersion correction, and searched using ab initio random structure searching. Results show that in general, dispersion-corrected PBE obtained similar lowest minima structures as those obtained via conventional PBE regardless of the type of implementation, although both D2 and TS found several high-energy isomers that conventional PBE did not arrive at, with TS in general giving more structures per energy range that could be attributed to its environment-dependent implementation. Moreover, D2 and TS dispersion corrections found a lowest energy geometry for Li8 cluster that is in agreement with the structure obtained via the typical benchmarking method diffusion Monte Carlo in a recent work. It is thus suggested that for much larger lithium clusters, utilization of dispersion correction could be of help in searching for lowest energy minima that is in close agreement with that of diffusion Monte Carlo results, but computationally inexpensive.

  16. Operating range, hold-up, droplet size and axial mixing of pulsed plate columns in highly disperse and low-continuity volume flows

    International Nuclear Information System (INIS)

    Schmidt, H.; Miller, H.

    Operating behavior, hold-up, droplet size and axial mixing are investigated in highly disperse and slightly continuous volume flows in a pulsed plate column. The geometry of the column of 4-m length and 10-cm inside diameter was held constant. The hole shape of the column bases was changed, wherby the cylindrical, sharp-edge drilled hole is compared with the punched, nozzle-shaped hole in their effects on the fluid-dynamic behavior. In this case we varied the volume flows, the ratio of volume flows, the pulse frequency and the operating temperature. The operation was held constant for the aqueous, the organic, the continuous and the disperse phases. The objective was to demonstrate the applicability of pulsed plate columns with very large differences between the organic disperse and the aqueous continuous volume flow, to obtain design data for such columns and to perform a scale-up to industrial reprocessing plant-size. 18 references, 11 figures, 3 tables

  17. On the reliability of seasonal climate forecasts

    Science.gov (United States)

    Weisheimer, A.; Palmer, T. N.

    2014-01-01

    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. PMID:24789559

  18. Long-range hazard assessment of volcanic ash dispersal for a Plinian eruptive scenario at Popocatépetl volcano (Mexico): implications for civil aviation safety

    Science.gov (United States)

    Bonasia, Rosanna; Scaini, Chiara; Capra, Lucia; Nathenson, Manuel; Siebe, Claus; Arana-Salinas, Lilia; Folch, Arnau

    2014-01-01

    Popocatépetl is one of Mexico's most active volcanoes threatening a densely populated area that includes Mexico City with more than 20 million inhabitants. The destructive potential of this volcano is demonstrated by its Late Pleistocene-Holocene eruptive activity, which has been characterized by recurrent Plinian eruptions of large magnitude, the last two of which destroyed human settlements in pre-Hispanic times. Popocatépetl's reawakening in 1994 produced a crisis that culminated with the evacuation of two villages on the northeastern flank of the volcano. Shortly after, a monitoring system and a civil protection contingency plan based on a hazard zone map were implemented. The current volcanic hazards map considers the potential occurrence of different volcanic phenomena, including pyroclastic density currents and lahars. However, no quantitative assessment of the tephra hazard, especially related to atmospheric dispersal, has been performed. The presence of airborne volcanic ash at low and jet-cruise atmospheric levels compromises the safety of aircraft operations and forces re-routing of aircraft to prevent encounters with volcanic ash clouds. Given the high number of important airports in the surroundings of Popocatépetl volcano and considering the potential threat posed to civil aviation in Mexico and adjacent regions in case of a Plinian eruption, a hazard assessment for tephra dispersal is required. In this work, we present the first probabilistic tephra dispersal hazard assessment for Popocatépetl volcano. We compute probabilistic hazard maps for critical thresholds of airborne ash concentrations at different flight levels, corresponding to the situation defined in Europe during 2010, and still under discussion. Tephra dispersal mode is performed using the FALL3D numerical model. Probabilistic hazard maps are built for a Plinian eruptive scenario defined on the basis of geological field data for the "Ochre Pumice" Plinian eruption (4965 14C yr BP

  19. Long-range hazard assessment of volcanic ash dispersal for a Plinian eruptive scenario at Popocatépetl volcano (Mexico): implications for civil aviation safety

    Science.gov (United States)

    Bonasia, Rosanna; Scaini, Chirara; Capra, Lucia; Nathenson, Manuel; Siebe, Claus; Arana-Salinas, Lilia; Folch, Arnau

    2013-01-01

    Popocatépetl is one of Mexico’s most active volcanoes threatening a densely populated area that includes Mexico City with more than 20 million inhabitants. The destructive potential of this volcano is demonstrated by its Late Pleistocene–Holocene eruptive activity, which has been characterized by recurrent Plinian eruptions of large magnitude, the last two of which destroyed human settlements in pre-Hispanic times. Popocatépetl’s reawakening in 1994 produced a crisis that culminated with the evacuation of two villages on the northeastern flank of the volcano. Shortly after, a monitoring system and a civil protection contingency plan based on a hazard zone map were implemented. The current volcanic hazards map considers the potential occurrence of different volcanic phenomena, including pyroclastic density currents and lahars. However, no quantitative assessment of the tephra hazard, especially related to atmospheric dispersal, has been performed. The presence of airborne volcanic ash at low and jet-cruise atmospheric levels compromises the safety of aircraft operations and forces re-routing of aircraft to prevent encounters with volcanic ash clouds. Given the high number of important airports in the surroundings of Popocatépetl volcano and considering the potential threat posed to civil aviation in Mexico and adjacent regions in case of a Plinian eruption, a hazard assessment for tephra dispersal is required. In this work, we present the first probabilistic tephra dispersal hazard assessment for Popocatépetl volcano. We compute probabilistic hazard maps for critical thresholds of airborne ash concentrations at different flight levels, corresponding to the situation defined in Europe during 2010, and still under discussion. Tephra dispersal mode is performed using the FALL3D numerical model. Probabilistic hazard maps are built for a Plinian eruptive scenario defined on the basis of geological field data for the “Ochre Pumice” Plinian eruption (4965 14C

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

    Science.gov (United States)

    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.

  1. Short-term wind power combined forecasting based on error forecast correction

    International Nuclear Information System (INIS)

    Liang, Zhengtang; Liang, Jun; Wang, Chengfu; Dong, Xiaoming; Miao, Xiaofeng

    2016-01-01

    Highlights: • The correlation relationships of short-term wind power forecast errors are studied. • The correlation analysis method of the multi-step forecast errors is proposed. • A strategy selecting the input variables for the error forecast models is proposed. • Several novel combined models based on error forecast correction are proposed. • The combined models have improved the short-term wind power forecasting accuracy. - Abstract: With the increasing contribution of wind power to electric power grids, accurate forecasting of short-term wind power has become particularly valuable for wind farm operators, utility operators and customers. The aim of this study is to investigate the interdependence structure of errors in short-term wind power forecasting that is crucial for building error forecast models with regression learning algorithms to correct predictions and improve final forecasting accuracy. In this paper, several novel short-term wind power combined forecasting models based on error forecast correction are proposed in the one-step ahead, continuous and discontinuous multi-step ahead forecasting modes. First, the correlation relationships of forecast errors of the autoregressive model, the persistence method and the support vector machine model in various forecasting modes have been investigated to determine whether the error forecast models can be established by regression learning algorithms. Second, according to the results of the correlation analysis, the range of input variables is defined and an efficient strategy for selecting the input variables for the error forecast models is proposed. Finally, several combined forecasting models are proposed, in which the error forecast models are based on support vector machine/extreme learning machine, and correct the short-term wind power forecast values. The data collected from a wind farm in Hebei Province, China, are selected as a case study to demonstrate the effectiveness of the proposed

  2. Forecasting winds over nuclear power plants statistics

    International Nuclear Information System (INIS)

    Marais, Ch.

    1997-01-01

    In the event of an accident at nuclear power plant, it is essential to forecast the wind velocity at the level where the efflux occurs (about 100 m). At present meteorologists refine the wind forecast from the coarse grid of numerical weather prediction (NWP) models. The purpose of this study is to improve the forecasts by developing a statistical adaptation method which corrects the NWP forecasts by using statistical comparisons between wind forecasts and observations. The Multiple Linear Regression method is used here to forecast the 100 m wind at 12 and 24 hours range for three Electricite de France (EDF) sites. It turns out that this approach gives better forecasts than the NWP model alone and is worthy of operational use. (author)

  3. Forecasting global atmospheric CO2

    International Nuclear Information System (INIS)

    Agusti-Panareda, A.; Massart, S.; Boussetta, S.; Balsamo, G.; Beljaars, A.; Engelen, R.; Jones, L.; Peuch, V.H.; Chevallier, F.; Ciais, P.; Paris, J.D.; Sherlock, V.

    2014-01-01

    A new global atmospheric carbon dioxide (CO 2 ) real-time forecast is now available as part of the preoperational Monitoring of Atmospheric Composition and Climate - Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO 2 forecasting system is that the land surface, including vegetation CO 2 fluxes, is modelled online within the IFS. Other CO 2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO 2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO 2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO 2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO 2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO 2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO 2 fluxes also lead to accumulating errors in the CO 2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO 2 fluxes compared to total optimized fluxes and the atmospheric CO 2 compared to observations. The largest biases in the atmospheric CO 2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO 2 analyses based on the assimilation of CO 2 products retrieved from satellite

  4. A Wind Forecasting System for Energy Application

    Science.gov (United States)

    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

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  4. pahn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  5. ksrq Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  6. kpvd Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  7. kisp Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  8. kttd Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  9. pmdy Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. kont Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. kyng Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. kcwa Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. kflg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. krsw Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. kmyl Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. krbg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. kril Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. ksus Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. padq Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. kbil Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. krfd Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  2. kdug Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  3. ktix Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  4. kcod Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  5. kslk Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  6. kgfl Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  7. kguc Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  8. kmlu Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  9. kbff Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. ksmn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. kdro Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. kmce Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. ktpa Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. kmot Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. kcre Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. klws Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. kotm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. khqm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. kabr Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. klal Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. kelp Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  2. kecg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  3. khbg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  4. kpbf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  5. konp Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  6. pkwa Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  7. ktvf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  8. paga Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  9. khks Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. kdsm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. kpsm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. kgrb Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. kgmu Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. papg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. kbgm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. pamc Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. klrd Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. ksan Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. patk Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. kowb Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. klru Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  2. kfxe Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  3. kjct Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  4. kcrg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  5. paaq Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  6. kaex Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  7. klbx Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  8. kmia Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  9. kpit Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. kcrw Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. paen Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. kast Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. kuin Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. kmht Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. kcys Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. kflo Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. pakn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. pabt Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. krdg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. khdn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. kjac Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  2. kphx Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  3. Robust forecast comparison

    OpenAIRE

    Jin, Sainan; Corradi, Valentina; Swanson, Norman

    2015-01-01

    Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast errors. We introduce the concepts of general-loss (GL) forecast superiority and convex-loss (CL) forecast superiority, and we establish a ...

  4. Ensemble forecasting of species distributions.

    Science.gov (United States)

    Araújo, Miguel B; New, Mark

    2007-01-01

    Concern over implications of climate change for biodiversity has led to the use of bioclimatic models to forecast the range shifts of species under future climate-change scenarios. Recent studies have demonstrated that projections by alternative models can be so variable as to compromise their usefulness for guiding policy decisions. Here, we advocate the use of multiple models within an ensemble forecasting framework and describe alternative approaches to the analysis of bioclimatic ensembles, including bounding box, consensus and probabilistic techniques. We argue that, although improved accuracy can be delivered through the traditional tasks of trying to build better models with improved data, more robust forecasts can also be achieved if ensemble forecasts are produced and analysed appropriately.

  5. Using demography and movement behavior to predict range expansion of the southern sea otter.

    Science.gov (United States)

    Tinker, M.T.; Doak, D.F.; Estes, J.A.

