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Sample records for subjective forecast derived

  1. Forecasting Long Memory Series Subject to Structural Change

    DEFF Research Database (Denmark)

    Dias, Gustavo Fruet; Papailias, Fotis

    A two-stage forecasting approach for long memory time series is introduced. In the first step we estimate the fractional exponent and, applying the fractional differencing operator, we obtain the underlying weakly dependent series. In the second step, we perform the multi-step ahead forecasts...... change and yields good forecasting results....

  2. Deriving age-specific death rates from life expectancy forecasts

    DEFF Research Database (Denmark)

    Pascariu, Marius; Canudas-Romo, Vladimir

    Predicting the human longevity level in the future by directly forecasting life expectancy others numerous advantages compared with methods based on extrapolation of age-specific death rates. But the reconstruction of accurate life tables starting from a given level of life expectancy at birth...

  3. Estimation efficiency of usage satellite derived and modelled biophysical products for yield forecasting

    Science.gov (United States)

    Kolotii, Andrii; Kussul, Nataliia; Skakun, Sergii; Shelestov, Andrii; Ostapenko, Vadim; Oliinyk, Tamara

    2015-04-01

    Efficient and timely crop monitoring and yield forecasting are important tasks for ensuring of stability and sustainable economic development [1]. As winter crops pay prominent role in agriculture of Ukraine - the main focus of this study is concentrated on winter wheat. In our previous research [2, 3] it was shown that usage of biophysical parameters of crops such as FAPAR (derived from Geoland-2 portal as for SPOT Vegetation data) is far more efficient for crop yield forecasting to NDVI derived from MODIS data - for available data. In our current work efficiency of usage such biophysical parameters as LAI, FAPAR, FCOVER (derived from SPOT Vegetation and PROBA-V data at resolution of 1 km and simulated within WOFOST model) and NDVI product (derived from MODIS) for winter wheat monitoring and yield forecasting is estimated. As the part of crop monitoring workflow (vegetation anomaly detection, vegetation indexes and products analysis) and yield forecasting SPIRITS tool developed by JRC is used. Statistics extraction is done for landcover maps created in SRI within FP-7 SIGMA project. Efficiency of usage satellite based and modelled with WOFOST model biophysical products is estimated. [1] N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "Sensor Web approach to Flood Monitoring and Risk Assessment", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 815-818. [2] F. Kogan, N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk, "Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models," International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 192-203, 2013. [3] Kussul O., Kussul N., Skakun S., Kravchenko O., Shelestov A., Kolotii A, "Assessment of relative efficiency of using MODIS data to winter wheat yield forecasting in Ukraine", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 3235 - 3238.

  4. Applications of Satellite-Derived Ocean Measurements to Tropical Cyclone Intensity Forecasting

    Science.gov (United States)

    2009-09-01

    no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control ...performing routine monitoring, analyses, and forecasts of various measures of ocean heat content and their respective clima - tological anomalies

  5. A data-derived forecast model of surface currents in a semi-enclosed bay (Yeosu Bay, Republic of Korea)

    Science.gov (United States)

    Won, S. I.; Kim, S. Y.

    2016-02-01

    We present a data-derived surface current forecast model based onobservations of high-frequency radar-derived surface currents, local winds, andalong-track altimeter-derived sea surface height anomalies off the southern coastof Korea (Yeosu Bay). The coastal surface circulation in this region is decomposedinto tide-, wind-, pressure gradient-coherent components depending on their forcingmechanisms in a hind cast model. The data-derived forecast model consistsof tidal harmonic analysis, response functions using wind stress and pressuregradients, and autoregressive process for residuals, These basis functions wereconsecutively added, and the performance of the forecast model is evaluated.

  6. Landslides Forecasting Analysis By Displacement Time Series Derived From Satellite INSAR Data: Preliminary Results

    Science.gov (United States)

    Mazzanti, P.; Rocca, A.; Bozzano, F.; Cossu, R.; Floris, M.

    2012-01-01

    In this paper preliminary results of the Cat-1 project ”Landslides forecasting analysis by displacement time series derived from Satellite and Terrestrial InSAR data” are presented. The project focuses on landslide forecasting analysis, based on the application of slope creep models. Displacements data through time, related to landslides strain evolution, are usually derived by classical monitoring methods. Here we propose the use of spaceborne synthetic aperture radar (SAR) differential interferometry (DInSAR) to achieve past displacements information of already collapsed landslides. Persistent Scatterers (PS) InSAR and Small Baseline Subset (SBAS) InSAR are considered and discussed in the perspective of proposed application. Furthermore, a rating method to evaluate the suitability of landslide prediction and investigation by Satellite InSAR technique is presented and tested over two case studies.

  7. Forecasting long memory series subject to structural change: A two-stage approach

    DEFF Research Database (Denmark)

    Papailias, Fotis; Dias, Gustavo Fruet

    2015-01-01

    A two-stage forecasting approach for long memory time series is introduced. In the first step, we estimate the fractional exponent and, by applying the fractional differencing operator, obtain the underlying weakly dependent series. In the second step, we produce multi-step-ahead forecasts...... change and yields good forecasting results....

  8. Probabilistic drought intensification forecasts using temporal patterns of satellite-derived drought indicators

    Science.gov (United States)

    Park, Sumin; Im, Jungho; Park, Seonyeong

    2016-04-01

    A drought occurs when the condition of below-average precipitation in a region continues, resulting in prolonged water deficiency. A drought can last for weeks, months or even years, so can have a great influence on various ecosystems including human society. In order to effectively reduce agricultural and economic damage caused by droughts, drought monitoring and forecasts are crucial. Drought forecast research is typically conducted using in situ observations (or derived indices such as Standardized Precipitation Index (SPI)) and physical models. Recently, satellite remote sensing has been used for short term drought forecasts in combination with physical models. In this research, drought intensification was predicted using satellite-derived drought indices such as Normalized Difference Drought Index (NDDI), Normalized Multi-band Drought Index (NMDI), and Scaled Drought Condition Index (SDCI) generated from Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) products over the Korean Peninsula. Time series of each drought index at the 8 day interval was investigated to identify drought intensification patterns. Drought condition at the previous time step (i.e., 8 days before) and change in drought conditions between two previous time steps (e.g., between 16 days and 8 days before the time step to forecast) Results show that among three drought indices, SDCI provided the best performance to predict drought intensification compared to NDDI and NMDI through qualitative assessment. When quantitatively compared with SPI, SDCI showed a potential to be used for forecasting short term drought intensification. Finally this research provided a SDCI-based equation to predict short term drought intensification optimized over the Korean Peninsula.

  9. Establishing a method of short-term rainfall forecasting based on GNSS-derived PWV and its application.

    Science.gov (United States)

    Yao, Yibin; Shan, Lulu; Zhao, Qingzhi

    2017-09-29

    Global Navigation Satellite System (GNSS) can effectively retrieve precipitable water vapor (PWV) with high precision and high-temporal resolution. GNSS-derived PWV can be used to reflect water vapor variation in the process of strong convection weather. By studying the relationship between time-varying PWV and rainfall, it can be found that PWV contents increase sharply before raining. Therefore, a short-term rainfall forecasting method is proposed based on GNSS-derived PWV. Then the method is validated using hourly GNSS-PWV data from Zhejiang Continuously Operating Reference Station (CORS) network of the period 1 September 2014 to 31 August 2015 and its corresponding hourly rainfall information. The results show that the forecasted correct rate can reach about 80%, while the false alarm rate is about 66%. Compared with results of the previous studies, the correct rate is improved by about 7%, and the false alarm rate is comparable. The method is also applied to other three actual rainfall events of different regions, different durations, and different types. The results show that the method has good applicability and high accuracy, which can be used for rainfall forecasting, and in the future study, it can be assimilated with traditional weather forecasting techniques to improve the forecasted accuracy.

  10. Use of observational and model-derived fields and regime model output statistics in mesoscale forecasting

    Science.gov (United States)

    Forbes, G. S.; Pielke, R. A.

    1985-01-01

    Various empirical and statistical weather-forecasting studies which utilize stratification by weather regime are described. Objective classification was used to determine weather regime in some studies. In other cases the weather pattern was determined on the basis of a parameter representing the physical and dynamical processes relevant to the anticipated mesoscale phenomena, such as low level moisture convergence and convective precipitation, or the Froude number and the occurrence of cold-air damming. For mesoscale phenomena already in existence, new forecasting techniques were developed. The use of cloud models in operational forecasting is discussed. Models to calculate the spatial scales of forcings and resultant response for mesoscale systems are presented. The use of these models to represent the climatologically most prevalent systems, and to perform case-by-case simulations is reviewed. Operational implementation of mesoscale data into weather forecasts, using both actual simulation output and method-output statistics is discussed.

  11. Objectively determined model derived parameters associated with forecasts of tropical cyclone formation

    OpenAIRE

    Cowan, Christy G.

    2006-01-01

    During the 2005 North Atlantic hurricane season, an objective tropical cyclone vortex identification and tracking technique was applied to analyzed and forecast fields of three global operational numerical models- the National Centers for Environmental Prediction Global Forecast System (GFS), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the United Kingdom Meteorological Office model (UKMET). For the purpose of evaluating each model's performance with respect to fore...

  12. Daily hay fever forecast in the Netherlands. Radio broadcasting of the expected influence of the weather or subjective complaints of hay fever sufferers.

    Science.gov (United States)

    Spieksma, F T

    1980-10-01

    The literature on local pollen counts and their significance for hay fever is reviewed and a system for forecasting hay fever is described. Such forecasts have been broadcast by radio in The Netherlands since 1977. The hay fever forecast takes the form of a prognosis (in terms of three grades) of the influence of the expected whether situation on tomorrow's course of the subjective complaints of hay fever sufferers. It is not a forecast of the pollen count. When the subjective complaints of about 150 hay fever patients were used as reference for evaluation, the forecasts proved to have been correct in 72, 85, and 88% of the cases in 1977, 1978, and 1979, respectively. The practical usefulness and the limitations of the system are briefly discussed, with emphasis on the principle that not the local pollen count but the weather should be taken as the main determinative factor for the expected subjective experiences in a group of hay fever sufferers in a certain region.

  13. Understanding the influence of assimilating satellite-derived observations on mesoscale analyses and forecasts of tropical cyclone track and structure

    Science.gov (United States)

    Wu, Ting-Chi

    This dissertation research explores the influence of assimilating satellite-derived observations on mesoscale numerical analyses and forecasts of tropical cyclones (TC). The ultimate goal is to provide more accurate mesoscale analyses of TC and its surrounding environment for superior TC track and intensity forecasts. High spatial and temporal resolution satellite-derived observations are prepared for two TC cases, Typhoon Sinlaku and Hurricane Ike (both 2008). The Advanced Research version of the Weather and Research Forecasting Model (ARW-WRF) is employed and data is assimilated using the Ensemble Adjustment Kalman Filter (EAKF) implemented in the Data Assimilation Research Testbed. In the first part of this research, the influence of assimilating enhanced atmospheric motion vectors (AMVs) derived from geostationary satellites is examined by comparing three parallel WRF/EnKF experiments. The control experiment assimilates the same AMV dataset assimilated in NCEP operational analysis along with conventional observations from radiosondes, aircraft, and advisory TC position data. During Sinlaku and Ike, the Cooperative Institute for Meteorological Satellite Studies (CIMSS) generates hourly AMVs along with Rapid-Scan (RS) AMVs when the satellite RS mode is activated. With an order of magnitude more AMV data assimilated, the assimilation of hourly CIMSS AMV dataset exhibit superior initial TC position, intensity and structure estimates to the control analyses and the subsequent short-range forecasts. When RS AMVs are processed and assimilated, the addition of RS AMVs offers additional modification to the TC and its environment and leads to Sinlaku's recurvature toward Japan, albeit prematurely. The results demonstrate the promise of assimilating enhanced AMV data into regional TC models. The second part of this research continues the work in the first part and further explores the influence of assimilating enhanced AMV datasets by conducting parallel data-denial WRF

  14. Accurate Forecasting of the Satellite-Derived Seasonal Caspian Sea Level Anomaly Using Polynomial Interpolation and Holt-Winters Exponential Smoothing

    Directory of Open Access Journals (Sweden)

    Moslem Imani

    2013-01-01

    Full Text Available Polynomial interpolation and Holt-Winters exponential smoothing (HWES are used to analyze and forecast Caspian Sea level anomalies derived from 15-year Topex/Poseidon (T/P and Jason-1 (J-1 altimetry covering 1993 to 2008. Because along-track altimetric products may contain temporal and spatial data gaps, a least squares polynomial interpolation is performed to fill the gaps of along-track sea surface heights used. The modeling results of a 3-year forecasting time span (2005 - 2008 derived using HWES agree well with the observed time series with a correlation coefficient of 0.86. Finally, the 3-year forecasted Caspian Sea level anomalies are compared with those obtained using an artificial neural network method with reasonable agreement found.