    2008-01-01

    In addition to forecasting population growth, basic demographic data combined with movement data provide a means for predicting rates of range expansion. Quantitative models of range expansion have rarely been applied to large vertebrates, although such tools could be useful for restoration and management of many threatened but recovering populations. Using the southern sea otter (Enhydra lutris nereis) as a case study, we utilized integro-difference equations in combination with a stage-structured projection matrix that incorporated spatial variation in dispersal and demography to make forecasts of population recovery and range recolonization. In addition to these basic predictions, we emphasize how to make these modeling predictions useful in a management context through the inclusion of parameter uncertainty and sensitivity analysis. Our models resulted in hind-cast (1989–2003) predictions of net population growth and range expansion that closely matched observed patterns. We next made projections of future range expansion and population growth, incorporating uncertainty in all model parameters, and explored the sensitivity of model predictions to variation in spatially explicit survival and dispersal rates. The predicted rate of southward range expansion (median = 5.2 km/yr) was sensitive to both dispersal and survival rates; elasticity analysis indicated that changes in adult survival would have the greatest potential effect on the rate of range expansion, while perturbation analysis showed that variation in subadult dispersal contributed most to variance in model predictions. Variation in survival and dispersal of females at the south end of the range contributed most of the variance in predicted southward range expansion. Our approach provides guidance for the acquisition of further data and a means of forecasting the consequence of specific management actions. Similar methods could aid in the management of other recovering populations.

  6. Forecaster Behaviour and Bias in Macroeconomic Forecasts

    OpenAIRE

    Roy Batchelor

    2007-01-01

    This paper documents the presence of systematic bias in the real GDP and inflation forecasts of private sector forecasters in the G7 economies in the years 1990–2005. The data come from the monthly Consensus Economics forecasting service, and bias is measured and tested for significance using parametric fixed effect panel regressions and nonparametric tests on accuracy ranks. We examine patterns across countries and forecasters to establish whether the bias reflects the inefficient use of i...

  7. Trends in mica–mica adhesion reflect the influence of molecular details on long-range dispersion forces underlying aggregation and coalignment

    Energy Technology Data Exchange (ETDEWEB)

    Li, Dongsheng; Chun, Jaehun; Xiao, Dongdong; Zhou, Weijiang; Cai, Huacheng; Zhang, Lei; Rosso, Kevin M.; Mundy, Christopher J.; Schenter, Gregory K.; De Yoreo, James J.

    2017-07-05

    Oriented attachment of nanocrystalline subunits is recognized as a common crystallization pathway that is closely related to formation of nanoparticle superlattices, mesocrystals, and other kinetically stabilized structures. Approaching particles have been observed to rotate to achieve co-alignment while separated by nanometer-scale solvent layers. Little is known about the forces that drive co-alignment, particularly in this “solvent-separated” regime. To obtain a mechanistic understanding of this process, we used atomic force microscopy-based dynamic force spectroscopy with tips fabricated from oriented mica to measure the adhesion forces between mica (001) surfaces in electrolyte solutions as a function of orientation, temperature, electrolyte type, and electrolyte concentration. The results reveal a ~60° periodicity as well as a complex dependence on electrolyte concentration and temperature. A continuum model that considers the competition between electrostatic repulsion and van der Waals attraction, augmented by microscopic details that include surface separation, water structure, ion hydration, and charge regulation at the interface, qualitatively reproduces the observed trends and implies that dispersion forces are responsible for establishing co-alignment in the solvent-separated state.

  8. Weather forecast

    CERN Document Server

    Courtier, P

    1994-02-07

    Weather prediction is performed using the numerical model of the atmosphere evolution.The evolution equations are derived from the Navier Stokes equation for the adiabatic part but the are very much complicated by the change of phase of water, the radiation porocess and the boundary layer.The technique used operationally is described. Weather prediction is an initial value problem and accurate initial conditions need to be specified. Due to the small number of observations available (105 ) as compared to the dimension of the model state variable (107),the problem is largely underdetermined. Techniques of optimal control and inverse problems are used and have been adapted to the large dimension of our problem. our problem.The at mosphere is a chaotic system; the implication for weather prediction is discussed. Ensemble prediction is used operationally and the technique for generating initial conditions which lead to a numerical divergence of the subsequent forecasts is described.

  9. Statistical methods for forecasting

    CERN Document Server

    Abraham, Bovas

    2009-01-01

    The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists."This book, it must be said, lives up to the words on its advertising cover: ''Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.'' It does just that!"-Journal of the Royal Statistical Society"A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series ...

  10. Monitoring and forecasting Etna volcanic plumes

    Directory of Open Access Journals (Sweden)

    S. Scollo

    2009-09-01

    Full Text Available 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.

  11. National Forecast Charts

    Science.gov (United States)

    code. Press enter or select the go button to submit request Local forecast by "City, St" or Prediction Center on Twitter NCEP Quarterly Newsletter WPC Home Analyses and Forecasts National Forecast to all federal, state, and local government web resources and services. National Forecast Charts

  12. Are Forecast Updates Progressive?

    NARCIS (Netherlands)

    C-L. Chang (Chia-Lin); Ph.H.B.F. Franses (Philip Hans); M.J. McAleer (Michael)

    2010-01-01

    textabstractMacro-economic forecasts typically involve both a model component, which is replicable, as well as intuition, which is non-replicable. Intuition is expert knowledge possessed by a forecaster. If forecast updates are progressive, forecast updates should become more accurate, on average,

  13. Dispersion properties and low infrared optical losses in epitaxial AlN on sapphire substrate in the visible and infrared range

    International Nuclear Information System (INIS)

    Soltani, A.; Stolz, A.; Gerbedoen, J.-C.; Rousseau, M.; Bourzgui, N.; De Jaeger, J.-C.; Charrier, J.; Mattalah, M.; Barkad, H. A.; Mortet, V.; BenMoussa, A.

    2014-01-01

    Optical waveguiding properties of a thick wurtzite aluminum nitride highly [002]-textured hetero-epitaxial film on (001) basal plane of sapphire substrate are studied. The physical properties of the film are determined by X-ray diffraction, atomic force microscopy, microRaman, and photocurrent spectroscopy. The refractive index and the thermo-optic coefficients are determined by m-lines spectroscopy using the classical prism coupling technique. The optical losses of this planar waveguide are also measured in the spectral range of 450–1553 nm. The lower value of optical losses is equal to 0.7 dB/cm at 1553 nm. The optical losses due to the surface scattering are simulated showing that the contribution is the most significant at near infrared wavelength range, whereas the optical losses are due to volume scattering and material absorption in the visible range. The good physical properties and the low optical losses obtained from this planar waveguide are encouraging to achieve a wide bandgap optical guiding platform from these aluminum nitride thin films

  14. Dispersion properties and low infrared optical losses in epitaxial AlN on sapphire substrate in the visible and infrared range

    Energy Technology Data Exchange (ETDEWEB)

    Soltani, A., E-mail: ali.soltani@iemn.univ-lille1.fr; Stolz, A.; Gerbedoen, J.-C.; Rousseau, M.; Bourzgui, N.; De Jaeger, J.-C. [Institut d' Électronique, Microélectronique et Nanotechnologie, UMR-CNRS 8520, PRES Université Lille Nord de France, Cité Scientifique, Avenue Poincaré, CS 60069, 59652 Villeneuve d' Ascq Cedex (France); Charrier, J. [Fonctions Optiques pour les Technologies de l' informatiON, UMR-CNRS 6082, ENSSAT 6, rue de Kerampont, CS 80518, 22305 Lannion Cedex (France); Mattalah, M. [Laboratoire de Microélectronique, Université Djilali Liabes, 22000 Sidi Bel Abbes (Algeria); Barkad, H. A. [Institut Universitaire Technologique Industriel, Université de Djibouti, Avenue Georges Clémenceau, BP 1904 Djibouti (Djibouti); Mortet, V. [Institute of Physics of Academy of Sciences of Czech Republic, Fyzikální ústav AV CR, v.v.i., Na Slovance 1999/2 (Czech Republic); BenMoussa, A. [Solar Terrestrial Center of Excellence, Royal Observatory of Belgium, Circular 3, B-1180 Brussels (Belgium)

    2014-04-28

    Optical waveguiding properties of a thick wurtzite aluminum nitride highly [002]-textured hetero-epitaxial film on (001) basal plane of sapphire substrate are studied. The physical properties of the film are determined by X-ray diffraction, atomic force microscopy, microRaman, and photocurrent spectroscopy. The refractive index and the thermo-optic coefficients are determined by m-lines spectroscopy using the classical prism coupling technique. The optical losses of this planar waveguide are also measured in the spectral range of 450–1553 nm. The lower value of optical losses is equal to 0.7 dB/cm at 1553 nm. The optical losses due to the surface scattering are simulated showing that the contribution is the most significant at near infrared wavelength range, whereas the optical losses are due to volume scattering and material absorption in the visible range. The good physical properties and the low optical losses obtained from this planar waveguide are encouraging to achieve a wide bandgap optical guiding platform from these aluminum nitride thin films.

  15. Forecasting freight flows

    DEFF Research Database (Denmark)

    Lyk-Jensen, Stéphanie

    2011-01-01

    Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...... constitute a valuable input to freight models for forecasting future capacity problems.......Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...

  16. How uncertain are day-ahead wind forecasts?

    Energy Technology Data Exchange (ETDEWEB)

    Grimit, E. [3TIER Environmental Forecast Group, Seattle, WA (United States)

    2006-07-01

    Recent advances in the combination of weather forecast ensembles with Bayesian statistical techniques have helped to address uncertainties in wind forecasting. Weather forecast ensembles are a collection of numerical weather predictions. The combination of several equally-skilled forecasts typically results in a consensus forecast with greater accuracy. The distribution of forecasts also provides an estimate of forecast inaccuracy. However, weather forecast ensembles tend to be under-dispersive, and not all forecast uncertainties can be taken into account. In order to address these issues, a multi-variate linear regression approach was used to correct the forecast bias for each ensemble member separately. Bayesian model averaging was used to provide a predictive probability density function to allow for multi-modal probability distributions. A test location in eastern Canada was used to demonstrate the approach. Results of the test showed that the method improved wind forecasts and generated reliable prediction intervals. Prediction intervals were much shorter than comparable intervals based on a single forecast or on historical observations alone. It was concluded that the approach will provide economic benefits to both wind energy developers and investors. refs., tabs., figs.

  17. Forecasting interest rates with shifting endpoints

    DEFF Research Database (Denmark)

    Van Dijk, Dick; Koopman, Siem Jan; Wel, Michel van der

    2014-01-01

    We consider forecasting the term structure of interest rates with the assumption that factors driving the yield curve are stationary around a slowly time-varying mean or ‘shifting endpoint’. The shifting endpoints are captured using either (i) time series methods (exponential smoothing) or (ii......) long-range survey forecasts of either interest rates or inflation and output growth, or (iii) exponentially smoothed realizations of these macro variables. Allowing for shifting endpoints in yield curve factors provides substantial and significant gains in out-of-sample predictive accuracy, relative...... to stationary and random walk benchmarks. Forecast improvements are largest for long-maturity interest rates and for long-horizon forecasts....

  18. Introduction to time series analysis and forecasting

    CERN Document Server

    Montgomery, Douglas C; Kulahci, Murat

    2008-01-01

    An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data. Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Introduction to Time Series Analysis and Forecasting presents the time series analysis branch of applied statistics as the underlying methodology for developing practical forecasts, and it also bridges the gap between theory and practice by equipping readers with the tools needed to analyze time-oriented data and construct useful, short- to medium-term, statistically based forecasts.

  19. Streamlined approach for environmental restoration (SAFER) plan for corrective action unit 412: clean slate I plutonium dispersion (TTR) tonopah test range, Nevada, revision 0

    Energy Technology Data Exchange (ETDEWEB)

    Matthews, Patrick K.

    2015-04-01

    This Streamlined Approach for Environmental Restoration (SAFER) Plan addresses the actions needed to achieve closure for Corrective Action Unit (CAU) 412. CAU 412 is located on the Tonopah Test Range and consists of a single corrective action site (CAS), TA-23-01CS, Pu Contaminated Soil. There is sufficient information and historical documentation from previous investigations and the 1997 interim corrective action to recommend closure of CAU 412 using the SAFER process. Based on existing data, the presumed corrective action for CAU 412 is clean closure. However, additional data will be obtained during a field investigation to document and verify the adequacy of existing information and determine whether the CAU 412 closure objectives have been achieved. This SAFER Plan provides the methodology to gather the necessary information for closing the CAU.The following summarizes the SAFER activities that will support the closure of CAU 412:• Collect environmental samples from designated target populations to confirm or disprove the presence of contaminants of concern (COCs) as necessary to supplement existing information.• If no COCs are present, establish clean closure as the corrective action. • If COCs are present, the extent of contamination will be defined and further corrective actions will be evaluated with the stakeholders (NDEP, USAF).• Confirm the preferred closure option is sufficient to protect human health and the environment.