  15. Brain-derived neurotrophic factor in human subjects with function-altering melanocortin-4 receptor variants

    Science.gov (United States)

    In rodents, hypothalamic brain-derived neurotrophic factor (BDNF) expression appears to be regulated by melanocortin-4 receptor (MC4R) activity. The impact of MC4R genetic variation on circulating BDNF in humans is unknown. The objective of this study is to compare BDNF concentrations of subjects wi...

  16. Circulating leukocyte-derived microparticles predict subclinical atherosclerosis burden in asymptomatic subjects.

    Science.gov (United States)

    Chironi, Gilles; Simon, Alain; Hugel, Bénédicte; Del Pino, Muriel; Gariepy, Jérôme; Freyssinet, Jean-Marie; Tedgui, Alain

    2006-12-01

    To clarify circulating microparticles (MP) relationships with preclinical atherosclerosis. In 216 subjects without cardiovascular disease, we assessed: (1) annexin V-positive, platelet-derived, endothelium-derived and leukocyte-derived circulating MP by capture on annexin V, anti-GPIb, anti-CD105, and anti-CD11a antibody-coated wells, respectively; (2) Framingham risk, metabolic syndrome, and low-grade inflammation by risk factors measurement including hsCRP; and (3) subclinical atherosclerosis by ultrasound examination of carotid, abdominal aorta, and femoral arteries. Number of sites with plaque ranged from 0 to 3 and plaque burden was classified into 0 to 1 or 2 to 3 sites disease. Leukocyte-derived MP level was higher in the presence than in the absence of moderate to high Framingham risk (Pmarkers or atherosclerosis. Leukocyte-derived MP, identified by affinity for CD11a, are increased in subjects with ultrasound evidence of subclinical atherosclerosis, unveiling new directions for atherosclerosis research.

  17. Using radar-derived parameters to forecast lightning cessation for nonisolated storms

    Science.gov (United States)

    Davey, Matthew J.; Fuelberg, Henry E.

    2017-03-01

    Lightning impacts operations at the Kennedy Space Center (KSC) and other outdoor venues leading to injuries, inconvenience, and detrimental economic impacts. This research focuses on cases of "nonisolated" lightning which we define as one cell whose flashes have ceased although it is still embedded in weak composite reflectivity (Z ≥ 15 dBZ) with another cell that is still producing flashes. The objective is to determine if any radar-derived parameters provide useful information about the occurrence of lightning cessation in remnant storms. The data set consists of 50 warm season (May-September) nonisolated storms near KSC during 2013. The research utilizes the National Lightning Detection Network, the second generation Lightning Detection and Ranging network, and polarized radar data. These data are merged and analyzed using the Warning Decision Support System-Integrated Information at 1 min intervals. Our approach only considers 62 parameters, most of which are related to the noninductive charging mechanism. They included the presence of graupel at various thermal altitudes, maximum reflectivity of the decaying storm at thermal altitudes, maximum connecting composite reflectivity between the decaying cell and active cell, minutes since the previous flash, and several others. Results showed that none of the parameters reliably indicated lightning cessation for even our restrictive definition of nonisolated storms. Additional research is needed before cessation can be determined operationally with the high degree of accuracy required for safety.

  18. Improving Landslide Forecasting Using ASCAT-Derived Soil Moisture Data: A Case Study of the Torgiovannetto Landslide in Central Italy

    Directory of Open Access Journals (Sweden)

    Wolfgang Wagner

    2012-05-01

    Full Text Available Predicting the spatial and temporal occurrence of rainfall triggered landslides represents an important scientific and operational issue due to the high threat that they pose to human life and property. This study investigates the relationship between rainfall, soil moisture conditions and landslide movement by using recorded movements of a rock slope located in central Italy, the Torgiovannetto landslide. This landslide is a very large rock slide, threatening county and state roads. Data acquired by a network of extensometers and a meteorological station clearly indicate that the movements of the unstable wedge, first detected in 2003, are still proceeding and the alternate phases of quiescence and reactivation are associated with rainfall patterns. By using a multiple linear regression approach, the opening of the tension cracks (as recorded by the extensometers as a function of rainfall and soil moisture conditions prior the occurrence of rainfall, are predicted for the period 2007–2009. Specifically, soil moisture indicators are obtained through the Soil Water Index, SWI, a product derived by the Advanced SCATterometer (ASCAT on board the MetOp (Meteorological Operational satellite and by an Antecedent Precipitation Index, API. Results indicate that the regression performance (in terms of correlation coefficient, r significantly enhances if an indicator of the soil moisture conditions is included. Specifically, r is equal to 0.40 when only rainfall is used as a predictor variable and increases to r = 0.68 and r = 0.85 if the API and the SWI are used respectively. Therefore, the coarse spatial resolution (25 km of satellite data notwithstanding, the ASCAT SWI is found to be very useful for the prediction of landslide movements on a local scale. These findings, although valid for a specific area, present new opportunities for the effective use of satellite-derived soil moisture estimates to improve landslide forecasting.

  19. Subjectivity

    Directory of Open Access Journals (Sweden)

    Jesús Vega Encabo

    2015-11-01

    Full Text Available In this paper, I claim that subjectivity is a way of being that is constituted through a set of practices in which the self is subject to the dangers of fictionalizing and plotting her life and self-image. I examine some ways of becoming subject through narratives and through theatrical performance before others. Through these practices, a real and active subjectivity is revealed, capable of self-knowledge and self-transformation. 

  20. Medium-range fire weather forecasts

    Science.gov (United States)

    J.O. Roads; K. Ueyoshi; S.C. Chen; J. Alpert; F. Fujioka

    1991-01-01

    The forecast skill of theNational Meteorological Center's medium range forecast (MRF) numerical forecasts of fire weather variables is assessed for the period June 1,1988 to May 31,1990. Near-surface virtual temperature, relative humidity, wind speed and a derived fire weather index (FWI) are forecast well by the MRF model. However, forecast relative humidity has...

  1. The accountability imperative for quantifying the uncertainty of emission forecasts: evidence from Mexico

    DEFF Research Database (Denmark)

    Puig, Daniel; Morales-Nápoles, Oswaldo; Bakhtiari, Fatemeh

    2017-01-01

    be agreed upon, to ensure that governmental forecasts meet certain minimum transparency and quality standards, and (ii) governments should be held accountable for the appropriateness of the forecasting approach applied to prepare governmental forecasts, especially when those forecasts are used to derive...... climate change mitigation targets. POLICY INSIGHTSNo minimum transparency and quality standards exist to guide the development of GHG emission scenario forecasts, not even when these forecasts are used to set national climate change mitigation targets.No accountability mechanisms appear to be in place...... are subject, thus increasing the validity of the target.Setting up minimum transparency and quality standards, and holding governments accountable for their choice of forecasting methods could lead to more robust emission reduction targets nationally and, by extension, internationally....

  2. Temporal and spatial variability of wind resources in the United States as derived from the Climate Forecast System Reanalysis

    Science.gov (United States)

    Lejiang Yu; Shiyuan Zhong; Xindi Bian; Warren E. Heilman

    2015-01-01

    This study examines the spatial and temporal variability of wind speed at 80m above ground (the average hub height of most modern wind turbines) in the contiguous United States using Climate Forecast System Reanalysis (CFSR) data from 1979 to 2011. The mean 80-m wind exhibits strong seasonality and large spatial variability, with higher (lower) wind speeds in the...

  3. Seasonal Characterization of Solar Radiation Estimates Obtained from a MSG-SEVIRI-Derived Dataset and a RAMS-Based Operational Forecasting System over the Western Mediterranean Coast

    Directory of Open Access Journals (Sweden)

    Igor Gómez

    2016-01-01

    Full Text Available Solar radiation is a key factor in the Earth’s energy balance and it is used as a crucial input parameter in many disciplines such as ecology, agriculture, solar energy and hydrology. Thus, accurate information of the global downward surface shortwave flux integration into the grid is of significant importance. From the different strategies used for grid integration of the surface solar radiation estimates, satellite-derived and numerical weather prediction forecasts are two interesting alternatives. In the current work, we present a comprehensive evaluation of the global downward solar radiation forecasts provided by the Regional Atmospheric Modeling System (RAMS and the Downwelling Surface Shortwave Flux (DSSF product, derived from the Meteosat Second Generation (MSG Spinning Enhanced Visible and Infrared Imager (SEVIRI. Both solar radiation estimates are compared to thirteen ground-based weather station measurements for the winter 2010–2011 and the summer 2011 seasons. For these periods, the most recent versions of RAMS (4.4 and 6.0 were running in parallel within the real-time weather forecasting system implemented over the Valencia Region. The solar radiation performance and accuracy are evaluated for these datasets segmented into two atmospheric conditions (clear and cloudy skies and two terrain classes (flat and hilly. DSSF shows a very good agreement over the study area. Statistical daily evaluations show that corresponding errors vary between seasons, with absolute bias ranging from −30 to 40 W·m−2, absolute root mean square errors (RMSE from 25 to 60 W·m−2, relative bias ranging from −11% to 7% and relative RMSE from 7% to 22%, depending on the sky condition and the terrain location as well, thus reproducing the observations more faithfully than RAMS, which produces higher errors in comparison to the measurements. In this regard, statistical daily evaluations show absolute bias values varying from −50 to 160 W·m−2

  4. Genetic variety of sinkholes and their reconaissance and classification for the derivation of hazards and to forecast of collapses

    Science.gov (United States)

    Mucke, D.

    2012-04-01

    Genetic variety of sinkholes and their reconnaissance and classification for the derivation of hazards and to forecast of collapses Dieter Mucke GEOMONTAN Gesellschaft für Geologie und Bergbau mbH&Co.KG, Muldentalstrasse 56, 09603 Rothenfurth, Saxony/Germany The term "sinkhole" covers a lot of depressions on the earth's surface, caused by very different geological processes and anthropogenic activities. The speed of the origin of the depressions is different and leads to different hazards. The forecast look for hazards and the introduction of preventive measures gets safer if type and cause of the depressions are known of. First aim of the lecture is the classification of sinkholes in different types. Geogenic depressions develope in karst landscapes as well as in plain areas of detrital sediments on soluble rocks. The depressions are in karst landscapes localized directly in the soluble rocks like limestone or sulphate rocks (anhydrite, gypsum). It results there for solution dolines and collapse dolines in these rocks themselves.. In other cases the soluble rocks often are in large depth under overlaying claystones, siltstones, sandstones or clays, silts, sands. A cave deeply is formed under the earth's surface and when a roof failure happens, the overburden sinks after. A depression of caldera shape with abrupt slopes suddenly forms in the non-karst rock at the surface. Such erdfall-collapses in Triassic claystones develop flatter walls in the course of the time. In German such depressions are called "Erdfall" to distinguish them of dolines. Because in English the term "earth fall" has an other meaning, I will further call such depressions "erdfall-collaps". The solution of limestones and sulphate rocks results with the formation of caves and following emergence of collapse dolines and erdfall-collapses. The underground dissolution (subrosion) of rock salt is as opposed to without formation of caves. It leads to a slow lowering of the earth's surface in flat

  5. Forecast of reliability for mechanical components subjected to wearing; Pronostico de la fiabilidad de componentes mecanicos sometidos a desgaste

    Energy Technology Data Exchange (ETDEWEB)

    Angulo-Zevallos, J.; Castellote-Varona, C.; Alanbari, M.