  20. Electrostatic Assemblies of Well-Dispersed AgNPs on the Surface of Electrospun Nanofibers as Highly Active SERS Substrates for Wide-Range pH Sensing.

    Science.gov (United States)

    Yang, Tong; Ma, Jun; Zhen, Shu Jun; Huang, Cheng Zhi

    2016-06-15

    Surface-enhanced Raman scattering (SERS) has shown high promise in analysis and bioanalysis, wherein noble metal nanoparticles (NMNPs) such as silver nanoparticles were employed as substrates because of their strong localized surface plasmon resonance (LSPR) properties. However, SERS-based pH sensing was restricted because of the aggregation of NMNPs in acidic medium or biosamples with high ionic strength. Herein, by using the electrostatic interaction as a driving force, AgNPs are assembled on the surface of ethylene imine polymer (PEI)/poly(vinyl alcohol) (PVA) electrospun nanofibers, which are then applied as highly sensitive and reproducible SERS substrate with an enhancement factor (EF) of 10(7)-10(8). When p-aminothiophenol (p-ATP) is used as an indicator with its b2 mode, a good and wide linear response to pH ranging from 2.56 to 11.20 could be available, and the as-prepared nanocomposite fibers then could be fabricated as excellent pH sensors in complicated biological samples such as urine, considering that the pH of urine could reflect the acid-base status of a person. This work not only emerges a cost-effective, direct, and convenient approach to homogeneously decorate AgNPs on the surface of polymer nanofibers but also supplies a route for preparing other noble metal nanofibrous sensing membranes.

  1. Sirocco - Fukushima Forecast Description

    International Nuclear Information System (INIS)

    2011-01-01

    SYMPHONIE-NH is the non-hydrostatic ocean model following the Boussinesq hydrostatic SYMPHONIE-2010 model developed by the Sirocco system team (CNRS and Toulouse University). Both are using an Arakawa type finite difference method for the C grid. The R and D team generally gives priority to a physically based approach of modelling (global conservation of the mechanical energy, consistency of pressure and density, accuracy of the bottom pressure torque,...) that tends to favour low order and robust numerical schemes. Most of the physical and numerical options (Non-Hydrostatic, free surface, generalised coordinates combined to an ALE method,...) are particularly suitable for the coastal area. At the request of the International Atomic Energy Agency (IAEA, March 14, 2011), SIROCCO is delivering every day a real time 6-day forecast bulletin of the dispersion in seawater of radionuclides emitted by the Fukushima nuclear plant. The simulations are based on the S2010.18 release of the 3D SIROCCO ocean circulation model. The system is operational since March 24 and the bulletin is available on an 'open-access' basis since March 28. The model uses a stretched horizontal grid with a variable horizontal resolution: from 600 m x 600 m at the nearest grid point from Fukushima, to 5 km x 5 km offshore. The initial fields (T, S, U, V, SSH) and the lateral open boundary conditions are provided by the Mercator PSY4V1R3 system (one field per day, horizontal resolution 1/12 deg. x 1/12 deg.). At the sea surface, the ocean model is forced by the meteorological fluxes delivered every 3 hours by ECMWF.i The tidal forcing at the lateral open boundaries is provided by the T-UGO model, implemented for this purpose by the SIROCCO team on the Japanese Pacific coast. Some details are given on the methodology: Bathymetry, Initialization and large scale forcing, Tides, Atmospheric forcing, Forecast protocol, and Scenario for radioactive tracers

  2. Sirocco - Fukushima Forecast Description

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2011-04-10

    SYMPHONIE-NH is the non-hydrostatic ocean model following the Boussinesq hydrostatic SYMPHONIE-2010 model developed by the Sirocco system team (CNRS and Toulouse University). Both are using an Arakawa type finite difference method for the C grid. The R and D team generally gives priority to a physically based approach of modelling (global conservation of the mechanical energy, consistency of pressure and density, accuracy of the bottom pressure torque,...) that tends to favour low order and robust numerical schemes. Most of the physical and numerical options (Non-Hydrostatic, free surface, generalised coordinates combined to an ALE method,...) are particularly suitable for the coastal area. At the request of the International Atomic Energy Agency (IAEA, March 14, 2011), SIROCCO is delivering every day a real time 6-day forecast bulletin of the dispersion in seawater of radionuclides emitted by the Fukushima nuclear plant. The simulations are based on the S2010.18 release of the 3D SIROCCO ocean circulation model. The system is operational since March 24 and the bulletin is available on an 'open-access' basis since March 28. The model uses a stretched horizontal grid with a variable horizontal resolution: from 600 m x 600 m at the nearest grid point from Fukushima, to 5 km x 5 km offshore. The initial fields (T, S, U, V, SSH) and the lateral open boundary conditions are provided by the Mercator PSY4V1R3 system (one field per day, horizontal resolution 1/12 deg. x 1/12 deg.). At the sea surface, the ocean model is forced by the meteorological fluxes delivered every 3 hours by ECMWF.i The tidal forcing at the lateral open boundaries is provided by the T-UGO model, implemented for this purpose by the SIROCCO team on the Japanese Pacific coast. Some details are given on the methodology: Bathymetry, Initialization and large scale forcing, Tides, Atmospheric forcing, Forecast protocol, and Scenario for radioactive tracers

  3. Combining forecast weights: Why and how?

    Science.gov (United States)

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

    2012-09-01

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

  4. Solid low-level waste forecasting guide

    International Nuclear Information System (INIS)

    Templeton, K.J.; Dirks, L.L.

    1995-03-01

    Guidance for forecasting solid low-level waste (LLW) on a site-wide basis is described in this document. Forecasting is defined as an approach for collecting information about future waste receipts. The forecasting approach discussed in this document is based solely on hanford's experience within the last six years. Hanford's forecasting technique is not a statistical forecast based upon past receipts. Due to waste generator mission changes, startup of new facilities, and waste generator uncertainties, statistical methods have proven to be inadequate for the site. It is recommended that an approach similar to Hanford's annual forecasting strategy be implemented at each US Department of Energy (DOE) installation to ensure that forecast data are collected in a consistent manner across the DOE complex. Hanford's forecasting strategy consists of a forecast cycle that can take 12 to 30 months to complete. The duration of the cycle depends on the number of LLW generators and staff experience; however, the duration has been reduced with each new cycle. Several uncertainties are associated with collecting data about future waste receipts. Volume, shipping schedule, and characterization data are often reported as estimates with some level of uncertainty. At Hanford, several methods have been implemented to capture the level of uncertainty. Collection of a maximum and minimum volume range has been implemented as well as questionnaires to assess the relative certainty in the requested data

  5. Hydrodynamic disperser

    Energy Technology Data Exchange (ETDEWEB)

    Bulatov, A.I.; Chernov, V.S.; Prokopov, L.I.; Proselkov, Yu.M.; Tikhonov, Yu.P.

    1980-01-15

    A hydrodynamic disperser is suggested which contains a housing, slit nozzles installed on a circular base arranged opposite from each other, resonators secured opposite the nozzle and outlet sleeve. In order to improve the effectiveness of dispersion by throttling the flow, each resonator is made in the form of a crimped plate with crimpings that decrease in height in a direction towards the nozzle.

  6. Development of a sales forecasting model for canopy windows

    OpenAIRE

    2014-01-01

    M.Com. (Business Management) Forecasting is an important function used in a wide range of business planning or decision-making situations. The purpose ofthis study was to build a sales forecasting model that would be practical and cost effective, from the various forecasting methods and techniques available. Various forecast models, methods and techniques are outlined in the initial part of this study by the author. The author has outlined some of the fundamentals and limitations that unde...

  7. Fuel cycle forecasting - there are forecasts and there are forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Puechl, K H

    1975-12-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis.

  8. Fuel cycle forecasting - there are forecasts and there are forecasts

    International Nuclear Information System (INIS)

    Puechl, K.H.

    1975-01-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis. (author)

  9. Verification of Space Weather Forecasts using Terrestrial Weather Approaches

    Science.gov (United States)

    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

  10. Inflation Forecast Contracts

    OpenAIRE

    Gersbach, Hans; Hahn, Volker

    2012-01-01

    We introduce a new type of incentive contract for central bankers: inflation forecast contracts, which make central bankers’ remunerations contingent on the precision of their inflation forecasts. We show that such contracts enable central bankers to influence inflation expectations more effectively, thus facilitating more successful stabilization of current inflation. Inflation forecast contracts improve the accuracy of inflation forecasts, but have adverse consequences for output. On balanc...

  11. International Workshop on Industry Practices for Forecasting

    CERN Document Server

    Poggi, Jean-Michel; Brossat, Xavier

    2015-01-01

    The chapters in this volume stress the need for advances in theoretical understanding to go hand-in-hand with the widespread practical application of forecasting in industry. Forecasting and time series prediction have enjoyed considerable attention over the last few decades, fostered by impressive advances in observational capabilities and measurement procedures. On June 5-7, 2013, an international Workshop on Industry Practices for FORecasting was held in Paris, France, organized and supported by the OSIRIS Department of Electricité de France Research and Development Division. In keeping with tradition, both theoretical statistical results and practical contributions on this active field of statistical research and on forecasting issues in a rapidly evolving industrial environment are presented. The volume reflects the broad spectrum of the conference, including 16 articles contributed by specialists in various areas. The material compiled is broad in scope and ranges from new findings on forecasting in in...

  12. Worldwide satellite market demand forecast

    Science.gov (United States)

    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.

  13. Electricity demand forecasting techniques

    International Nuclear Information System (INIS)

    Gnanalingam, K.

    1994-01-01

    Electricity demand forecasting plays an important role in power generation. The two areas of data that have to be forecasted in a power system are peak demand which determines the capacity (MW) of the plant required and annual energy demand (GWH). Methods used in electricity demand forecasting include time trend analysis and econometric methods. In forecasting, identification of manpower demand, identification of key planning factors, decision on planning horizon, differentiation between prediction and projection (i.e. development of different scenarios) and choosing from different forecasting techniques are important

  14. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

    Containing 12 new chapters, this second edition contains offers increased-coverage of weather correction and normalization of forecasts, anticipation of redevelopment, determining the validity of announced developments, and minimizing risk from over- or under-planning. It provides specific examples and detailed explanations of key points to consider for both standard and unusual utility forecasting situations, information on new algorithms and concepts in forecasting, a review of forecasting pitfalls and mistakes, case studies depicting challenging forecast environments, and load models illustrating various types of demand.

  15. Gambling scores for earthquake predictions and forecasts

    Science.gov (United States)

    Zhuang, Jiancang

    2010-04-01

    This paper presents a new method, namely the gambling score, for scoring the performance earthquake forecasts or predictions. Unlike most other scoring procedures that require a regular scheme of forecast and treat each earthquake equally, regardless their magnitude, this new scoring method compensates the risk that the forecaster has taken. Starting with a certain number of reputation points, once a forecaster makes a prediction or forecast, he is assumed to have betted some points of his reputation. The reference model, which plays the role of the house, determines how many reputation points the forecaster can gain if he succeeds, according to a fair rule, and also takes away the reputation points betted by the forecaster if he loses. This method is also extended to the continuous case of point process models, where the reputation points betted by the forecaster become a continuous mass on the space-time-magnitude range of interest. We also calculate the upper bound of the gambling score when the true model is a renewal process, the stress release model or the ETAS model and when the reference model is the Poisson model.

  16. Ensemble atmospheric dispersion modeling for emergency response consequence assessments

    International Nuclear Information System (INIS)

    Addis, R.P.; Buckley, R.L.