    2010-07-01

    Generally, improving quality and price of products, obtaining a complete customer satisfaction and achieving excellence in all the processes are some of the challenges currently set up by every company. To do this, knowing frequently the reliability of some component is necessary. To achieve this goal, a research, that contributes with clear ideas and offers a methodology for the assessment of the parameters involved in the reliability calculation, becomes necessary. A parameter closely related to this concept is the probability of product failure depending on the operating time. It is known that mechanical components fail by: creep, fatigue, wear, corrosion, etc. This article proposes a methodology for finding the reliability of a component subject to wear, such as brake pads, grinding wheels, brake linings of clutch discs, etc. (Author)

  6. Comparison between nutritional risk tools and parameters derived from bioelectrical impedance analysis with subjective global assessment.

    Science.gov (United States)

    Meireles, Marion Schneider; Wazlawik, Elisabeth; Bastos, João Luiz; Garcia, Monique Ferreira

    2012-10-01

    Nutritional risk and malnutrition are highly prevalent among hospitalized patients. As a result, several methods have been developed to produce an adequate nutritional diagnosis. We aimed to assess the relationship between nutritional risk tools and parameters derived from bioelectrical impedance analysis with a Subjective Global Assessment (SGA). A cross-sectional study was conducted from April to September 2010. The study included 124 patients admitted to the Surgical Clinic I, University Hospital, Federal University of Santa Catarina, Florianópolis, Brazil, to undergo elective surgery. We utilized SGA and Nutritional Risk Screening 2002 (NRS 2002), Nutritional Risk Index (NRI), Fat-Free Mass Index (FFMI), Fat Mass Index (FMI), body cell mass as a percentage of the total weight (%BCM), and standardized phase angle (SPA). The agreement was tested by κ coefficient, while bivariate associations were tested by Mann-Whitney U test. Prevalence of nutritional risk by NRS 2002 and NRI or malnutrition by SGA, FFMI, FMI, %BCM, and SPA was 19.3%, 69.5%, 35.5%, 12.9%, 8.1%, 46.8%, and 4.8%, respectively. The best agreement was between SGA and NRS 2002 (κ=.490), possibly because they constitute similar instruments. Patients identified as malnourished by SGA (B+C) showed considerably lower values of FFMI, FMI, BCM, and SPA. The results suggest that the NRS 2002 and parameters derived from bioelectrical impedance analysis identify patients with impaired nutritional status. Copyright © 2012 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

  7. 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.

  8. Wind Farm Power Forecasting

    OpenAIRE

    Haouas, Nabiha; Bertrand, Pierre R.

    2013-01-01

    Forecasting annual wind power production is useful for the energy industry. Until recently, attention has only been paid to the mean annual wind power energy and statistical uncertainties on this forecasting. Recently, Bensoussan et al. (2012) have pointed that the annual wind power produced by one wind turbine is a Gaussian random variable under a reasonable set of assumptions. Moreover, they can derive both mean and quantiles of annual wind power produced by one wind ...

  9. 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

  10. Short-term cloudiness forecasting for solar energy purposes in Greece, based on satellite-derived information

    Science.gov (United States)

    Nikitidou, E.; Zagouras, A.; Salamalikis, V.; Kazantzidis, A.

    2017-10-01

    A novel method for the short-term (15-240 min) forecasting of cloudiness in Greece is presented by taking into account that this is the main atmospheric factor responsible for the spatial and temporal distribution of surface solar irradiance. Images from the Spinning Enhanced Visible and Infrared Imager onboard the Meteosat Second Generation satellite, for a 3-year time period and with high spatial and temporal resolution (0.05°, 15 min), were processed to retrieve the cloud clearness index (CCI) and used for the training and testing of an artificial neural network (ANN). The estimated and the measured values of CCI are in good agreement and emphasis is given to the spatial distribution of the seasonal errors. The ANN was trained according to pre-classified areas that present similar cloud characteristics and could provide estimations of surface solar irradiance in synergy with models that calculate surface irradiance under clear skies.

  11. Hydrological Forecast Certainty Using Historical Forecast Skill Curves - For A Forecast-Informed Reservoir Operation

    Science.gov (United States)

    Sellars, S. L.; Reynolds, D.; Kawzenuk, B.; Ralph, F. M.

    2016-12-01

    A novel forecast verification ``skill curve" method and associated forecast certainty calculation is presented and applied to historical, daily hydrological streamflow operational forecasts used to manage and operate the Coyote Valley Dam (COY), which forms Lake Mendocino in the Russian River basin in Northern California from 2005 to 2015. The presented skill curves represent the historical forecast skill as a function of forecast lead time skill (in forecast hours) and forecast event values (volumetric inflow in acre-feet) for a range of inflow events. We define skill as the lead time when a forecast event value is more likely to be correct than incorrect by calculating the lead time where the Critical Success Index (CSI) value is equals to .5. We explore other CSI values ranging from .1 to .9. Using the skill curve, we define the Actionable Forecast Certainty (AFC) as a measure of real-time forecast certainty as it is compared to the historical skill derived by the skill curve method. The AFC is quantifiable measure of certainty based on the skill of historical 24 and 72 forecast event volume forecast skill, which indicates the degree of certanty on a range from [1,-1] where particular forecast value and lead time, where 1 being highly certain and -1 having least amount of certainty. In addition, we explore the new skill curve and AFC in developing criteria and applicability for Forecast-Informed Reservoir Operations or FIRO, which is a proposed management strategy that uses data from watershed monitoring and modern weather and water forecasting to help water managers selectively retain or release water from reservoirs in a manner that reflects current and forecasted conditions. Both methods are applied to a case study for a Lake Mendocino major inflow event occurring in December, 2012 and results are presented.

  12. Different response to hypoxia of adipose-derived multipotent cells from obese subjects with and without metabolic syndrome

    Science.gov (United States)

    Moreno-Indias, Isabel; Coín-Aragüez, Leticia; Lhamyani, Said; Alcaide Torres, Juan; Fernández-Veledo, Sonia; Vendrell, Joan; Camargo, Antonio; El Bekay, Rajaa; Tinahones, Francisco José

    2017-01-01

    Background/Objectives Multiple studies suggest that hypoxia, together with inflammation, could be one of the phenomena involved in the onset and progression of obesity-related insulin resistance. In addition, dysfunction of adipose tissue in obese subjects with metabolic syndrome is associated with decreased angiogenesis. However, some subjects with a high body mass index do not develop metabolic abnormalities associated with obesity. The aim of the current study was to examine the neovascular properties of visceral adipose tissue-derived multipotent mesenchymal cells subjected to hypoxia (hypox-visASCs) from normal-weight subjects (Nw) and obese patients with metabolic syndrome (MS) and without metabolic syndrome (NonMS). Methods This was a 2-year study to enroll subjects who underwent bariatric surgery or cholecystectomy. Eight patients who underwent either bariatric surgery or cholecystectomy (27 patients) participated in the study. Visceral adipose tissue samples from Nw, MS and NonMS subjects were processed by enzymatic digestion. VisASCs cultured under hypoxic conditions were characterized by tubule formation assay, ELISA, flow cytometry, migration rate, and qRT-PCR, and the effects of visASCs-conditioned medium on survival and endothelial cell tubule formation were evaluated. Results Hypox-visASCs from NonMS subjects showed a greater capacity for tubule formation than hypox-visASCs from Nw and MS subjects. The lower percentage of CD140b+/CD44+ and CD140b+/CD184+ cells observed in hypox-visASCs from NonMS subjects compared to MS subjects was accompanied not only by a lower migration rate from the chemotactic effects of stromal cell derived factor 1α, but also by lower levels of NOX5 mRNA expression. While the levels of monocyte chemoattractant protein 1 mRNA expressed by hypox-visASCs correlated positively with the body mass index and waist circumference of the subjects, the concentration of vascular endothelial growth factor present in hypox

  13. Different response to hypoxia of adipose-derived multipotent cells from obese subjects with and without metabolic syndrome.

    Directory of Open Access Journals (Sweden)

    Wilfredo Oliva-Olivera

    Full Text Available Multiple studies suggest that hypoxia, together with inflammation, could be one of the phenomena involved in the onset and progression of obesity-related insulin resistance. In addition, dysfunction of adipose tissue in obese subjects with metabolic syndrome is associated with decreased angiogenesis. However, some subjects with a high body mass index do not develop metabolic abnormalities associated with obesity. The aim of the current study was to examine the neovascular properties of visceral adipose tissue-derived multipotent mesenchymal cells subjected to hypoxia (hypox-visASCs from normal-weight subjects (Nw and obese patients with metabolic syndrome (MS and without metabolic syndrome (NonMS.This was a 2-year study to enroll subjects who underwent bariatric surgery or cholecystectomy. Eight patients who underwent either bariatric surgery or cholecystectomy (27 patients participated in the study. Visceral adipose tissue samples from Nw, MS and NonMS subjects were processed by enzymatic digestion. VisASCs cultured under hypoxic conditions were characterized by tubule formation assay, ELISA, flow cytometry, migration rate, and qRT-PCR, and the effects of visASCs-conditioned medium on survival and endothelial cell tubule formation were evaluated.Hypox-visASCs from NonMS subjects showed a greater capacity for tubule formation than hypox-visASCs from Nw and MS subjects. The lower percentage of CD140b+/CD44+ and CD140b+/CD184+ cells observed in hypox-visASCs from NonMS subjects compared to MS subjects was accompanied not only by a lower migration rate from the chemotactic effects of stromal cell derived factor 1α, but also by lower levels of NOX5 mRNA expression. While the levels of monocyte chemoattractant protein 1 mRNA expressed by hypox-visASCs correlated positively with the body mass index and waist circumference of the subjects, the concentration of vascular endothelial growth factor present in hypox-visASC-conditioned culture medium

  14. Forecasting Sales

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans)

    2009-01-01

    textabstractThis chapter deals with forecasting sales (in units or money), where an explicit distinction is made between sales of durable goods (computers, cars, books) and sales of utilitarian products (SKU level in supermarkets). Invariably, sales forecasting amounts to a combination of

  15. Subjectivities, the political and the politics: derives on a theoretical discussion

    Directory of Open Access Journals (Sweden)

    José Ignacio Allevi

    2015-11-01

    Full Text Available In the paper that follows, I propose myself to tense a series of theoretical discussions on what each one of them understand by subjetification processes, in a social and political key. With that purpose in mind, I organize the writing into two sections. The first one will discuss the processes of subjective setting-up from the perspective of Slavoj Zizek taking his dialogue with the lacanian psychoanalysis, thinking on its approaches on the renewed spot of the subject in the postestructuralist frame. In a second moment, I will continue with the proposals of Judith Butler and Ernesto Laclau, taking Jacques Rancière as a counterpoint with the aim of resituate the point on the subjetification process as a political commitment. The main goal I am pursuing with this critique relies on reflecting, on the one hand, on the strictly political character that some authors give to the subjetive constitution process itself, while, on the other hand, I am interested on the possible divergences on those that examine the process in a mayor and more complex frame, related to the constitution of the social. The starting point of this reflections is found on the differences that a myriad of authors compromised with a posfundacional view have proposed between the political and the politics, and on the spot of the subject on that arena.