    2003-01-01

    models. This provides a better understanding of the atmosphere and plume behavior than would a single model output. Atmospheric models often give the impression of greater accuracy than the science is capable of delivering. The ensemble approach is a powerful way to reassert the concept of having a family of equally valid solutions, while enabling outliers to be identified. The U.S. Department of Energy's Savannah River Technology Center (SRTC) has participated in RTMOD and ENSEMBLE. SRTC uses the Regional Atmospheric Modeling System (RAMS) and Lagrangian Particle Dispersion Model (LPDM) to provide plume forecasts in real-time for the European grid as described in the figure. The NOAA northern hemispheric model, Global Forecast System (a combination of the medium range forecast and aviation forecast models), is used to provide the initial and boundary conditions for RAMS. The model plume forecast data are sent to the ENSEMBLE WEB page in real-time where they may be compared with other model outputs. SRTC has participated in all the ENSEMBLE exercises in real-time. An example of the ensemble output is shown in the figure, which shows an overlay of the SRTC (crosshatched) initial 60-hour forecast for the plume overlaid on an ensemble of 5 other model outputs. The plume shadings show the level of consensus for a minimum threshold, enabling modelers to determine consensus between models and identify possible outliers. The traditional approach to provide atmospheric consequence assessment tools to aid decision-makers in response to a release from a nuclear facility is to provide a plume output from a particular model. However, the non-unique nature of solutions to the non-linear equations that govern the atmosphere, and the sensitivity of such equations to perturbations in the initial and boundary conditions, results in any single model output being simply one of many viable solutions. As such, the traditional approach does a disservice to decision-makers by inferring greater

  17. Using Temperature Forecasts to Improve Seasonal Streamflow Forecasts in the Colorado and Rio Grande Basins

    Science.gov (United States)

    Lehner, F.; Wood, A.; Llewellyn, D.; Blatchford, D. B.; Goodbody, A. G.; Pappenberger, F.

    2017-12-01

    Recent studies have documented the influence of increasing temperature on streamflow across the American West, including snow-melt driven rivers such as the Colorado or Rio Grande. At the same time, some basins are reporting decreasing skill in seasonal streamflow forecasts, termed water supply forecasts (WSFs), over the recent decade. While the skill in seasonal precipitation forecasts from dynamical models remains low, their skill in predicting seasonal temperature variations could potentially be harvested for WSFs to account for non-stationarity in regional temperatures. Here, we investigate whether WSF skill can be improved by incorporating seasonal temperature forecasts from dynamical forecasting models (from the North American Multi Model Ensemble and the European Centre for Medium-Range Weather Forecast System 4) into traditional statistical forecast models. We find improved streamflow forecast skill relative to traditional WSF approaches in a majority of headwater locations in the Colorado and Rio Grande basins. Incorporation of temperature into WSFs thus provides a promising avenue to increase the robustness of current forecasting techniques in the face of continued regional warming.

  18. Dispersion stability of thermal nanofluids

    Directory of Open Access Journals (Sweden)

    Fan Yu

    2017-10-01

    Full Text Available Thermal nanofluids, the engineered fluids with dispersed functional nanoparticles, have exhibited extraordinary thermophysical properties and added functionalities, and thus have enabled a broad range of important applications. The poor dispersion stability of thermal nanofluids, however, has been considered as a long-existing issue that limits their further development and practical application. This review overviews the recent efforts and progresses in improving the dispersion stability of thermal nanofluids such as mechanistic understanding of dispersion behavior of nanofluids, examples of both water-based and oil-based nanofluids, strategies to stabilize nanofluids, and characterization techniques for dispersion behavior of nanofluids. Finally, on-going research needs, and possible solutions to research challenges and future research directions in exploring stably dispersed thermal nanofluids are discussed. Keywords: Thermal nanofluids, Dispersion, Aggregation, Electrostatic stabilization, Steric stabilization

  19. Inaccuracy in traffic forecasts

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent; Holm, Mette K. Skamris; Buhl, Søren Ladegaard

    2006-01-01

    This paper presents results from the first statistically significant study of traffic forecasts in transportation infrastructure projects. The sample used is the largest of its kind, covering 210 projects in 14 nations worth US$58 billion. The study shows with very high statistical significance...... that forecasters generally do a poor job of estimating the demand for transportation infrastructure projects. The result is substantial downside financial and economic risk. Forecasts have not become more accurate over the 30-year period studied. If techniques and skills for arriving at accurate demand forecasts...... forecasting. Highly inaccurate traffic forecasts combined with large standard deviations translate into large financial and economic risks. But such risks are typically ignored or downplayed by planners and decision-makers, to the detriment of social and economic welfare. The paper presents the data...

  20. Chemical dispersants

    NARCIS (Netherlands)

    Rahsepar, Shokouhalsadat; Smit, Martijn P.J.; Murk, Albertinka J.; Rijnaarts, Huub H.M.; Langenhoff, Alette A.M.

    2016-01-01

    Chemical dispersants were used in response to the Deepwater Horizon oil spill in the Gulf of Mexico, both at the sea surface and the wellhead. Their effect on oil biodegradation is unclear, as studies showed both inhibition and enhancement. This study addresses the effect of Corexit on oil

  1. FORECASTING MODELS IN MANAGEMENT

    OpenAIRE

    Sindelar, Jiri

    2008-01-01

    This article deals with the problems of forecasting models. First part of the article is dedicated to definition of the relevant areas (vertical and horizontal pillar of definition) and then the forecasting model itself is defined; as article presents theoretical background for further primary research, this definition is crucial. Finally the position of forecasting models within the management system is identified. The paper is a part of the outputs of FEM CULS grant no. 1312/11/3121.

  2. Forecasting in Planning

    OpenAIRE

    Ike, P.; Voogd, Henk; Voogd, Henk; Linden, Gerard

    2004-01-01

    This chapter begins with a discussion of qualitative forecasting by describing a number of methods that depend on judgements made by stakeholders, experts or other interested parties to arrive at forecasts. Two qualitative approaches are illuminated, the Delphi and scenario methods respectively. Quantitative forecasting is illustrated with a brief overview of time series methods. Both qualitative and quantitative methods are illustrated by an example. The role and relative importance of forec...

  3. The strategy of professional forecasting

    DEFF Research Database (Denmark)

    Ottaviani, Marco; Sørensen, Peter Norman

    2006-01-01

    We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters endeavor to convince the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts...... and the realized state. If the market expects forecasters to report their posterior expectations honestly, then forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded. The second theory posits that forecasters compete in a forecasting...... contest with pre-specified rules. In a winner-take-all contest, equilibrium forecasts are excessively differentiated...

  4. When mechanism matters: Bayesian forecasting using models of ecological diffusion

    Science.gov (United States)

    Hefley, Trevor J.; Hooten, Mevin B.; Russell, Robin E.; Walsh, Daniel P.; Powell, James A.

    2017-01-01

    Ecological diffusion is a theory that can be used to understand and forecast spatio-temporal processes such as dispersal, invasion, and the spread of disease. Hierarchical Bayesian modelling provides a framework to make statistical inference and probabilistic forecasts, using mechanistic ecological models. To illustrate, we show how hierarchical Bayesian models of ecological diffusion can be implemented for large data sets that are distributed densely across space and time. The hierarchical Bayesian approach is used to understand and forecast the growth and geographic spread in the prevalence of chronic wasting disease in white-tailed deer (Odocoileus virginianus). We compare statistical inference and forecasts from our hierarchical Bayesian model to phenomenological regression-based methods that are commonly used to analyse spatial occurrence data. The mechanistic statistical model based on ecological diffusion led to important ecological insights, obviated a commonly ignored type of collinearity, and was the most accurate method for forecasting.

  5. Measurement of the refractive index dispersion of As2Se3 bulk glass and thin films prior to and after laser irradiation and annealing using prism coupling in the near- and mid-infrared spectral range

    International Nuclear Information System (INIS)

    Carlie, N.; Petit, L.; Musgraves, J. D.; Richardson, K.; Anheier, N. C. Jr.; Qiao, H. A.; Bernacki, B.; Phillips, M. C.

    2011-01-01

    The prism coupling technique has been utilized to measure the refractive index in the near- and mid-IR spectral region of chalcogenide glasses in bulk and thin film form. A commercial system (Metricon model 2010) has been modified with additional laser sources, detectors, and a new GaP prism to allow the measurement of refractive index dispersion over the 1.5-10.6 μm range. The instrumental error was found to be ±0.001 refractive index units across the entire wavelength region examined. Measurements on thermally evaporated AMTIR2 thin films confirmed that (i) the film deposition process provides thin films with reduced index compared to that of the bulk glass used as a target, (ii) annealing of the films increases the refractive index of the film to the level of the bulk glass used as a target to create it, and (iii) it is possible to locally increase the refractive index of the chalcogenide glass using laser exposure at 632.8 nm.

  6. Forecasting Canadian nuclear power station construction costs

    International Nuclear Information System (INIS)

    Keng, C.W.K.

    1985-01-01

    Because of the huge volume of capital required to construct a modern electric power generating station, investment decisions have to be made with as complete an understanding of the consequences of the decision as possible. This understanding must be provided by the evaluation of future situations. A key consideration in an evaluation is the financial component. This paper attempts to use an econometric method to forecast the construction costs escalation of a standard Canadian nuclear generating station (NGS). A brief review of the history of Canadian nuclear electric power is provided. The major components of the construction costs of a Canadian NGS are studied and summarized. A database is built and indexes are prepared. Based on these indexes, an econometric forecasting model is constructed using an apparently new econometric methodology of forecasting modelling. Forecasts for a period of 40 years are generated and applications (such as alternative scenario forecasts and range forecasts) to uncertainty assessment and/or decision-making are demonstrated. The indexes, the model, and the forecasts and their applications, to the best of the author's knowledge, are the first for Canadian NGS constructions. (author)

  7. Use and Communication of Probabilistic Forecasts.

    Science.gov (United States)

    Raftery, Adrian E

    2016-12-01

    Probabilistic forecasts are becoming more and more available. How should they be used and communicated? What are the obstacles to their use in practice? I review experience with five problems where probabilistic forecasting played an important role. This leads me to identify five types of potential users: Low Stakes Users, who don't need probabilistic forecasts; General Assessors, who need an overall idea of the uncertainty in the forecast; Change Assessors, who need to know if a change is out of line with expectatations; Risk Avoiders, who wish to limit the risk of an adverse outcome; and Decision Theorists, who quantify their loss function and perform the decision-theoretic calculations. This suggests that it is important to interact with users and to consider their goals. The cognitive research tells us that calibration is important for trust in probability forecasts, and that it is important to match the verbal expression with the task. The cognitive load should be minimized, reducing the probabilistic forecast to a single percentile if appropriate. Probabilities of adverse events and percentiles of the predictive distribution of quantities of interest seem often to be the best way to summarize probabilistic forecasts. Formal decision theory has an important role, but in a limited range of applications.

  8. Use and Communication of Probabilistic Forecasts

    Science.gov (United States)

    Raftery, Adrian E.

    2015-01-01

    Probabilistic forecasts are becoming more and more available. How should they be used and communicated? What are the obstacles to their use in practice? I review experience with five problems where probabilistic forecasting played an important role. This leads me to identify five types of potential users: Low Stakes Users, who don’t need probabilistic forecasts; General Assessors, who need an overall idea of the uncertainty in the forecast; Change Assessors, who need to know if a change is out of line with expectatations; Risk Avoiders, who wish to limit the risk of an adverse outcome; and Decision Theorists, who quantify their loss function and perform the decision-theoretic calculations. This suggests that it is important to interact with users and to consider their goals. The cognitive research tells us that calibration is important for trust in probability forecasts, and that it is important to match the verbal expression with the task. The cognitive load should be minimized, reducing the probabilistic forecast to a single percentile if appropriate. Probabilities of adverse events and percentiles of the predictive distribution of quantities of interest seem often to be the best way to summarize probabilistic forecasts. Formal decision theory has an important role, but in a limited range of applications. PMID:28446941

  9. Six rules for accurate effective forecasting.

    Science.gov (United States)

    Saffo, Paul

    2007-01-01

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

  10. Assessing flood forecast uncertainty with fuzzy arithmetic

    Directory of Open Access Journals (Sweden)

    de Bruyn Bertrand

    2016-01-01

    Full Text Available Providing forecasts for flow rates and water levels during floods have to be associated with uncertainty estimates. The forecast sources of uncertainty are plural. For hydrological forecasts (rainfall-runoff performed using a deterministic hydrological model with basic physics, two main sources can be identified. The first obvious source is the forcing data: rainfall forecast data are supplied in real time by meteorological forecasting services to the Flood Forecasting Service within a range between a lowest and a highest predicted discharge. These two values define an uncertainty interval for the rainfall variable provided on a given watershed. The second source of uncertainty is related to the complexity of the modeled system (the catchment impacted by the hydro-meteorological phenomenon, the number of variables that may describe the problem and their spatial and time variability. The model simplifies the system by reducing the number of variables to a few parameters. Thus it contains an intrinsic uncertainty. This model uncertainty is assessed by comparing simulated and observed rates for a large number of hydro-meteorological events. We propose a method based on fuzzy arithmetic to estimate the possible range of flow rates (and levels of water making a forecast based on possible rainfalls provided by forcing and uncertainty model. The model uncertainty is here expressed as a range of possible values. Both rainfall and model uncertainties are combined with fuzzy arithmetic. This method allows to evaluate the prediction uncertainty range. The Flood Forecasting Service of Oise and Aisne rivers, in particular, monitors the upstream watershed of the Oise at Hirson. This watershed’s area is 310 km2. Its response time is about 10 hours. Several hydrological models are calibrated for flood forecasting in this watershed and use the rainfall forecast. This method presents the advantage to be easily implemented. Moreover, it permits to be carried out

  11. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    Directory of Open Access Journals (Sweden)

    Christian Pierdzioch

    2012-11-01

    Full Text Available We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-herding of forecasters. Forecasts are consistent with herding (anti-herding of forecasters if forecasts are biased towards (away from the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time.

  12. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Ruelke

    2013-01-01

    We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-)herding of forecasters. Forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from) t......) the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time....

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

    Science.gov (United States)

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

    2016-11-01

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

  14. World Area Forecast System (WAFS)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The World Area Forecast System (WAFS) is a worldwide system by which world area forecast centers provide aeronautical meteorological en-route forecasts in uniform...

  15. Dispersal of sticky particles

    Science.gov (United States)

    Reddy, Ramana; Kumar, Sanjeev

    2007-12-01

    In this paper, we show through simulations that when sticky particles are broken continually, particles are dispersed into fine dust only if they are present in a narrow range of volume fractions. The upper limit of this range is 0.20 in the 2D and 0.10 in the 3D space. An increase in the dimensionality of space reduces the upper limit nearly by a factor of two. This scaling holds for dispersal of particles in hyperdimensional space of dimensions up to ten, the maximum dimension studied in this work. The maximum values of volume fractions obtained are significantly lower than those required for close packing and random packing of discs in 2D and spheres in 3D space. These values are also smaller than those required for critical phenomena of cluster percolation. The results obtained are attributed to merger cascades of sticky particles, triggered by breakup events. A simple theory that incorporates this cascade is developed to quantitatively explain the observed scaling of the upper limit with the dimensionality of space. The theory also captures the dynamics of the dispersal process in the corresponding range of particle volume fractions. The theory suggests that cascades of order one and two predominantly decide the upper limit for complete dispersal of particles.

  16. Improving weather forecasts for wind energy applications

    Science.gov (United States)

    Kay, Merlinde; MacGill, Iain

    2010-08-01

    Weather forecasts play an important role in the energy industry particularly because of the impact of temperature on electrical demand. Power system operation requires that this variable and somewhat unpredictable demand be precisely met at all times and locations from available generation. As wind generation makes up a growing component of electricity supply around the world, it has become increasingly important to be able to provide useful forecasting for this highly variable and uncertain energy resource. Of particular interest are forecasts of weather events that rapidly change wind energy production from one or more wind farms. In this paper we describe work underway to improve the wind forecasts currently available from standard Numerical Weather Prediction (NWP) through a bias correction methodology. Our study has used the Australian Bureau of Meteorology MesoLAPS 5 km limited domain model over the Victoria/Tasmania region, providing forecasts for the Woolnorth wind farm, situated in Tasmania, Australia. The accuracy of these forecasts has been investigated, concentrating on the key wind speed ranges 5 - 15 ms-1 and around 25 ms-1. A bias correction methodology was applied to the NWP hourly forecasts to help account for systematic issues such as the NWP grid point not being at the exact location of the wind farm. An additional correction was applied for timing issues by using meteorological data from the wind farm. Results to date show a reduction in spread of forecast error for hour ahead forecasts by as much as half using this double correction methodology - a combination of both bias correction and timing correction.

  17. Improving weather forecasts for wind energy applications

    International Nuclear Information System (INIS)

    Kay, Merlinde; MacGill, Iain

    2010-01-01

    Weather forecasts play an important role in the energy industry particularly because of the impact of temperature on electrical demand. Power system operation requires that this variable and somewhat unpredictable demand be precisely met at all times and locations from available generation. As wind generation makes up a growing component of electricity supply around the world, it has become increasingly important to be able to provide useful forecasting for this highly variable and uncertain energy resource. Of particular interest are forecasts of weather events that rapidly change wind energy production from one or more wind farms. In this paper we describe work underway to improve the wind forecasts currently available from standard Numerical Weather Prediction (NWP) through a bias correction methodology. Our study has used the Australian Bureau of Meteorology MesoLAPS 5 km limited domain model over the Victoria/Tasmania region, providing forecasts for the Woolnorth wind farm, situated in Tasmania, Australia. The accuracy of these forecasts has been investigated, concentrating on the key wind speed ranges 5 - 15 ms -1 and around 25 ms -1 . A bias correction methodology was applied to the NWP hourly forecasts to help account for systematic issues such as the NWP grid point not being at the exact location of the wind farm. An additional correction was applied for timing issues by using meteorological data from the wind farm. Results to date show a reduction in spread of forecast error for hour ahead forecasts by as much as half using this double correction methodology - a combination of both bias correction and timing correction.

  18. Forecasting in Planning

    NARCIS (Netherlands)

    Ike, P.; Voogd, Henk; Voogd, Henk; Linden, Gerard

    2004-01-01

    This chapter begins with a discussion of qualitative forecasting by describing a number of methods that depend on judgements made by stakeholders, experts or other interested parties to arrive at forecasts. Two qualitative approaches are illuminated, the Delphi and scenario methods respectively.

  19. Improving Garch Volatility Forecasts

    NARCIS (Netherlands)

    Klaassen, F.J.G.M.

    1998-01-01

    Many researchers use GARCH models to generate volatility forecasts. We show, however, that such forecasts are too variable. To correct for this, we extend the GARCH model by distinguishing two regimes with different volatility levels. GARCH effects are allowed within each regime, so that our model

  20. On density forecast evaluation

    NARCIS (Netherlands)

    Diks, C.

    2008-01-01

    Traditionally, probability integral transforms (PITs) have been popular means for evaluating density forecasts. For an ideal density forecast, the PITs should be uniformly distributed on the unit interval and independent. However, this is only a necessary condition, and not a sufficient one, as

  1. Net load forecasting for high renewable energy penetration grids

    International Nuclear Information System (INIS)

    Kaur, Amanpreet; Nonnenmacher, Lukas; Coimbra, Carlos F.M.

    2016-01-01

    We discuss methods for net load forecasting and their significance for operation and management of power grids with high renewable energy penetration. Net load forecasting is an enabling technology for the integration of microgrid fleets with the macrogrid. Net load represents the load that is traded between the grids (microgrid and utility grid). It is important for resource allocation and electricity market participation at the point of common coupling between the interconnected grids. We compare two inherently different approaches: additive and integrated net load forecast models. The proposed methodologies are validated on a microgrid with 33% annual renewable energy (solar) penetration. A heuristics based solar forecasting technique is proposed, achieving skill of 24.20%. The integrated solar and load forecasting model outperforms the additive model by 10.69% and the uncertainty range for the additive model is larger than the integrated model by 2.2%. Thus, for grid applications an integrated forecast model is recommended. We find that the net load forecast errors and the solar forecasting errors are cointegrated with a common stochastic drift. This is useful for future planning and modeling because the solar energy time-series allows to infer important features of the net load time-series, such as expected variability and uncertainty. - Highlights: • Net load forecasting methods for grids with renewable energy generation are discussed. • Integrated solar and load forecasting outperforms the additive model by 10.69%. • Net load forecasting reduces the uncertainty between the interconnected grids.

  2. Forecast Accuracy Uncertainty and Momentum

    OpenAIRE

    Bing Han; Dong Hong; Mitch Warachka

    2009-01-01

    We demonstrate that stock price momentum and earnings momentum can result from uncertainty surrounding the accuracy of cash flow forecasts. Our model has multiple information sources issuing cash flow forecasts for a stock. The investor combines these forecasts into an aggregate cash flow estimate that has minimal mean-squared forecast error. This aggregate estimate weights each cash flow forecast by the estimated accuracy of its issuer, which is obtained from their past forecast errors. Mome...

  3. Review and forecast: Making hay

    International Nuclear Information System (INIS)

    Curran, R.

    1997-01-01

    Oil and natural gas industry prospects for 1997 were reviewed. By way of providing the foundation for a very favorable forecast, a wide range of indicators of a banner year in 1996 were assembled and provided in tabular form. Some 28 tables of statistical data provide insight into the reasons for an optimistic forecast for 1997. Statistics on oil and gas production, industry expenditures, exploratory well completions, costs per barrel of oil, estimates of supply and demand for petroleum products, gas liquid production, petrochemical and fertilizer production, sulfur production, drilling statistics, natural gas sales, gross production revenues and land sales, all attest to a record year in 1996, and provide reasons for a rosy outlook for 1997. 28 tabs

  4. Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch

    KAUST Repository

    Xie, Le

    2014-01-01

    We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models. © 2013 IEEE.

  5. Objective Identification of Environmental Patterns Related to Tropical Cyclone Track Forecast Errors

    National Research Council Canada - National Science Library

    Sanabia, Elizabeth R

    2006-01-01

    The increase in skill of numerical model guidance and the use of consensus forecast techniques have led to significant improvements in the accuracy of tropical cyclone track forecasts at ranges beyond 72 hours...

  6. Operational foreshock forecasting: Fifteen years after

    Science.gov (United States)

    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. Forecasting market developments

    International Nuclear Information System (INIS)

    Weller, T.

    1997-01-01

    Traditional planning in essence consists of linear extrapolation of established facts and experience. This approach was good enough until recently, when progress would be relatively foreseeable within a stable system. The situation has been changing with developments and modifications in the global economic sector proceeding at accelerated pace, so that conventional planning methods become hopelessly inadequate. The past is of low significance to emerging markets; planners today have to keep abreast with and take into account the possible and emerging influencing factors. Experience is a factor to be replaced by intelligent analysis and conclusion within the framework of system networks. Modern scenario modelling methods are based on this approach: They are able to simulate and forecast a whole range of ''possible futures'', derived from perceivable trends. The article illustrates the novel planning methodology by assessing the future of the renewable energy sources, applying a computerized planning method (vision design) which is based on intelligent comparative analysis of all relevant trends. (Orig./RHM) [de

  8. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

    Spatial Electric Load Forecasting Consumer Demand for Power and ReliabilityCoincidence and Load BehaviorLoad Curve and End-Use ModelingWeather and Electric LoadWeather Design Criteria and Forecast NormalizationSpatial Load Growth BehaviorSpatial Forecast Accuracy and Error MeasuresTrending MethodsSimulation Method: Basic ConceptsA Detailed Look at the Simulation MethodBasics of Computerized SimulationAnalytical Building Blocks for Spatial SimulationAdvanced Elements of Computerized SimulationHybrid Trending-Simulation MethodsAdvanced

  9. High Resolution Trajectory-Based Smoke Forecasts Using VIIRS Aerosol Optical Depth and NUCAPS Carbon Monoxide Retrievals

    Science.gov (United States)

    Pierce, R. B.; Smith, N.; Barnet, C.; Barnet, C. D.; Kondragunta, S.; Davies, J. E.; Strabala, K.