  16. Neovascular deterioration, impaired NADPH oxidase and inflammatory cytokine expression in adipose-derived multipotent cells from subjects with metabolic syndrome.

    Science.gov (United States)

    Oliva-Olivera, Wilfredo; Lhamyani, Said; Coín-Aragüez, Leticia; Castellano-Castillo, Daniel; Alcaide-Torres, Juan; Yubero-Serrano, Elena María; El Bekay, Rajaa; Tinahones, Francisco José

    2017-06-01

    Expansion of adipose tissue depends on the growth of its vascular network and it has been shown that adipose tissue dysfunction in obese subjects with the metabolic syndrome is associated with decreased angiogenesis. However, some subjects with a high body mass index do not develop metabolic abnormalities associated with obesity. In this study we examined the neovascular properties, expression levels of proteins involved in cellular redox balance and inflammatory cytokines in adipose-derived multipotent mesenchymal cells (ASCs) of subjects with different metabolic profiles. We applied cell culture, flow cytometry, RT-qPCR and ELISA techniques to characterize the ASCs isolated from paired biopsies of visceral (visASCs) and subcutaneous (subASCs) adipose tissue from 39 subjects grouped into normal weight (Nw), obese without metabolic syndrome (NonMS) and with metabolic syndrome (MS). VisASCs and subASCs from MS subjects showed a decrease in tubules formation capacity compared to ASCs from NonMS subjects as well as changes in the expression levels of proteins involved in cell redox balance and secretion levels of proteins linked to the senescence-associated secretory phenotype. Deterioration in the neovascular properties of subASCs from the MS subjects was also evident in the decreased levels of VEGF secretion during adipogenesis and in the effects of the conditioned medium on endothelial cell tubule formation. Our findings suggest a redox imbalance status in ASCs from subjects with metabolic syndrome and decreased their neovascular function that probably contributes to the vascular insufficiency of adipose depots. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Fishing Forecasts

    Science.gov (United States)

    1988-01-01

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

  18. Recapitulation of Clinical Individual Susceptibility to Drug-Induced QT Prolongation in Healthy Subjects Using iPSC-Derived Cardiomyocytes

    Directory of Open Access Journals (Sweden)

    Tadahiro Shinozawa

    2017-02-01

    Full Text Available To predict drug-induced serious adverse events (SAE in clinical trials, a model using a panel of cells derived from human induced pluripotent stem cells (hiPSCs of individuals with different susceptibilities could facilitate major advancements in translational research in terms of safety and pharmaco-economics. However, it is unclear whether hiPSC-derived cells can recapitulate interindividual differences in drug-induced SAE susceptibility in populations not having genetic disorders such as healthy subjects. Here, we evaluated individual differences in SAE susceptibility based on an in vitro model using hiPSC-derived cardiomyocytes (hiPSC-CMs as a pilot study. hiPSCs were generated from blood samples of ten healthy volunteers with different susceptibilities to moxifloxacin (Mox-induced QT prolongation. Different Mox-induced field potential duration (FPD prolongation values were observed in the hiPSC-CMs from each individual. Interestingly, the QT interval was significantly positively correlated with FPD at clinically relevant concentrations (r > 0.66 in multiple analyses including concentration-QT analysis. Genomic analysis showed no interindividual significant differences in known target-binding sites for Mox and other drugs such as the hERG channel subunit, and baseline QT ranges were normal. The results suggest that hiPSC-CMs from healthy subjects recapitulate susceptibility to Mox-induced QT prolongation and provide proof of concept for in vitro preclinical trials.

  19. Strategic Forecasting

    DEFF Research Database (Denmark)

    Duus, Henrik Johannsen

    2016-01-01

    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......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...

  20. 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...

  1. Candida virulence and ethanol-derived acetaldehyde production in oral cancer and non-cancer subjects.

    Science.gov (United States)

    Alnuaimi, A D; Ramdzan, A N; Wiesenfeld, D; O'Brien-Simpson, N M; Kolev, S D; Reynolds, E C; McCullough, M J

    2016-11-01

    To compare biofilm-forming ability, hydrolytic enzymes and ethanol-derived acetaldehyde production of oral Candida isolated from the patients with oral cancer and matched non-oral cancer. Fungal biofilms were grown in RPMI-1640 medium, and biofilm mass and biofilm activity were assessed using crystal violet staining and XTT salt reduction assays, respectively. Phospholipase, proteinase, and esterase production were measured using agar plate method, while fungal acetaldehyde production was assessed via gas chromatography. Candida isolated from patients with oral cancer demonstrated significantly higher biofilm mass (P = 0.031), biofilm metabolic activity (P Candida were more prevalent in patients with oral cancer than non-oral cancer (P = 0.01). In univariate regression analysis, high biofilm mass (P = 0.03) and biofilm metabolic activity (P Candida isolates to form biofilms, to produce hydrolytic enzymes, and to metabolize alcohol to acetaldehyde with their ability to promote oral cancer development. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  2. Nutritional Assessment Score: A new tool derived from Subjective Global Assessment for hospitalized adults.

    Science.gov (United States)

    da Silva Fink, Jaqueline; de Mello, Elza Daniel; Beghetto, Mariur Gomes; Luft, Vivian Cristine; de Jezus Castro, Stela Maris; de Mello, Paula Daniel

    2017-02-24

    There is no method to be used as a reference standard for nutritional assessment. This study aims to develop and verify the performance of a new tool, based on the Item Response Theory (IRT), from the Subjective Global Assessment (SGA) questionnaire, in hospitalized adult patients. Retrospective cohort study, composed by secondary database, formed by patients included from October 2005 to June 2006. The new tool presented was developed through the usage of cumulative models from the IRT. Out of 1503 evaluated patients, 2/3 were randomly selected to the development sample of the new tool and 1/3 to the performance verification sample. After item adjustments, the "Nutritional Assessment Score" (NAS) was proposed, with reduced number of questions, and, in comparison to SGA, less polytomic items. NAS demonstrates association to variables that are clinically relevant (hospital mortality, long hospital stay, serum albumin and body mass index) and has shown itself to be more precise to patients with the worst degrees of nutritional status. Results point to the validation of the NAS in detecting, accurately, the nutritional status of hospitalized patients. Copyright © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

  3. User-Centric Key Entropy: Study of Biometric Key Derivation Subject to Spoofing Attacks

    Directory of Open Access Journals (Sweden)

    Lavinia Mihaela Dinca

    2017-02-01

    Full Text Available Biometric data can be used as input for PKI key pair generation. The concept of not saving the private key is very appealing, but the implementation of such a system shouldn’t be rushed because it might prove less secure then current PKI infrastructure. One biometric characteristic can be easily spoofed, so it was believed that multi-modal biometrics would offer more security, because spoofing two or more biometrics would be very hard. This notion, of increased security of multi-modal biometric systems, was disproved for authentication and matching, studies showing that not only multi-modal biometric systems are not more secure, but they introduce additional vulnerabilities. This paper is a study on the implications of spoofing biometric data for retrieving the derived key. We demonstrate that spoofed biometrics can yield the same key, which in turn will lead an attacker to obtain the private key. A practical implementation is proposed using fingerprint and iris as biometrics and the fuzzy extractor for biometric key extraction. Our experiments show what happens when the biometric data is spoofed for both uni-modal systems and multi-modal. In case of multi-modal system tests were performed when spoofing one biometric or both. We provide detailed analysis of every scenario in regard to successful tests and overall key entropy. Our paper defines a biometric PKI scenario and an in depth security analysis for it. The analysis can be viewed as a blueprint for implementations of future similar systems, because it highlights the main security vulnerabilities for bioPKI. The analysis is not constrained to the biometric part of the system, but covers CA security, sensor security, communication interception, RSA encryption vulnerabilities regarding key entropy, and much more.

  4. Skin-derived precursors from human subjects with Type 2 diabetes yield dysfunctional vascular smooth muscle cells.

    Science.gov (United States)

    Steinbach, Sarah K; Yau, Terrence M; Ouzounian, Maral; Abdel-Qadir, Husam; Chandy, Mark; Waddell, Thomas K; Husain, Mansoor

    2017-08-01

    Objective : Few methods enable molecular and cellular studies of vascular aging or Type 2 diabetes (T2D). Here, we report a new approach to studying human vascular smooth muscle cell (VSMC) pathophysiology by examining VSMCs differentiated from progenitors found in skin. Approach and results : Skin-derived precursors (SKPs) were cultured from biopsies ( N =164, ∼1 cm 2 ) taken from the edges of surgical incisions of older adults ( N =158; males 72%; mean age 62.7 ± 13 years) undergoing cardiothoracic surgery, and differentiated into VSMCs at high efficiency (>80% yield). The number of SKPs isolated from subjects with T2D was ∼50% lower than those without T2D (cells/g: 0.18 ± 0.03, N =58 versus 0.40 ± 0.05, N =100, P <0.05). Importantly, SKP-derived VSMCs from subjects with T2D had higher Fluo-5F-determined baseline cytosolic Ca 2+ concentrations (AU: 1,968 ± 160, N =7 versus 1,386 ± 170, N =13, P <0.05), and a trend toward greater Ca 2+ cycling responses to norepinephrine (NE) (AUC: 177,207 ± 24,669, N =7 versus 101,537 ± 15,881, N =20, P <0.08) despite a reduced frequency of Ca 2+ cycling (events s -1 cell -1 : 0.011 ± 0.004, N =8 versus 0.021 ± 0.003, N =19, P <0.05) than those without T2D. SKP-derived VSMCs from subjects with T2D also manifest enhanced sensitivity to phenylephrine (PE) in an impedance-based assay (EC 50 nM: 72.3 ± 63.6, N =5 versus 3,684 ± 3,122, N =9, P <0.05), and impaired wound closure in vitro (% closure: 21.9 ± 3.6, N =4 versus 67.0 ± 10.3, N =4, P <0.05). Compared with aortic- and saphenous vein-derived primary VSMCs, SKP-derived VSMCs are functionally distinct, but mirror defects of T2D also exhibited by primary VSMCs. Skin biopsies from older adults yield sufficient SKPs to differentiate VSMCs, which reveal abnormal phenotypes of T2D that survive differentiation and persist even after long-term normoglycemic culture. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

  5. Bayesian Decision Theory in Enrollment Forecasting. AIR Forum 1979 Paper.

    Science.gov (United States)

    Lind, Douglas A.

    The use of subjective probability as a theoretical model for enrollment forecasting is proposed, and the results of an application of subjective probability to enrollment forecasting at the University of Toledo are reported. Subjective probability can be used as an enrollment forecasting technique for both headcount and full-time equivalent using…

  6. Successful isolation of infectious and high titer human monocyte-derived HIV-1 from two subjects with discontinued therapy.