    2016-12-01

    We use Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Aerosol Optical Depth (AOD) and combined Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) NOAA-Unique CrIS-ATMS Processing System (NUCAPS) carbon monoxide (CO) retrievals to initialize trajectory-based, high spatial resolution North American smoke dispersion forecasts during the May 2016 Fort McMurray wildfire in northern Alberta and the July 2016 Soberanes Fire in Northern California. These two case studies illustrate how long range transport of wild fire smoke can adversely impact surface air quality thousands of kilometers downwind and how local topographic flow can lead to complex transport patterns near the wildfire source region. The NUCAPS CO retrievals are shown to complement the high resolution VIIRS AOD retrievals by providing retrievals in partially cloudy scenes and also providing information on the vertical distribution of the wildfire smoke. This work addresses the need for low latency, web-based, high resolution forecasts of smoke dispersion for use by NWS Incident Meteorologists (IMET) to support on-site decision support services for fire incident management teams. The primary user community for the IDEA-I smoke forecasts is the Western regions of the NWS and US EPA due to the significant impacts of wildfires in these regions. Secondary users include Alaskan NWS offices and Western State and Local air quality management agencies such as the Western Regional Air Partnership (WRAP).

  10. About the National Forecast Chart

    Science.gov (United States)

    code. Press enter or select the go button to submit request Local forecast by "City, St" or Prediction Center on Twitter NCEP Quarterly Newsletter WPC Home Analyses and Forecasts National Forecast to all federal, state, and local government web resources and services. The National Forecast Charts

  11. Boundary layer heights and surface fluxes of momentum and heat derived from ECMWF data for use in pollutant dispersion models - problems with data accuracy

    Energy Technology Data Exchange (ETDEWEB)

    Wotawa, G. [Univ. of Agricultural Sciences, Inst. of Meteorology and Physics, Vienna (Austria); Stohl, A. [Ludwig-Maximilians-Univ. Muenchen, Munich (Germany)

    1997-10-01

    Certain boundary layer parameters, especially boundary layer heights, are very important for pollutant dispersion modelling. On the regional scale (>- 100 km), data of the numerical weather prediction model of the European Centre for Medium-Range Weather Forecasts are often used for that purpose. Based on ECMWF data, the meteorological preprocessor FLEXTRA for Lagrangian air quality simulation models and the Lagrangian particle diffusion model FLEXPART have been developed. Using analyses and short term forecasts, a temporal resolution of three hours can be achieved. Some alternative methods to obtain boundary layer parameters can be applied, producing different results which affect all subsequent calculations, for instance the calculation of boundary layer trajectories and the dispersion of air pollutants. (au)

  12. Atmospheric dispersion modeling: Challenges of the Fukushima Daiichi response

    Energy Technology Data Exchange (ETDEWEB)

    Sugiyama, Gayle [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Nasstrom, John [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pobanz, Brenda [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Foster, Kevin [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Simpson, Matthew [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Vogt, Phil [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Aluzzi, Fernando [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Homann, Steve [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2012-05-01

    In this research, the U.S. Department of Energy’s (DOE) National Atmospheric Release Advisory Center (NARAC) provided a wide range of predictions and analyses as part of the response to the Fukushima Daiichi Nuclear Power Plant accident including: daily Japanese weather forecasts and atmospheric transport predictions to inform planning for field monitoring operations and to provide U.S. government agencies with ongoing situational awareness of meteorological conditions; estimates of possible dose in Japan based on hypothetical U.S. Nuclear Regulatory Commission scenarios of potential radionuclide releases to support protective action planning for U.S. citizens; predictions of possible plume arrival times and dose levels at U.S. locations; and source estimation and plume model refinement based on atmospheric dispersion modeling and available monitoring data.

  13. Marine Point Forecasts

    Science.gov (United States)

    will link to the zone forecast and then allow further zooming to the point of interest whereas on the Honolulu, HI Chicago, IL Northern Indiana, IN Lake Charles, LA New Orleans, LA Boston, MA Caribou, ME

  14. Socioeconomic Forecasting : [Technical Summary

    Science.gov (United States)

    2012-01-01

    Because the traffic forecasts produced by the Indiana : Statewide Travel Demand Model (ISTDM) are driven by : the demographic and socioeconomic inputs to the model, : particular attention must be given to obtaining the most : accurate demographic and...

  15. NYHOPS Forecast Model Results

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — 3D Marine Nowcast/Forecast System for the New York Bight NYHOPS subdomain. Currents, waves, surface meteorology, and water conditions.

  16. Inflow forecasting at BPA

    Energy Technology Data Exchange (ETDEWEB)

    McManamon, A. [Bonneville Power Administration, Portland, OR (United States)

    2007-07-01

    The Columbia River Power System operates with consideration for flood control, endangered species, navigation, irrigation, water supply, recreation, other fish and wildlife concerns and power production. The Bonneville Power Association (BPA) located in Portland, Oregon is responsible for 35-40 per cent of the power consumed within the region. This presentation discussed inflow power concerns at BPA. The presentation illustrated elevational relief of projects; annual and daily variability; the hydrologic cycle; national river service weather forecasting service (NRSWFS); components of NRSWFS; and hydrologic forecast locations. Project operations and inventory were included along with a comparison of the 71-year average unregulated flow with regulated flow at the Dalles. Consistency between short-term and long-term forecasts and long-term streamflow forecasts were also illustrated in graphical format. The presentation also discussed the issue of reducing model and parameter uncertainty; reducing initial conditions uncertainty; snow updating; and reducing meteorological uncertainty. tabs., figs.

  17. CCAA seasonal forecasting

    International Development Research Centre (IDRC) Digital Library (Canada)

    Integrating meteorological and indigenous knowledge-based seasonal climate forecasts in ..... Explanation is based on spiritual and social values. Taught by .... that provided medicine and food became the subject of strict rules and practices ...

  18. Forecast Icing Product

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Forecast Icing Product (FIP) is an automatically-generated index suitable for depicting areas of potentially hazardous airframe icing. The FIP algorithm uses...

  19. Numerical Weather Forecasting at the Savannah River Site

    International Nuclear Information System (INIS)

    Buckley, R.L.

    1999-01-01

    Facilities such as the Savannah River Site (SRS), which contain the potential for hazardous atmospheric releases, rely on the predictive capabilities of dispersion models to assess possible emergency response actions. The operational design in relation to domain size and forecast time is presented, along with verification of model results over extended time periods with archived surface observations

  20. Dispersion strengthening

    International Nuclear Information System (INIS)

    Scattergood, R.O.; Das, E.S.P.

    1976-01-01

    Using digital computer-based methods, models for dispersion strengthening can now be developed which take into account many of the important effects that have been neglected in the past. In particular, the self interaction of a dislocation can be treated, and a computer simulation method was developed to determine the flow stress of a random distribution of circular, impenetrable obstacles, taking into account all such interactions. The flow stress values depended on the obstacle sizes and spacings, over and above the usual 1/L dependence where L is the average obstacle spacing. From an analysis of the results, it was found that the main effects of the self interactions can be captured in a line tension analogue in which the obstacles appear to be penetrable

  1. Conditional Probabilistic Population Forecasting

    OpenAIRE

    Sanderson, W.C.; Scherbov, S.; O'Neill, B.C.; Lutz, W.

    2003-01-01

    Since policy makers often prefer to think in terms of scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy makers it allows them to answer "what if"...

  2. Conditional probabilistic population forecasting

    OpenAIRE

    Sanderson, Warren; Scherbov, Sergei; O'Neill, Brian; Lutz, Wolfgang

    2003-01-01

    Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because it allows them...

  3. Conditional Probabilistic Population Forecasting

    OpenAIRE

    Sanderson, Warren C.; Scherbov, Sergei; O'Neill, Brian C.; Lutz, Wolfgang

    2004-01-01

    Since policy-makers often prefer to think in terms of alternative scenarios, the question has arisen as to whether it is possible to make conditional population forecasts in a probabilistic context. This paper shows that it is both possible and useful to make these forecasts. We do this with two different kinds of examples. The first is the probabilistic analog of deterministic scenario analysis. Conditional probabilistic scenario analysis is essential for policy-makers because...

  4. EU pharmaceutical expenditure forecast

    OpenAIRE

    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’ ph...

  5. Problems of Forecast

    OpenAIRE

    Kucharavy , Dmitry; De Guio , Roland

    2005-01-01

    International audience; The ability to foresee future technology is a key task of Innovative Design. The paper focuses on the obstacles to reliable prediction of technological evolution for the purpose of Innovative Design. First, a brief analysis of problems for existing forecasting methods is presented. The causes for the complexity of technology prediction are discussed in the context of reduction of the forecast errors. Second, using a contradiction analysis, a set of problems related to ...

  6. The potential value of seasonal forecasts in a changing climate

    CSIR Research Space (South Africa)

    Winsemius, HC

    2013-12-01

    Full Text Available -range Weather Forecasts (ECMWF) seasonal forecasting system. The focus is on the frequency of dry spells as well as the frequency of heat stress conditions expressed in the Temperature Heat Index. In areas where their frequency of occurrence increases...

  7. Visualizing uncertainty : Towards a better understanding of weather forecasts

    NARCIS (Netherlands)

    Toet, A.; Tak, S.; Erp, J.B.F. van

    2016-01-01

    Uncertainty visualizations are increasingly used in communications to the general public. A well-known example is the weather forecast. Rather than providing an exact temperature value, weather forecasts often show the range in which the temperature will lie. But uncertainty visualizations are also

  8. Long range trajectories

    Energy Technology Data Exchange (ETDEWEB)

    Allen, P. W.; Jessup, E. A.; White, R. E. [Air Resources Field Research Office, Las Vegas, Nevada (United States)

    1967-07-01

    A single air molecule can have a trajectory that can be described with a line, but most meteorologists use single lines to represent the trajectories of air parcels. A single line trajectory has the disadvantage that it is a categorical description of position. Like categorized forecasts it provides no qualification, and no provision for dispersion in case the parcel contains two or more molecules which may take vastly different paths. Diffusion technology has amply demonstrated that an initial aerosol cloud or volume of gas in the atmosphere not only grows larger, but sometimes divides into puffs, each having a different path or swath. Yet, the average meteorologist, faced with the problem of predicting the future motion of a cloud, usually falls back on the line trajectory approach with the explanation that he had no better tool for long range application. In his more rational moments, he may use some arbitrary device to spread his cloud with distance. One such technique has been to separate the trajectory into two or more trajectories, spaced about the endpoint of the original trajectory after a short period of travel, repeating this every so often like a chain reaction. This has the obvious disadvantage of involving a large amount of labor without much assurance of improved accuracy. Another approach is to draw a circle about the trajectory endpoint, to represent either diffusion or error. The problem then is to know what radius to give the circle and also whether to call it diffusion or error. Meteorologists at the Nevada Test Site (NTS) are asked frequently to provide advice which involves trajectory technology, such as prediction of an aerosol cloud path, reconstruction of the motion of a volume of air, indication of the dilution, and the possible trajectory prediction error over great distances. Therefore, we set out, nearly three years ago, to provide some statistical knowledge about the status of our trajectory technology. This report contains some of the

  9. Multicomponent ensemble models to forecast induced seismicity

    Science.gov (United States)

    Király-Proag, E.; Gischig, V.; Zechar, J. D.; Wiemer, S.

    2018-01-01

    In recent years, human-induced seismicity has become a more and more relevant topic due to its economic and social implications. Several models and approaches have been developed to explain underlying physical processes or forecast induced seismicity. They range from simple statistical models to coupled numerical models incorporating complex physics. We advocate the need for forecast testing as currently the best method for ascertaining if models are capable to reasonably accounting for key physical governing processes—or not. Moreover, operational forecast models are of great interest to help on-site decision-making in projects entailing induced earthquakes. We previously introduced a standardized framework following the guidelines of the Collaboratory for the Study of Earthquake Predictability, the Induced Seismicity Test Bench, to test, validate, and rank induced seismicity models. In this study, we describe how to construct multicomponent ensemble models based on Bayesian weightings that deliver more accurate forecasts than individual models in the case of Basel 2006 and Soultz-sous-Forêts 2004 enhanced geothermal stimulation projects. For this, we examine five calibrated variants of two significantly different model groups: (1) Shapiro and Smoothed Seismicity based on the seismogenic index, simple modified Omori-law-type seismicity decay, and temporally weighted smoothed seismicity; (2) Hydraulics and Seismicity based on numerically modelled pore pressure evolution that triggers seismicity using the Mohr-Coulomb failure criterion. We also demonstrate how the individual and ensemble models would perform as part of an operational Adaptive Traffic Light System. Investigating seismicity forecasts based on a range of potential injection scenarios, we use forecast periods of different durations to compute the occurrence probabilities of seismic events M ≥ 3. We show that in the case of the Basel 2006 geothermal stimulation the models forecast hazardous levels

  10. Energy reference forecast for 2014

    International Nuclear Information System (INIS)

    Schlesinger, Michael; Lutz, Christian

    2014-01-01

    The German Federal Ministry for Economic Affairs and Energy has commissioned three reputed institutions to prepare an energy reference forecast as well as a target scenario up to the year 2050. The results of this survey evidence a substantial need for political action if the goals of the Federal Government's energy concept are to be achieved as planned. In view of the wide range of interests among the players involved as well as the complexity of the demands facing the political leadership from diverse areas of life it appears unlikely that the targets laid down in the energy concept can be realised.

  11. Lagrangian Stochastic Dispersion Model IMS Model Suite and its Validation against Experimental Data

    International Nuclear Information System (INIS)

    Bartok, J.

    2010-01-01

    The dissertation presents IMS Lagrangian Dispersion Model, which is a 'new generation' Slovak dispersion model of long-range transport, developed by MicroStep-MIS. It solves trajectory equation for a vast number of Lagrangian 'particles' and stochastic equation that simulates the effects of turbulence. Model contains simulation of radioactive decay (full decay chains of more than 300 nuclides), and dry and wet deposition. Model was integrated into IMS Model Suite, a system in which several models and modules can run and cooperate, e.g. LAM model WRF preparing fine resolution meteorological data for dispersion. The main theme of the work is validation of dispersion model against large scale international campaigns CAPTEX and ETEX, which are two of the largest tracer experiments. Validation addressed treatment of missing data, data interpolation into comparable temporal and spatial representation. The best model results were observed for ETEX I, standard results for CAPTEXes and worst results for ETEX II, known in modelling community for its meteorological conditions that can be hardly resolved by models. The IMS Lagrangian Dispersion Model was identified as capable long range dispersion model for slowly- or nonreacting chemicals and radioactive matter. Influence of input data on simulation quality is discussed within the work. Additional modules were prepared according to praxis requirement: a) Recalculation of concentrations of radioactive pollutant into effective doses form inhalation, immersion in the plume and deposition. b) Dispersion of mineral dust was added and tested in desert locality, where wind and soil moisture were firstly analysed and forecast by WRF. The result was qualitatively verified in case study against satellite observations. (author)

  12. Hydrodynamic dispersion

    International Nuclear Information System (INIS)

    Pryce, M.H.L.

    1985-01-01

    A dominant mechanism contributing to hydrodynamic dispersion in fluid flow through rocks is variation of travel speeds within the channels carrying the fluid, whether these be interstices between grains, in granular rocks, or cracks in fractured crystalline rocks. The complex interconnections of the channels ensure a mixing of those parts of the fluid which travel more slowly and those which travel faster. On a macroscopic scale this can be treated statistically in terms of the distribution of times taken by a particle of fluid to move from one surface of constant hydraulic potential to another, lower, potential. The distributions in the individual channels are such that very long travel times make a very important contribution. Indeed, while the mean travel time is related to distance by a well-defined transport speed, the mean square is effectively infinite. This results in an asymmetrical plume which differs markedly from a gaussian shape. The distribution of microscopic travel times is related to the distribution of apertures in the interstices, or in the microcracks, which in turn are affected in a complex way by the stresses acting on the rock matrix

  13. The Lagrangian particle dispersion model FLEXPART-WRF VERSION 3.1

    Energy Technology Data Exchange (ETDEWEB)

    Brioude, J.; Arnold, D.; Stohl, A.; Cassiani, M.; Morton, Don; Seibert, P.; Angevine, W. M.; Evan, S.; Dingwell, A.; Fast, Jerome D.; Easter, Richard C.; Pisso, I.; Bukhart, J.; Wotawa, G.

    2013-11-01

    The Lagrangian particle dispersion model FLEXPART was originally designed for cal- culating long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. In the meantime FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. This multiscale need from the modeler community has encouraged new developments in FLEXPART. In this document, we present a version that works with the Weather Research and Forecasting (WRF) mesoscale meteoro- logical model. Simple procedures on how to run FLEXPART-WRF are presented along with special options and features that differ from its predecessor versions. In addition, test case data, the source code and visualization tools are provided to the reader as supplementary material.

  14. Blending Chem-Bio Dispersion Forecasts and Sensor Data

    Science.gov (United States)

    2008-12-31

    Kerrie Long. 5d. PROJECT NUMBER N/A 5e. TASK NUMBER N/A 5f. WORK UNIT NUMBER N/A 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) CUBRC ...Acknowlegments I gratefully acknowledge the efforts of the team of faculty, consultants and graduate students from CUBRC , the University at Buffalo, the...Moskal, CUBRC Alex James, CUBRC 3.5 Graduate Students Umamaheswara Reddy, Dept. Mechanical Engineering, University at Buffalo Gabriel Terejanu

  15. The forecasting of the dispersal of gaseous reactor wastes

    International Nuclear Information System (INIS)

    Belot, Y.; Caput, C.; Quinault, J.M.

    1977-01-01

    Given the wind rose, the mean annual concentrations can be determined by the mean of a simple model. The amounts of iodine and tritium deposited into vegetation are calculated by multiplying the concentrations by easily derived coefficients. A calculation program has been worked out giving isopleths on the regional maps [fr

  16. Dispersion coefficients for coastal regions

    International Nuclear Information System (INIS)

    MacRae, B.L.; Kaleel, R.J.; Shearer, D.L.

    1983-03-01

    The Nuclear Regulatory Commission (NRC) has undertaken an extensive atmospheric dispersion research and measurement program from which it is intended will emerge improved predictive techniques for employment in licensing decisions and for emergency planning and response. Through this program the NRC has conducted field measurement programs over a wide range of geographic and topographic locations, and are using the acquired tracer and meteorological measurements to evaluate existing dispersion models and prediction techniques, and to develop new techniques when necessary

  17. Operational mesoscale atmospheric dispersion prediction using high performance parallel computing cluster for emergency response

    International Nuclear Information System (INIS)

    Srinivas, C.V.; Venkatesan, R.; Muralidharan, N.V.; Das, Someshwar; Dass, Hari; Eswara Kumar, P.

    2005-08-01

    An operational atmospheric dispersion prediction system is implemented on a cluster super computer for 'Online Emergency Response' for Kalpakkam nuclear site. The numerical system constitutes a parallel version of a nested grid meso-scale meteorological model MM5 coupled to a random walk particle dispersion model FLEXPART. The system provides 48 hour forecast of the local weather and radioactive plume dispersion due to hypothetical air borne releases in a range of 100 km around the site. The parallel code was implemented on different cluster configurations like distributed and shared memory systems. Results of MM5 run time performance for 1-day prediction are reported on all the machines available for testing. A reduction of 5 times in runtime is achieved using 9 dual Xeon nodes (18 physical/36 logical processors) compared to a single node sequential run. Based on the above run time results a cluster computer facility with 9-node Dual Xeon is commissioned at IGCAR for model operation. The run time of a triple nested domain MM5 is about 4 h for 24 h forecast. The system has been operated continuously for a few months and results were ported on the IMSc home page. Initial and periodic boundary condition data for MM5 are provided by NCMRWF, New Delhi. An alternative source is found to be NCEP, USA. These two sources provide the input data to the operational models at different spatial and temporal resolutions and using different assimilation methods. A comparative study on the results of forecast is presented using these two data sources for present operational use. Slight improvement is noticed in rainfall, winds, geopotential heights and the vertical atmospheric structure while using NCEP data probably because of its high spatial and temporal resolution. (author)

  18. Space Weather Forecasting at IZMIRAN

    Science.gov (United States)

    Gaidash, S. P.; Belov, A. V.; Abunina, M. A.; Abunin, A. A.

    2017-12-01

    Since 1998, the Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation (IZMIRAN) has had an operating heliogeophysical service—the Center for Space Weather Forecasts. This center transfers the results of basic research in solar-terrestrial physics into daily forecasting of various space weather parameters for various lead times. The forecasts are promptly available to interested consumers. This article describes the center and the main types of forecasts it provides: solar and geomagnetic activity, magnetospheric electron fluxes, and probabilities of proton increases. The challenges associated with the forecasting of effects of coronal mass ejections and coronal holes are discussed. Verification data are provided for the center's forecasts.

  19. Assessment of storm forecast

    DEFF Research Database (Denmark)

    Cutululis, Nicolaos Antonio; Hahmann, Andrea N.; Huus Bjerge, Martin

    When wind speed exceeds a certain value, wind turbines shut-down in order to protect their structure. This leads to sudden wind plants shut down and to new challenges concerning the secure operation of the pan-European electric system with future large scale offshore wind power. This task aims...... stopped, completely or partially, producing due to extreme wind speeds. Wind speed and power measurements from those events are presented and compared to the forecast available at Energinet.dk. The analysis looked at wind speed and wind power forecast. The main conclusion of the analysis is that the wind...... to consider it an EWP) and that the available wind speed forecasts are given as a mean wind speed over a rather large area. At wind power level, the analysis shows that prediction of accurate production levels from a wind farm experiencing EWP is rather poor. This is partially because the power curve...

  20. Financial Analysts’ Forecasts

    DEFF Research Database (Denmark)

    Stæhr, Simone

    . The primary focus is on financial analysts in the task of conducting earnings forecasts while a secondary focus is on investors’ abilities to interpret and make use of these forecasts. Simply put, financial analysts can be seen as information intermediators receiving inputs to their analyses from firm...... in the decision making and the magnitude of these constraints does sometimes vary with personal traits. Therefore, to the extent that financial analysts are subjects to behavioral biases their outputs to the investors are likely to be biased by their interpretation of information. Because investors need accuracy...... management and providing outputs to the investors. Amongst various outputs from the analysts are forecasts of earnings. According to decision theories mostly from the literature in psychology all humans are affected by cognitive constraints to some degree. These constraints may lead to unintentional biases...

  1. Wind power forecast

    Energy Technology Data Exchange (ETDEWEB)

    Pestana, Rui [Rede Electrica Nacional (REN), S.A., Lisboa (Portugal). Dept. Systems and Development System Operator; Trancoso, Ana Rosa; Delgado Domingos, Jose [Univ. Tecnica de Lisboa (Portugal). Seccao de Ambiente e Energia

    2012-07-01

    Accurate wind power forecast are needed to reduce integration costs in the electric grid caused by wind inherent variability. Currently, Portugal has a significant wind power penetration level and consequently the need to have reliable wind power forecasts at different temporal scales, including localized events such as ramps. This paper provides an overview of the methodologies used by REN to forecast wind power at national level, based on statistical and probabilistic combinations of NWP and measured data with the aim of improving accuracy of pure NWP. Results show that significant improvement can be achieved with statistical combination with persistence in the short-term and with probabilistic combination in the medium-term. NWP are also able to detect ramp events with 3 day notice to the operational planning. (orig.)