    Science.gov (United States)

    Wang, Tong; Xu, Younong; Zhu, Haiying; Andrus, Thomas; Ivanov, Sergei B; Pan, Charlotte; Dolores, Jazel; Dann, Gregory C; Zhou, Michael; Forte, Dominic; Yang, Zihuan; Holte, Sarah; Corey, Lawrence; Zhu, Tuofu

    2013-01-01

    HIV-1 DNA in blood monocytes is considered a viral source of various HIV-1 infected tissue macrophages, which is also known as "Trojan horse" hypothesis. However, whether these DNA can produce virions has been an open question for years, due to the inability of isolating high titer and infectious HIV-1 directly from monocytes. In this study, we demonstrated successful isolation of two strains of M-HIV-1 (1690 M and 1175 M) from two out of four study subjects, together with their in vivo controls, HIV-1 isolated from CD4+ T-cells (T-HIV-1), 1690 T and 1175 T. All M- and T- HIV-1 isolates were detected CCR5-tropic. Both M- HIV-1 exhibited higher levels of replication in monocyte-derived macrophages (MDM) than the two T- HIV-1. Consistent with our previous reports on the subject 1175 with late infection, compartmentalized env C2-V3-C3 sequences were identified between 1175 M and 1175 T. In contrast, 1690 M and 1690 T, which were isolated from subject 1690 with relatively earlier infection, showed homogenous env C2-V3-C3 sequences. However, multiple reverse transcriptase (RT) inhibitor resistance-associated variations were detected in the Gag-Pol region of 1690 M, but not of 1690 T. By further measuring HIV DNA intracellular copy numbers post-MDM infection, 1690 M was found to have significantly higher DNA synthesis efficiency than 1690 T in macrophages, indicating a higher RT activity, which was confirmed by AZT inhibitory assays. These results suggested that the M- and T- HIV-1 are compartmentalized in the two study subjects, respectively. Therefore, we demonstrated that under in vitro conditions, HIV-1 infected human monocytes can productively release live viruses while differentiating into macrophages.

  7. Optimization Design of Structures Subjected to Transient Loads Using First and Second Derivatives of Dynamic Displacement and Stress

    Directory of Open Access Journals (Sweden)

    Qimao Liu

    2012-01-01

    Full Text Available This paper developed an effective optimization method, i.e., gradient-Hessian matrix-based method or second order method, of frame structures subjected to the transient loads. An algorithm of first and second derivatives of dynamic displacement and stress with respect to design variables is formulated based on the Newmark method. The inequality time-dependent constraint problem is converted into a sequence of appropriately formed time-independent unconstrained problems using the integral interior point penalty function method. The gradient and Hessian matrixes of the integral interior point penalty functions are also computed. Then the Marquardt's method is employed to solve unconstrained problems. The numerical results show that the optimal design method proposed in this paper can obtain the local optimum design of frame structures and sometimes is more efficient than the augmented Lagrange multiplier method.

  8. Reasonable Forecasts

    Science.gov (United States)

    Taylor, Kelley R.

    2010-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1983-07-01

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

  10. CCK-4-induced anxiety but not panic is associated with serum brain-derived neurotrophic factor in healthy subjects.

    Science.gov (United States)

    Maron, E; Tõru, I; Mäemets, K; Sepp, S; Vasar, V; Shlik, J; Zharkovsky, A

    2009-06-01

    Recent animal studies consistently confirm the involvement of brain-derived neurotrophic factor (BDNF) in the regulation of anxiety-related behaviours. The role of BDNF in human anxiety has been less investigated. The aim of our study was to examine the association between serum BDNF levels and panic/anxiety responses to cholecystokinin-tetrapeptide (CCK-4) challenge in healthy subjects. BDNF concentrations were detected in serum samples of 37 male and female volunteers before and 120 min after CCK-4 injection. The baseline levels of serum BDNF did not predict the occurrence of CCK-4-induced panic attacks or intensity of panic symptoms and did not significantly change 2 h after the challenge. BDNF serum concentrations 120 min after provocation did not differentiate panickers from non-panickers; however, the subjects reporting stronger anxiety response showed higher levels of BDNF than those with mild anxiety. The anxiety net increase on the Visual Analogue Scale, but not severity of panic symptoms, significantly and positively correlated with the change in BDNF concentration from baseline values. This is the first challenge study to demonstrate a possible impact of BDNF on human anxiety. Our findings suggest a general involvement of BDNF in the regulation of anxiety rather than a specific role of BDNF in disposition to panic attacks.

  11. Digitized hand-wrist radiographs: comparison of subjective and software-derived image quality at various compression ratios.

    Science.gov (United States)

    McCord, Layne K; Scarfe, William C; Naylor, Rachel H; Scheetz, James P; Silveira, Anibal; Gillespie, Kevin R

    2007-05-01

    The objectives of this study were to compare the effect of JPEG 2000 compression of hand-wrist radiographs on observer image quality qualitative assessment and to compare with a software-derived quantitative image quality index. Fifteen hand-wrist radiographs were digitized and saved as TIFF and JPEG 2000 images at 4 levels of compression (20:1, 40:1, 60:1, and 80:1). The images, including rereads, were viewed by 13 orthodontic residents who determined the image quality rating on a scale of 1 to 5. A quantitative analysis was also performed by using a readily available software based on the human visual system (Image Quality Measure Computer Program, version 6.2, Mitre, Bedford, Mass). ANOVA was used to determine the optimal compression level (P quality. When we used quantitative indexes, the JPEG 2000 images had lower quality at all compression ratios compared with the original TIFF images. There was excellent correlation (R2 >0.92) between qualitative and quantitative indexes. Image Quality Measure indexes are more sensitive than subjective image quality assessments in quantifying image degradation with compression. There is potential for this software-based quantitative method in determining the optimal compression ratio for any image without the use of subjective raters.

  12. DIFFERENT CIRCULATING BRAIN-DERIVED NEUROTROPHIC FACTOR RESPONSES TO ACUTE EXERCISE BETWEEN PHYSICALLY ACTIVE AND SEDENTARY SUBJECTS

    Directory of Open Access Journals (Sweden)

    Yu Nofuji

    2012-03-01

    Full Text Available Although circulating brain-derived neurotrophic factor (BDNF level is affected by both acute and chronic physical activity, the interaction of acute and chronic physical activity was still unclear. In this study, we compared the serum and plasma BDNF responses to maximal and submaximal acute exercises between physically active and sedentary subjects. Eight active and 8 sedentary female subjects participated in the present study. Both groups performed 3 exercise tests with different intensities, i.e. 100% (maximal, 60% (moderate and 40% (low of their peak oxygen uptake. In each exercise test, blood samples were taken at the baseline and immediately, 30 and 60 min after the test. The serum BDNF concentration was found to significantly increase immediately after maximal and moderate exercise tests in both groups. In maximal exercise test, the pattern of change in the serum BDNF concentration was different between the groups. While the serum BDNF level for the sedentary group returned to the baseline level during the recovery phase, the BDNF levels for the active group decreased below the baseline level after the maximal exercise test. No group differences were observed in the pattern of plasma BDNF change for all exercise tests. These findings suggest that regular exercise facilitates the utilization of circulating BDNF during and/or after acute exercise with maximal intensity

  13. Trading wind generation from short-term probabilistic forecasts of wind power

    DEFF Research Database (Denmark)

    Pinson, Pierre; Chevallier, Christophe; Kariniotakis, Georges

    2007-01-01

    Due to the fluctuating nature of the wind resource, a wind power producer participating in a liberalized electricity market is subject to penalties related to regulation costs. Accurate forecasts of wind generation are therefore paramount for reducing such penalties and thus maximizing revenue...... participation. Such strategies permit to further increase revenues and thus enhance competitiveness of wind generation compared to other forms of dispatchable generation. This paper formulates a general methodology for deriving optimal bidding strategies based on probabilistic forecasts of wind generation....... Despite the fact that increasing accuracy in spot forecasts may reduce penalties, this paper shows that, if such forecasts are accompanied with information on their uncertainty, i.e., in the form of predictive distributions, then this can be the basis for defining advanced strategies for market...

  14. On the Use of Global Flood Forecasts and Satellite-Derived Inundation Maps for Flood Monitoring in Data-Sparse Regions

    Directory of Open Access Journals (Sweden)

    Beatriz Revilla-Romero

    2015-11-01

    Full Text Available Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response decisions. Global-scale flood forecasting and satellite-based flood detection systems are currently operating, however their reliability for decision-making applications needs to be assessed. In this study, we performed comparative evaluations of several operational global flood forecasting and flood detection systems, using 10 major flood events recorded over 2012–2014. Specifically, we evaluated the spatial extent and temporal characteristics of flood detections from the Global Flood Detection System (GFDS and the Global Flood Awareness System (GloFAS. Furthermore, we compared the GFDS flood maps with those from NASA’s two Moderate Resolution Imaging Spectroradiometer (MODIS sensors. Results reveal that: (1 general agreement was found between the GFDS and MODIS flood detection systems, (2 large differences exist in the spatio-temporal characteristics of the GFDS detections and GloFAS forecasts, and (3 the quantitative validation of global flood disasters in data-sparse regions is highly challenging. Overall, satellite remote sensing provides useful near real-time flood information that can be useful for risk management. We highlight the known limitations of global flood detection and forecasting systems, and propose ways forward to improve the reliability of large-scale flood monitoring tools.

  15. Financial Analysts’ Forecasts

    DEFF Research Database (Denmark)

    Stæhr, Simone

    This thesis is broadly concentrated on decision making under uncertainty. It seeks to investigate how agents in financial markets make decisions at the individual level and how these decisions can sometimes be affected by personal traits and cognitive biases rather than being perfectly rational....... 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...

  16. A Forecast Model for Unemployment by Education

    DEFF Research Database (Denmark)

    Tranæs, Torben; Larsen, Anders Holm; Groes, Niels

    1994-01-01

    We present a dynamic forecast model for the labour market: demand for labour by education and the distribution of labour by education among industries are determined endogenously with overall demand by industry given exogenously. The model is derived from a simple behavioural equation based on a ...... for educational groups, where the initial forecast year is a change point for unemployment....

  17. Magnetogram Forecast: An All-Clear Space Weather Forecasting System

    Science.gov (United States)

    Barghouty, Nasser; Falconer, David

    2015-01-01

    Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

  18. pawg 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. kgfk 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. kcll 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. kden 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...

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    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...

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    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...

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    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...

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    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. khot 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. kpih 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...

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    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...

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    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...

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    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...

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    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...

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    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...

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    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...

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    Data.gov (United States)

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    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...

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    Data.gov (United States)

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    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...

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    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...

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    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...

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    Data.gov (United States)

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    Data.gov (United States)

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    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...

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    Data.gov (United States)

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    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...

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    Data.gov (United States)

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    Data.gov (United States)

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    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...

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    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...

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    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...

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    Data.gov (United States)

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    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...

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    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...

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    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...

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    Data.gov (United States)

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    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...

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    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...

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    Data.gov (United States)

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    Data.gov (United States)

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    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...

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    Data.gov (United States)

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    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...

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    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...

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    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...

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    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...

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    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...

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    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...

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    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...

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    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...

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    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...

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    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...

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    Data.gov (United States)

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    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...

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    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...

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    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...

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    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...

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    Data.gov (United States)

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    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...

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    Data.gov (United States)

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    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...

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    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...

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    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...

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    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. kalb 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...

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    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. kink 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...

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    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...

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    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. kpna 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...

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    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...

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    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...

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    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...

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    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...

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    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...

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    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...

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    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. kgsp 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. kgpt 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. 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...

  7. keri 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. kcid 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. ksaf 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...

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    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. ptya 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. katl 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. kmth 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. Assessment of reservoir system variable forecasts

    Science.gov (United States)

    Kistenmacher, Martin; Georgakakos, Aris P.

    2015-05-01

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

  15. Uncertainty and Disagreement in Forecasting Inflation : Evidence from the Laboratory (Revised version of EBC DP 2011-014)

    NARCIS (Netherlands)

    Pfajfar, D.; Zakelj, B.

    2012-01-01

    Abstract: This paper compares the behavior of subjects' uncertainty in different monetary policy environments when forecasting inflation in the laboratory. We find that inflation targeting produces lower uncertainty and higher accuracy of interval forecasts than inflation forecast targeting. We also

  16. Uncertainty and Disagreement in Forecasting Inflation : Evidence from the Laboratory (Revised version of CentER DP 2011-053)

    NARCIS (Netherlands)

    Pfajfar, D.; Zakelj, B.