  2. Intelligent launch and range operations virtual testbed (ILRO-VTB)

    Science.gov (United States)

    Bardina, Jorge; Rajkumar, Thirumalainambi

    2003-09-01

    Intelligent Launch and Range Operations Virtual Test Bed (ILRO-VTB) is a real-time web-based command and control, communication, and intelligent simulation environment of ground-vehicle, launch and range operation activities. ILRO-VTB consists of a variety of simulation models combined with commercial and indigenous software developments (NASA Ames). It creates a hybrid software/hardware environment suitable for testing various integrated control system components of launch and range. The dynamic interactions of the integrated simulated control systems are not well understood. Insight into such systems can only be achieved through simulation/emulation. For that reason, NASA has established a VTB where we can learn the actual control and dynamics of designs for future space programs, including testing and performance evaluation. The current implementation of the VTB simulates the operations of a sub-orbital vehicle of mission, control, ground-vehicle engineering, launch and range operations. The present development of the test bed simulates the operations of Space Shuttle Vehicle (SSV) at NASA Kennedy Space Center. The test bed supports a wide variety of shuttle missions with ancillary modeling capabilities like weather forecasting, lightning tracker, toxic gas dispersion model, debris dispersion model, telemetry, trajectory modeling, ground operations, payload models and etc. To achieve the simulations, all models are linked using Common Object Request Broker Architecture (CORBA). The test bed provides opportunities for government, universities, researchers and industries to do a real time of shuttle launch in cyber space.

  3. Does money matter in inflation forecasting?

    Science.gov (United States)

    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.

  4. Forecasting Turbine Icing Events

    DEFF Research Database (Denmark)

    Davis, Neil; Hahmann, Andrea N.; Clausen, Niels-Erik

    2012-01-01

    In this study, we present a method for forecasting icing events. The method is validated at two European wind farms in with known icing events. The icing model used was developed using current ice accretion methods, and newly developed ablation algorithms. The model is driven by inputs from the WRF...... mesoscale model, allowing for both climatological estimates of icing and short term icing forecasts. The current model was able to detect periods of icing reasonably well at the warmer site. However at the cold climate site, the model was not able to remove ice quickly enough leading to large ice...

  5. Spatial load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Willis, H.L.; Engel, M.V.; Buri, M.J.

    1995-04-01

    The reliability, efficiency, and economy of a power delivery system depend mainly on how well its substations, transmission lines, and distribution feeders are located within the utility service area, and how well their capacities match power needs in their respective localities. Often, utility planners are forced to commit to sites, rights of way, and equipment capacities year in advance. A necessary element of effective expansion planning is a forecast of where and how much demand must be served by the future T and D system. This article reports that a three-stage method forecasts with accuracy and detail, allowing meaningful determination of sties and sizes for future substation, transmission, and distribution facilities.

  6. 3-D visualization of ensemble weather forecasts - Part 2: Forecasting warm conveyor belt situations for aircraft-based field campaigns

    Science.gov (United States)

    Rautenhaus, M.; Grams, C. M.; Schäfler, A.; Westermann, R.

    2015-02-01

    We present the application of interactive 3-D visualization of ensemble weather predictions to forecasting warm conveyor belt situations during aircraft-based atmospheric research campaigns. Motivated by forecast requirements of the T-NAWDEX-Falcon 2012 campaign, a method to predict 3-D probabilities of the spatial occurrence of warm conveyor belts has been developed. Probabilities are derived from Lagrangian particle trajectories computed on the forecast wind fields of the ECMWF ensemble prediction system. Integration of the method into the 3-D ensemble visualization tool Met.3D, introduced in the first part of this study, facilitates interactive visualization of WCB features and derived probabilities in the context of the ECMWF ensemble forecast. We investigate the sensitivity of the method with respect to trajectory seeding and forecast wind field resolution. Furthermore, we propose a visual analysis method to quantitatively analyse the contribution of ensemble members to a probability region and, thus, to assist the forecaster in interpreting the obtained probabilities. A case study, revisiting a forecast case from T-NAWDEX-Falcon, illustrates the practical application of Met.3D and demonstrates the use of 3-D and uncertainty visualization for weather forecasting and for planning flight routes in the medium forecast range (three to seven days before take-off).

  7. Forecasting Housing Approvals in Australia: Do Forecasters Herd?

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Rülke

    2012-01-01

    Price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using more than 6,000 forecasts of housing approvals for Australia, we did not find...

  8. Evaluation and Application of the Weather Research and Forecast Model

    National Research Council Canada - National Science Library

    Passner, Jeffrey E

    2007-01-01

    ... by the U.S. Army Research Laboratory (ARL) to determine how accurate and robust the model is under a variety of meteorological conditions, with an emphasis on fine resolution, short-range forecasts in complex terrain...

  9. Teaching ocean wave forecasting using computer-generated visualization and animation—Part 2: swell forecasting

    Science.gov (United States)

    Whitford, Dennis J.

    2002-05-01

    This paper, the second of a two-part series, introduces undergraduate students to ocean wave forecasting using interactive computer-generated visualization and animation. Verbal descriptions and two-dimensional illustrations are often insufficient for student comprehension. Fortunately, the introduction of computers in the geosciences provides a tool for addressing this problem. Computer-generated visualization and animation, accompanied by oral explanation, have been shown to be a pedagogical improvement to more traditional methods of instruction. Cartographic science and other disciplines using geographical information systems have been especially aggressive in pioneering the use of visualization and animation, whereas oceanography has not. This paper will focus on the teaching of ocean swell wave forecasting, often considered a difficult oceanographic topic due to the mathematics and physics required, as well as its interdependence on time and space. Several MATLAB ® software programs are described and offered to visualize and animate group speed, frequency dispersion, angular dispersion, propagation, and wave height forecasting of deep water ocean swell waves. Teachers may use these interactive visualizations and animations without requiring an extensive background in computer programming.

  10. CDM Convective Forecast Planning guidance

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The CDM Convective Forecast Planning (CCFP) guidance product provides a foreast of en-route aviation convective hazards. The forecasts are updated every 2 hours and...

  11. Seed dispersal in fens

    NARCIS (Netherlands)

    Middleton, Beth; van Diggelen, Rudy; Jensen, Kai

    Question: How does seed dispersal reduce fen isolation and contribute to biodiversity? Location: European and North American fens. Methods: This paper reviews the literature on seed dispersal to fens. Results: Landscape fragmentation may reduce dispersal opportunities thereby isolating fens and

  12. Are demand forecasting techniques applicable to libraries?

    OpenAIRE

    Sridhar, M. S.

    1984-01-01

    Examines the nature and limitations of demand forecasting, discuses plausible methods of forecasting demand for information, suggests some useful hints for demand forecasting and concludes by emphasizing unified approach to demand forecasting.

  13. Forecasting daily patient volumes in the emergency department.

    Science.gov (United States)

    Jones, Spencer S; Thomas, Alun; Evans, R Scott; Welch, Shari J; Haug, Peter J; Snow, Gregory L

    2008-02-01

    Shifts in the supply of and demand for emergency department (ED) resources make the efficient allocation of ED resources increasingly important. Forecasting is a vital activity that guides decision-making in many areas of economic, industrial, and scientific planning, but has gained little traction in the health care industry. There are few studies that explore the use of forecasting methods to predict patient volumes in the ED. The goals of this study are to explore and evaluate the use of several statistical forecasting methods to predict daily ED patient volumes at three diverse hospital EDs and to compare the accuracy of these methods to the accuracy of a previously proposed forecasting method. Daily patient arrivals at three hospital EDs were collected for the period January 1, 2005, through March 31, 2007. The authors evaluated the use of seasonal autoregressive integrated moving average, time series regression, exponential smoothing, and artificial neural network models to forecast daily patient volumes at each facility. Forecasts were made for horizons ranging from 1 to 30 days in advance. The forecast accuracy achieved by the various forecasting methods was compared to the forecast accuracy achieved when using a benchmark forecasting method already available in the emergency medicine literature. All time series methods considered in this analysis provided improved in-sample model goodness of fit. However, post-sample analysis revealed that time series regression models that augment linear regression models by accounting for serial autocorrelation offered only small improvements in terms of post-sample forecast accuracy, relative to multiple linear regression models, while seasonal autoregressive integrated moving average, exponential smoothing, and artificial neural network forecasting models did not provide consistently accurate forecasts of daily ED volumes. This study confirms the widely held belief that daily demand for ED services is characterized by

  14. Taylor dispersion of nanoparticles

    Science.gov (United States)

    Balog, Sandor; Urban, Dominic A.; Milosevic, Ana M.; Crippa, Federica; Rothen-Rutishauser, Barbara; Petri-Fink, Alke

    2017-08-01

    The ability to detect and accurately characterize particles is required by many fields of nanotechnology, including materials science, nanotoxicology, and nanomedicine. Among the most relevant physicochemical properties of nanoparticles, size and the related surface-to-volume ratio are fundamental ones. Taylor dispersion combines three independent phenomena to determine particle size: optical extinction, translational diffusion, and sheer-enhanced dispersion of nanoparticles subjected to a steady laminar flow. The interplay of these defines the apparent size. Considering that particles in fact are never truly uniform nor monodisperse, we rigorously address particle polydispersity and calculate the apparent particle size measured by Taylor dispersion analysis. We conducted case studies addressing aqueous suspensions of model particles and large-scale-produced "industrial" particles of both academic and commercial interest of various core materials and sizes, ranging from 15 to 100 nm. A comparison with particle sizes determined by transmission electron microscopy confirms that our approach is model-independent, non-parametric, and of general validity that provides an accurate account of size polydispersity—independently on the shape of the size distribution and without any assumption required a priori.

  15. Using ensemble forecasting for wind power

    Energy Technology Data Exchange (ETDEWEB)

    Giebel, G.; Landberg, L.; Badger, J. [Risoe National Lab., Roskilde (Denmark); Sattler, K.

    2003-07-01

    /or parameterizations. Two of the large ensembles run this way are available from the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, and from the National Center for Environmental Protection (NCEP) in the US. These are used to calculate the uncertainty of the prediction from the model spread. However, since the model domains are global, it is not certain that this approach will work, due to insufficient spread in Denmark. Additionally, we will try to establish an ensemble of members of DMIs forecasts together with forecasts from the Deutscher Wetterdienst. The project is funded by the Danish PSO funds under the reference no. ORDRE-101295 (FU 2101). (au)

  16. Forecasting of superconducting compounds

    International Nuclear Information System (INIS)

    Savitskii, E.M.; Gribulya, V.G.; Kiseleva, N.N.

    1981-01-01

    In forecasting new superconducting intermetallic compounds of the A15 and Mo 3 Se types most promising from the viewpoint of high critical temperature Tsub(c), high critical magnetic fields Hsub(c), and high critical currents and in estimating their transition temperature it is proposed to apply cybernetic methods of computer learning

  17. Forecast of nuclear energetics

    Energy Technology Data Exchange (ETDEWEB)

    Sikora, W

    1976-01-01

    The forecast concerning the development of nuclear energetics is presented. Some information on economics of nuclear power plants is given. The nuclear fuel reserves are estimated on the background of power resources of the world. The safety and environment protection problems are mentioned.

  18. Climate Forecast System

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Forecast System Home News Organization Web portal to all Federal, state and local government Web resources and services. The NCEP Climate when using the CFS Reanalysis (CFSR) data. Saha, Suranjana, and Coauthors, 2010: The NCEP Climate

  19. Foresight and Forecasts

    DEFF Research Database (Denmark)

    Kilbourn, Kyle; Bay, Marie Brøndum

    In predicting areas of growth, public innovation projects may rely on optimistic visions of technology still in development as a way of ensuring novelty for funding. This paper explores what happens when forecasts of robotic technology meets the practice of sterile supply in a preliminary stage...

  20. Hydrology and flow forecasting

    NARCIS (Netherlands)

    Vrijling, J.K.; Kwadijk, J.; Van Duivendijk, J.; Van Gelder, P.; Pang, H.; Rao, S.Q.; Wang, G.Q.; Huang, X.Q.

    2002-01-01

    We have studied and applied the statistic model (i.e. MMC) and hydrological models to Upper Yellow River. This report introduces the results and some conclusions from the model. The three models, MMC, MWBM and NAM, have be applied in the research area. The forecasted discharge by the three models