    2012-01-01

    Abstract: This paper compares the behavior of subjects' uncertainty in different monetary policy environments when forecasting inflation in the laboratory. We find that inflation targeting produces lower uncertainty and higher accuracy of interval forecasts than inflation forecast targeting. We also

  17. Modelling and forecasting WIG20 daily returns

    DEFF Research Database (Denmark)

    Amado, Cristina; Silvennoinen, Annestiina; Terasvirta, Timo

    of the model is that the deterministic component is specified before estimating the multiplicative conditional variance component. The resulting model is subjected to misspecification tests and its forecasting performance is compared with that of commonly applied models of conditional heteroskedasticity....

  18. 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,

  19. Are Forecast Updates Progressive?

    NARCIS (Netherlands)

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

    2013-01-01

    textabstractMany macroeconomic forecasts and forecast updates like those from IMF and OECD 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,

  20. Effect of Training Exercise on Urinary Brain-derived Neurotrophic Factor Levels and Cognitive Performances in Overweight and Obese Subjects.

    Science.gov (United States)

    Russo, Angelo; Buratta, Livia; Pippi, Roberto; Aiello, Cristina; Ranucci, Claudia; Reginato, Elisa; Santangelo, Valerio; DeFeo, Pierpaolo; Mazzeschi, Claudia

    2017-02-01

    Exercise-mediated, brain-derived neurotrophic factor induction benefits health and cognitive functions. The multifaceted interplay between physical activity, urinary brain-derived neurotrophic factor levels and cognitive functioning has been largely neglected in previous literature. In this pilot study, two bouts of training exercise (65% and 70% of heart rate reserve) influenced urinary brain-derived neurotrophic factor levels and cognitive performances in 12 overweight and obese participants. Percent heart rate reserve, expenditure energy, brain-derived neurotrophic factor urinary levels and cognitive performances were measured before and after the exercise. No significant variations in energy expenditure were observed, while differences of heart rate reserve between two groups were maintained. Both bouts of training exercise induced a similar reduction in urinary brain-derived neurotrophic factor levels. Only visuo-spatial working memory capacity at 65% of heart rate reserve showed a significant increase. These findings indicate a consistent effect of training exercise on urinary brain-derived neurotrophic factor levels and cognitive factors in overweight and obese participants.

  1. Acute differential effects of milk-derived dietary proteins on postprandial lipaemia in obese non-diabetic subjects

    DEFF Research Database (Denmark)

    Holmer-Jensen, Jens; Hartvigsen, Merete; Mortensen, L.S.

    2012-01-01

    Postprandial lipaemia is an established risk factor for atherosclerosis. To investigate the acute effect of four milk-derived dietary proteins (alpha-lactalbumin, whey isolate, caseinoglycomacropeptide and whey hydrolysate) on postprandial lipaemia, we have conducted a randomized, acute, single-b...

  2. Analysis of mesoscale forecasts using ensemble methods

    CERN Document Server

    Gross, Markus

    2016-01-01

    Mesoscale forecasts are now routinely performed as elements of operational forecasts and their outputs do appear convincing. However, despite their realistic appearance at times the comparison to observations is less favorable. At the grid scale these forecasts often do not compare well with observations. This is partly due to the chaotic system underlying the weather. Another key problem is that it is impossible to evaluate the risk of making decisions based on these forecasts because they do not provide a measure of confidence. Ensembles provide this information in the ensemble spread and quartiles. However, running global ensembles at the meso or sub mesoscale involves substantial computational resources. National centers do run such ensembles, but the subject of this publication is a method which requires significantly less computation. The ensemble enhanced mesoscale system presented here aims not at the creation of an improved mesoscale forecast model. Also it is not to create an improved ensemble syste...

  3. Development of Ensemble Model Based Water Demand Forecasting Model

    Science.gov (United States)

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

    2014-05-01

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

  4. Assimilation of Goes-Derived Skin Temperature Tendencies into Mesoscale Models to Improve Forecasts of near Surface Air Temperature and Mixing Ratio

    Science.gov (United States)

    Lapenta, William M.; McNider, Richard T.; Suggs, Ron; Jedlovec, Gary; Robertson, Franklin R.

    1998-01-01

    A technique has been developed for assimilating GOES-FR skin temperature tendencies into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature chance closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. An advantage of this technique for short-range forecasts (0-48 h) is that it does not require a complex land-surface formulation within the atmospheric model. As a result, the need to specify poorly known soil and vegetative characteristics is eliminated. The GOES assimilation technique has been incorporated into the PSU/NCAR MM5. Results will be presented to demonstrate the ability of the assimilation scheme to improve short- term (0-48h) simulations of near-surface air temperature and mixing ratio during the warm season for several selected cases which exhibit a variety of atmospheric and land-surface conditions. In addition, validation of terms in the simulated surface energy budget will be presented using in situ data collected at the Southern Great Plains (SGP) Cloud And Radiation Testbed (CART) site as part of the Atmospheric Radiation Measurements Program (ARM).

  5. Global Energy Forecasting Competition 2012

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2014-01-01

    The Global Energy Forecasting Competition (GEFCom2012) attracted hundreds of participants worldwide, who contributed many novel ideas to the energy forecasting field. This paper introduces both tracks of GEFCom2012, hierarchical load forecasting and wind power forecasting, with details...

  6. Improving Software Reliability Forecasting

    NARCIS (Netherlands)

    Burtsy, Bernard; Albeanu, Grigore; Boros, Dragos N.; Popentiu, Florin; Nicola, V.F.

    1996-01-01

    This work investigates some methods for software reliability forecasting. A supermodel is presented as a suited tool for prediction of reliability in software project development. Also, times series forecasting for cumulative interfailure time is proposed and illustrated.

  7. From beat rate variability in induced pluripotent stem cell-derived pacemaker cells to heart rate variability in human subjects.

    Science.gov (United States)

    Ben-Ari, Meital; Schick, Revital; Barad, Lili; Novak, Atara; Ben-Ari, Erez; Lorber, Avraham; Itskovitz-Eldor, Joseph; Rosen, Michael R; Weissman, Amir; Binah, Ofer

    2014-10-01

    We previously reported that induced pluripotent stem cell-derived cardiomyocytes manifest beat rate variability (BRV) resembling heart rate variability (HRV) in the human sinoatrial node. We now hypothesized the BRV-HRV continuum originates in pacemaker cells. To investigate whether cellular BRV is a source of HRV dynamics, we hypothesized 3 levels of interaction among different cardiomyocyte entities: (1) single pacemaker cells, (2) networks of electrically coupled pacemaker cells, and (3) the in situ sinoatrial node. We measured BRV/HRV properties in single pacemaker cells, induced pluripotent stem cell-derived contracting embryoid bodies (EBs), and electrocardiograms from the same individual. Pronounced BRV/HRV was present at all 3 levels. The coefficient of variance of interbeat intervals and Poincaré plot indices SD1 and SD2 for single cells were 20 times greater than those for EBs (P heart (the latter two were similar; P > .05). We also compared BRV magnitude among single cells, small EBs (~5-10 cells), and larger EBs (>10 cells): BRV indices progressively increased with the decrease in the cell number (P heart rhythm. The decreased BRV magnitude in transitioning from the single cell to the EB suggests that the HRV of in situ hearts originates from the summation and integration of multiple cell-based oscillators. Hence, complex interactions among multiple pacemaker cells and intracellular Ca(2+) handling determine HRV in humans and cardiomyocyte networks. Copyright © 2014 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

  8. Forecasts of land uses

    Science.gov (United States)

    David N. Wear

    2013-01-01

    Key FindingsBetween 30 million and 43 million acres of land in the South are forecasted to be developed for urban uses by 2060 from a base of 30 million acres in 1997. These forecasts are based on a continuation of historical development intensities.From 1997 to 2060, the South is forecasted to lose between 11 million acres (7...

  9. Hydrological Forecasting in Mexico: Extending the University of Washington West-wide Seasonal Hydrologic Forecast System

    Science.gov (United States)

    Munoz-Arriola, F.; Thomas, G.; Wood, A.; Wagner-Gomez, A.; Lobato-Sanchez, R.; Lettenmaier, D. P.

    2007-12-01

    Hydrologic forecasting in areas constrained by the availability of hydrometeorological records is a notable challenge in water resource management. Techniques from the University of Washington West-wide Seasonal Hydrologic Forecast system www.hydro.washington.edu/forecast/westwide) for generating daily nowcasts in areas with sparse and time-varying station coverage have been extended from the western U.S. into Mexico. The primary forecasting approaches consist of ensembles based on the NWS ensemble streamflow prediction method (ESP; essentially resampling of climatology) and on NCEP Coupled Forecast System (CFS) outputs. These in turn are used to force the Variable Infiltration Capacity (VIC) macroscale hydrology model to produce streamflow ensembles. The initial hydrologic state utilized in the seasonal forecasting is generated by VIC using daily real-time hydrologic nowcasts, produced using forcings derived via an 'index-station percentile' approach from meteorological station data accessed in real time from Servicio Meteorológico Nacional (SMN). One-year lead time streamflow forecasts at monthly time step are produced at a set of major river locations in Mexico. As a case study, the streamflow forecasts, along with forecasts of reservoir evaporation, are used as input to the Simulation-Optimization (SIMOP) model of the Rio Yaqui system, one of the major agricultural production centers of Mexico. This is the first step in an eventual planned water management implementation over all of Mexico.

  10. Severe Weather Forecast Decision Aid

    Science.gov (United States)

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

    2005-01-01

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

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

    Science.gov (United States)

    Lall, U.

    2012-12-01

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

  12. An unusually large 5q duplication in an adult female subject: spreading of inactivation and in vitro instability of the derivative Xp/5q chromosome.

    Science.gov (United States)

    Rovescalli, A; Ghidoni, A

    1989-01-01

    An unbalanced translocation resulting in an unusually large partial 5q trisomy (5q11-5qter) and partial Xp monosomy (Xp11-Xpter) is reported in a 24 yr old woman with phenotypic abnormalities including gonadal dysgenesis and mental retardation. The karyotypes of the parents and the brother were found normal. Peripheral blood stimulated lymphocytes and cutaneous fibroblasts of the proband exhibited constantly, after BrdU incorporation, selective inactivation of the derivative X;5 chromosome spreading to the 5q duplicate segment. A variety of numerical and structural changes involving the derivative chromosome were observed in about 10% of cells of the cultured lymphoblastoid line established from the subject's lymphocytes. The extended 5q duplication, according to the literature, is generally accompanied by a severe phenotype and by developmental failure; it is therefore believe that genetic inactivation of the 5q duplicated region permitted the proband's development to adult age, despite the profound chromosomal imbalance.

  13. Error analysis for Winters' Additive Seasonal Forecasting System

    OpenAIRE

    McKenzie, Edward

    1984-01-01

    A procedure for deriving the variance of the forecast error for Winters' Additive Seasonal Forecasting system is given. Both point and cumulative T-step ahead forecasts are dealt with. Closed form expressions are given in the cases when the model is (i) trend-free and (ii) non-seasonal. The effects of renormal ization of the seasonal factors is also discussed. The fact that the error variance for this system can be infinite is discussed and the relationship of this property ...

  14. Toward Improved Solar Irradiance Forecasts: Comparison of the Global Horizontal Irradiances Derived from the COMS Satellite Imagery Over the Korean Peninsula

    Science.gov (United States)

    Kim, Chang Ki; Kim, Hyun-Goo; Kang, Yong-Heack; Yun, Chang-Yeol

    2017-07-01

    This study introduces the University of Arizona Solar Irradiance Based on Satellite/Korea Institute of Energy Research, which is usually called UASIBS/KIER model. Then the evaluation of modeling performance is done against the ground observations for the instantaneous, hourly, and daily time scales over the Korean Peninsula in this study. The relative root mean square error for the instantaneous time scale is 7.4 and 16.7% for the clear and cloudy skies, respectively. The hourly mean estimates are compared with the in situ measurements from 35 ground observation stations, resulting in a relative root mean square error ranging from 9.1 to 15.5%. The daily aggregates are proven as the most reliable estimates. The UASIBS/KIER estimates are also compared with the routine solar insolation product from the Korea Meteorological Administration. Finally, the solar energy resource map has been built by the daily solar irradiance derived from the UASIBS/KIER model, followed by its comparison with the other gridded datasets.

  15. Forecasters priorities for improving probabilistic flood forecasts

    Science.gov (United States)

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

    2013-02-01

    Hydrological ensemble prediction systems (HEPS) have in recent years been increasingly used for the operational forecasting of floods by hydrometeorological agencies. The most obvious advantages of HEPS are that more of the uncertainty in the modelling system can be assessed; and that ensemble prediction systems generally have better skill than deterministic systems both in the terms of the mean forecast performance and the potential forecasting of extreme events. Research efforts have so far mostly been devoted to the improvement of the technical aspects of the model systems themselves. However, in this paper we argue that there are other areas of HEPS that need urgent attention; such as assessment of the full uncertainty in the forecast chain, multimodel approaches, robust forecast skill assessment and further collaboration and knowledge exchange between operational forecasters and the model development community. In light of limited resources we suggest a simple model to classify the identified priorities in terms of their cost and complexity to decide in which order to tackle them This model is then used to create an action plan of short-, medium- and long-term research priorities with the ultimate goal of an optimal improvement in operational HEPS.

  16. Prospective Tests of Southern California Earthquake Forecasts

    Science.gov (United States)

    Jackson, D. D.; Schorlemmer, D.; Gerstenberger, M.; Kagan, Y. Y.; Helmstetter, A.; Wiemer, S.; Field, N.

    2004-12-01

    We are testing earthquake forecast models prospectively using likelihood ratios. Several investigators have developed such models as part of the Southern California Earthquake Center's project called Regional Earthquake Likelihood Models (RELM). Various models are based on fault geometry and slip rates, seismicity, geodetic strain, and stress interactions. Here we describe the testing procedure and present preliminary results. Forecasts are expressed as the yearly rate of earthquakes within pre-specified bins of longitude, latitude, magnitude, and focal mechanism parameters. We test models against each other in pairs, which requires that both forecasts in a pair be defined over the same set of bins. For this reason we specify a standard "menu" of bins and ground rules to guide forecasters in using common descriptions. One menu category includes five-year forecasts of magnitude 5.0 and larger. Contributors will be requested to submit forecasts in the form of a vector of yearly earthquake rates on a 0.1 degree grid at the beginning of the test. Focal mechanism forecasts, when available, are also archived and used in the tests. Interim progress will be evaluated yearly, but final conclusions would be made on the basis of cumulative five-year performance. The second category includes forecasts of earthquakes above magnitude 4.0 on a 0.1 degree grid, evaluated and renewed daily. Final evaluation would be based on cumulative performance over five years. Other types of forecasts with different magnitude, space, and time sampling are welcome and will be tested against other models with shared characteristics. Tests are based on the log likelihood scores derived from the probability that future earthquakes would occur where they do if a given forecast were true [Kagan and Jackson, J. Geophys. Res.,100, 3,943-3,959, 1995]. For each pair of forecasts, we compute alpha, the probability that the first would be wrongly rejected in favor of the second, and beta, the probability

  17. A hindcast archive to assess forecast uncertainty of seasonal forecasts for the Columbia River Basin

    Science.gov (United States)

    Nijssen, B.

    2006-12-01

    More than half of the electricity in the northwestern United States is generated by hydropower facilities in the Columbia River Basin. Consequently, seasonal hydrologic forecasts of naturalized streamflow are of interest to system operators, energy traders and financial institutions. Much of the seasonal streamflow predictability is derived from the importance of snow melt in the Columbia River Basin. Further predictability is derived from the ENSO-state (El Niño Southern Oscillation), which affects precipitation patterns in the basin. Typically, the Pacific Northwest experiences a greater likelihood of reduced precipitation during El Niño episodes, and a greater likelihood of increased precipitation during La Niña episodes. For the 2006 water year, we created long-range operational hydrologic forecasts for selected locations in the basin using a macroscale hydrologic model and an ensemble streamflow prediction (ESP) methodology. Although our ESP approach provided a measure of the range of expected streamflow conditions, it did not account for the uncertainty in forecast initial conditions, parameter uncertainty or model uncertainty. To assess the total uncertainty associated with our hydrologic forecasts, we have created a hindcast database for the period 1950-2005, which includes 12-month forecasts made on the start of each month during the period November May. This hindcast archive enables us to assess the total uncertainty associated with our seasonal forecasts. We will present forecast verification results for selected locations in the Columbia River Basin as a function of lead time and ENSO condition.

  18. Brain-derived neurotrophic factor is increased in atopic dermatitis and modulates eosinophil functions compared with that seen in nonatopic subjects.

    Science.gov (United States)

    Raap, Ulrike; Goltz, Christine; Deneka, Nicole; Bruder, Manuela; Renz, Harald; Kapp, Alexander; Wedi, Bettina

    2005-06-01

    Recently, the pivotal role of brain-derived neurotrophic factor (BDNF) has been described in allergic asthma. However, the role of this neurotrophin in atopic dermatitis (AD) still remains unknown. The aim of this study was to investigate the functional role of BDNF on eosinophils and to assess BDNF levels in patients with AD and nonatopic control subjects. Methods p75 Neurotrophin receptor and tyrosine kinase B receptor expression was demonstrated by using FACS analysis and immunohistochemistry. BDNF levels were assessed with ELISA and FACS analysis. Chemotactic activity (modified Boyden chamber assay), eosinophil cationic protein release (fluoroenzyme immunoassay), respiratory burst (lucigenin-dependent chemiluminescence), and apoptosis (Nicoletti protocol and Annexin-V method) assays were used to assess BDNF functional activity. BDNF levels were increased in serum, plasma, eosinophils, and supernatants of stimulated eosinophils from patients with AD compared with levels seen in nonatopic control subjects ( P neurotrophin receptor and tyrosine kinase B expression was higher on eosinophils from patients with AD compared with that seen on eosinophils from nonatopic control subjects ( P < .05-.001). Eosinophil apoptosis was inhibited by BDNF ( P < .05-.01) and chemotactic index was increased ( P < .001) in BDNF-stimulated eosinophils from patients with AD, whereas this effect was not shown in eosinophils from nonatopic control subjects. However, no response of BDNF through the release of eosinophil cationic protein or reactive oxygen species was found. This study provides the first evidence for a functional role of BDNF on eosinophils from patients with AD, probably mediated by an increased expression of BDNF receptors compared with that seen in nonatopic control subjects. In addition, higher intracellular, serum, and plasma BDNF levels, as well as the release of BDNF by eosinophils, underline the particular importance of BDNF in patients with AD, pointing to new

  19. Isolation of a high affinity Bet v 1-specific IgG-derived ScFv from a subject vaccinated with hypoallergenic Bet v 1 fragments.

    Science.gov (United States)

    Gadermaier, Elisabeth; Marth, Katharina; Lupinek, Christian; Campana, Raffaela; Hofer, Gerhard; Blatt, Katharina; Smiljkovic, Dubravka; Roder, Uwe; Focke-Tejkl, Margarete; Vrtala, Susanne; Keller, Walter; Valent, Peter; Valenta, Rudolf; Flicker, Sabine

    2018-01-09

    Recombinant hypoallergenic allergen derivatives have been used in clinical immunotherapy studies and clinical efficacy seems to be related to the induction of blocking IgG antibodies recognizing the wild type allergens. However, so far no treatment-induced IgG antibodies have been characterized. To clone, express and characterize IgG antibodies induced by vaccination with two hypoallergenic recombinant fragments of the major birch pollen allergen, Bet v 1 in a non-allergic subject. A phage-displayed combinatorial single chain fragment (ScFv) library was constructed from blood of the immunized subject and screened for Bet v 1-reactive antibody fragments. ScFvs were tested for specificity and cross-reactivity to native Bet v 1 and related pollen and food allergens and epitope mapping was performed. Germline ancestor genes of the antibody were analyzed with the ImMunoGeneTics (IMGT) database. The affinity to Bet v 1 and cross-reactive allergens was determined by surface plasmon resonance measurements. The ability to inhibit patients' IgE binding to ELISA plate-bound allergens and allergen-induced basophil activation was assessed. A combinatorial ScFv library was obtained from the vaccinated donor after three injections with the Bet v 1 fragments. Despite being almost in germline configuration, ScFv (clone H3-1) reacted with high affinity to native Bet v 1 and homologous allergens, inhibited allergic patients' polyclonal IgE binding to Bet v 1 and partially suppressed allergen-induced basophil activation. Immunization with unfolded hypoallergenic allergen derivatives induces high affinity antibodies even in non-allergic subjects which recognize the folded wild-type allergens and inhibit polyclonal IgE binding of allergic patients. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  20. Statistical Flood Forecasting for the Mekong River

    Science.gov (United States)

    Shahzad, M. K.; Lindenmaier, F.; Ihringer, J.; Plate, E. J.; Nestmann, F.

    2009-04-01

    An ongoing study for improving flood forecasting for the Mekong River by statistical methods has yielded first results, which reduce forecasting errors of previous forecasting models. A forecast always is subject to uncertainty, both due to model uncertainty and natural variability. In principle, model uncertainty could be reduced by improved models and better calibration, whereas natural variability has to be endured. In flood forecasting, hydro-meteorological uncertainties, physiographic unknowns together with measurement errors and model errors are decisive factors determining the width of future uncertainty bands. The degree of certitude of forecasts varies from event to event depending on the ensemble of realizations of the flood hydrograph (Krzysztofowicz, 2001). Without any information on previous discharges and rainfall the range of forecasts can be between zero and infinity. When time series of discharges are available then the uncertainty band is the probability distribution of the stages. At any particular point in time the uncertainty band can be further narrowed by usage of real time discharges of the past, and conditional maximum and minimum discharges for the future can be estimated, due to the existence of physical continuity in space and time. As a consequence, for one day ahead forecasts the coefficient of variation of the forecast for small basins is large, whereas it is small for large river basins, as for the Mekong River (Plate, 2005). The consequences of this continuity for the Mekong are explored in this study. The basin of the Mekong River has an area of 795,000 km² and a length of about 4000 km. Flooding is a major problem, and flood forecasting is the most important non-technical solution. The existing forecasting method is based on a physical hydrological model, which yields forecasts of limited accuracy, partly due to limited quality of runoff data and insufficient rainfall information in this data sparse basin. To overcome

  1. Evaluating probability forecasts

    OpenAIRE

    Lai, Tze Leung; Gross, Shulamith T.; Shen, David Bo

    2011-01-01

    Probability forecasts of events are routinely used in climate predictions, in forecasting default probabilities on bank loans or in estimating the probability of a patient's positive response to treatment. Scoring rules have long been used to assess the efficacy of the forecast probabilities after observing the occurrence, or nonoccurrence, of the predicted events. We develop herein a statistical theory for scoring rules and propose an alternative approach to the evaluation of probability for...

  2. Commuter Airline Forecasts,

    Science.gov (United States)

    1981-05-01

    conterminous United States (48 contiguous states and the District of Columbia), for the State of Hawaii, and for the U.S. Carribean areas, Puerto Rico and U.S...FAA 15. Supplementary Notes I Abstract This publication presents forecasts of cammuter air carrier activity and describes the models designed for...forecasting Contenninous United States, Puerto Rico and the Virgin Islands, Hawaii, and individual airport activity. These forecasts take into account the

  3. Forecaster priorities for improving probabilistic flood forecasts

    Science.gov (United States)

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

    2014-05-01

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

  4. 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...

  5. Steam coal forecaster

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-07-01

    This quarterly forecasting service provides a short-term analysis and predictions of the international steam coal trade. Sections are entitled: market review; world steam coal at a glance; economics/foreign exchange; demand (reviewing the main purchasing companies country-by-country); supply (country-by-country information on the main producers of steam coal); and freight. A subscription to Steam Coal Forecaster provides: a monthly PDF of McCloskey's Steam Coal Forecaster sent by email; access to database of stories in Steam Coal Forecaster via the search function; and online access to the latest issue of Steam Coal.

  6. A Hidden Markov Model for avalanche forecasting on Chowkibal ...

    Indian Academy of Sciences (India)

    for operational avalanche forecasting in the ski area of the Parsenn region and found quite useful for operational purpose. Following the suggestions of. Obled and Good (1980) and Buser et al. (1987),. McClung and Tweedy (1994) derived a numerical avalanche prediction scheme for avalanche forecast- ing on Kootenay ...

  7. The Forecast Combination Puzzle: A Simple Theoretical Explanation

    NARCIS (Netherlands)

    G. Claeskens (Gerda); J. Magnus (Jan); A. Vasnev (Andrey); W. Wang (Wendun)

    2014-01-01

    markdownabstract__Abstract__ is papers offers a theoretical explanation for the stylized fact that forecast combinations with estimated optimal weights often perform poorly in applications. The properties of the forecast combination are typically derived under the assumption that the weights are

  8. The forecast combination puzzle : A simple theoretical explanation

    NARCIS (Netherlands)

    Claeskens, Gerda; Magnus, Jan R.; Vasnev, Andrey L.; Wang, Wendun

    2016-01-01

    This paper offers a theoretical explanation for the stylized fact that forecast combinations with estimated optimal weights often perform poorly in applications. The properties of the forecast combination are typically derived under the assumption that the weights are fixed, while in practice they

  9. Differential Phenotypes of Myeloid-Derived Suppressor and T Regulatory Cells and Cytokine Levels in Amnestic Mild Cognitive Impairment Subjects Compared to Mild Alzheimer Diseased Patients

    Directory of Open Access Journals (Sweden)

    Aurélie Le Page

    2017-07-01

    Full Text Available Alzheimer disease (AD is the most prevalent form of dementia although the underlying cause(s remains unknown at this time. However, neuroinflammation is believed to play an important role and suspected contributing immune parameters can be revealed in studies comparing patients at the stage of amnestic mild cognitive impairment (aMCI to healthy age-matched individuals. A network of immune regulatory cells including regulatory T cells (Tregs and myeloid-derived suppressor cells (MDSCs maintains immune homeostasis but there are very few data on the role of these cells in AD. Here, we investigated the presence of these cells in the blood of subjects with aMCI and mild AD (mAD in comparison with healthy age-matched controls. We also quantitated several pro- and anti-inflammatory cytokines in sera which can influence the development and activation of these cells. We found significantly higher levels of MDSCs and Tregs in aMCI but not in mAD patients, as well as higher serum IL-1β levels. Stratifying the subjects based on CMV serostatus that is known to influence multiple immune parameters showed an absence of differences between aMCI subjects compared to mAD patients and healthy controls. We suggest that the increase in MDSCs and Tregs number in aMCI subjects may have a beneficial role in modulating inflammatory processes. However, this protective mechanism may have failed in mAD patients, allowing progression of the disease. This working hypothesis obviously requires testing in future studies.

  10. 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......) 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....

  11. 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...

  12. Nambe Pueblo Water Budget and Forecasting model.

    Energy Technology Data Exchange (ETDEWEB)

    Brainard, James Robert

    2009-10-01

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

  13. 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

  14. Forecasts of forest conditions

    Science.gov (United States)

    Robert Huggett; David N. Wear; Ruhong Li; John Coulston; Shan Liu

    2013-01-01

    Key FindingsAmong the five forest management types, only planted pine is expected to increase in area. In 2010 planted pine comprised 19 percent of southern forests. By 2060, planted pine is forecasted to comprise somewhere between 24 and 36 percent of forest area.Although predicted rates of change vary, all forecasts reveal...

  15. 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

  16. 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.

  17. The GOCF/AWAP system - forecasting temperature extremes

    Energy Technology Data Exchange (ETDEWEB)

    Fawcett, Robert [National Climate Centre, Australian Bureau of Meteorology, Docklands, Victoria 3008 (Australia); Hume, Timothy, E-mail: r.fawcett@bom.gov.a, E-mail: t.hume@bom.gov.a [Centre for Australian Weather and Climate Research, Australian Bureau of Meteorology, Docklands, Victoria 3008 (Australia)

    2010-08-15

    Gridded hourly temperature forecasts from the Bureau of Meteorology's Gridded Operational Consensus Forecasting (GOCF) system are combined in real time with the Australian Water Availability Project (AWAP) gridded daily temperature analyses to produce gridded daily maximum and minimum temperature forecasts with lead times from one to five days. These forecasts are compared against the historical record of AWAP daily temperature analyses (1911 to present), to identify regions where record or near-record temperatures are predicted to occur. This paper describes the GOCF/AWAP system, showing how the daily maximum and minimum temperature forecasts are prepared from the hourly forecasts, and how they are bias-corrected in real time using the AWAP analyses, against which they are subsequently verified. Using monthly climatologies of long-term daily mean, standard deviation and all-time highest and lowest on record, derived forecast products (for both maximum and minimum temperature) include ordinary and standardised anomalies, 'forecast - highest on record' and 'forecast - lowest on record'. Compensation for the climatological variation across the country is achieved in these last two products, which provide the necessary guidance as to whether or not record-breaking temperatures are expected, by expressing the forecast departure from the previous record in both {sup 0}C and standard deviations.

  18. Assessment of storm forecast

    DEFF Research Database (Denmark)

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

    at analysing the ability of existing forecast tools to predict storms at the Horns Rev 2 wind farm. The focus will be on predicting the time where the wind turbine will need to shut down to protect itself, e.g. the time where wind speed exceeds 25 m/s. At the same time, the planned shut-down should cost...... as little lost wind energy as possible. Therefore, the planned shut down time should be as close as possible to the time where the wind turbine itself would shut down, but still reliable. The forecast systems available to ENERGINET.dk will be applied. The forecast tools ability of accurately predicting...... 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...

  19. Statistical methods for solar flare probability forecasting

    Science.gov (United States)

    Vecchia, D. F.; Tryon, P. V.; Caldwell, G. A.; Jones, R. W.

    1980-09-01

    The Space Environment Services Center (SESC) of the National Oceanic and Atmospheric Administration provides probability forecasts of regional solar flare disturbances. This report describes a statistical method useful to obtain 24 hour solar flare forecasts which, historically, have been subjectively formulated. In Section 1 of this report flare classifications of the SESC and the particular probability forecasts to be considered are defined. In Section 2 we describe the solar flare data base and outline general principles for effective data management. Three statistical techniques for solar flare probability forecasting are discussed in Section 3, viz, discriminant analysis, logistic regression, and multiple linear regression. We also review two scoring measures and suggest the logistic regression approach for obtaining 24 hour forecasts. In Section 4 a heuristic procedure is used to select nine basic predictors from the many available explanatory variables. Using these nine variables logistic regression is demonstrated by example in Section 5. We conclude in Section 6 with band broad suggestions regarding continued development of objective methods for solar flare probability forecasting.

  20. Forecasting Companies’ Future Economic Development

    Directory of Open Access Journals (Sweden)

    Jaroslav Dvořáček

    2012-12-01

    Full Text Available The subject of this paper is financial forecasting. The objective is to predict whether a company can continue in successful operationor is jeopardised by default. The paper takes into account an application of discriminate analysis concerning data files of 85 non-bankrupt,and 85 bankrupt firms in the Czech Republic, at which point mining companies are in minority, industrial enterprises predominate. 5-8 inputvariables in the form of ratios and indexes have been used for the analysis. The non-bankrupt vis-à-vis bankrupt classification accuracyis defined.

  1. Enrollment Forecasting. Educational Facilities Digest 1.

    Science.gov (United States)

    Piele, Philip; Wright, Darrell

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

  2. The effects of forecast errors on the merchandising of wind power; Auswirkungen von Prognosefehlern auf die Vermarktung von Windstrom

    Energy Technology Data Exchange (ETDEWEB)

    Roon, Serafin von

    2012-02-28

    A permanent balance between consumption and generation is essential for a stable supply of electricity. In order to ensure this balance, all relevant load data have to be announced for the following day. Consequently, a day-ahead forecast of the wind power generation is required, which also forms the basis for the sale of the wind power at the wholesale market. The main subject of the study is the short-term power supply, which compensates errors in wind power forecasting for balancing the wind power forecast errors at short notice. These forecast errors effects the revenues and the expenses by selling and buying power in the day-ahead, intraday and balance energy market. These price effects resulting from the forecast errors are derived from an empirical analysis. In a scenario for the year 2020 the potential of conventional power plants to supply power at short notice is evaluated from a technical and economic point of view by a time series analysis and a unit commitment simulation.

  3. Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2016-01-01

    fundamentally. In this competitive and dynamic environment, many decision-making processes rely on probabilistic forecasts to quantify the uncertain future. Although most of the papers in the energy forecasting literature focus on point or singlevalued forecasts, the research interest in probabilistic energy...... forecasting research has taken off rapidly in recent years. In this paper, we summarize the recent research progress on probabilistic energy forecasting. A major portion of the paper is devoted to introducing the Global Energy Forecasting Competition 2014 (GEFCom2014), a probabilistic energy forecasting...

  4. Volatility Forecast in Crises and Expansions

    Directory of Open Access Journals (Sweden)

    Sergii Pypko

    2015-08-01

    Full Text Available We build a discrete-time non-linear model for volatility forecasting purposes. This model belongs to the class of threshold-autoregressive models, where changes in regimes are governed by past returns. The ability to capture changes in volatility regimes and using more accurate volatility measures allow outperforming other benchmark models, such as linear heterogeneous autoregressive model and GARCH specifications. Finally, we show how to derive closed-form expression for multiple-step-ahead forecasting by exploiting information about the conditional distribution of returns.

  5. 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

  6. Model selection for forecast combination

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans)

    2008-01-01

    textabstractIn this paper it is advocated to select a model only if it significantly contributes to the accuracy of a combined forecast. Using hold-out-data forecasts of individual models and of the combined forecast, a useful test for equal forecast accuracy can be designed. An illustration for

  7. 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.

  8. 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 Apex NYHOPS subdomain. Currents, waves, surface meteorology, and water conditions.

  9. New approach to rock burst forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Ivanov, V.V.; Fokin, A.N.; Pimonov, A.G. (Kuzbasskii Politekhnicheskii Institut (USSR))

    1990-10-01

    Deals with the problem of rock burst forecasting that departs from the concept of solid body strength and breaking and from equations that relate endurance of a solid body to continuous stress. A formula is derived that permits the lifetime of a rock volume under stress to be calculated. A block diagram of a laboratory automatic system is presented that is capable of monitoring the stress state of a rock sample and of forecasting the time to sample destruction. The system consists of a loading fixture, electromagnetic emission sensor, frequency meter, microprocessor and plotter. An example of a plot of the rate of fissure formation as a function of time is shown and a monitor screen display of a sample life versus time is also presented. It is maintained that the system creates a basis for developing a system that would monitor and forecast rock burst hazards in a continuous manner. 4 refs.

  10. 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 ...

  11. NEMEFO: NEural MEteorological FOrecast

    Energy Technology Data Exchange (ETDEWEB)

    Pasero, E.; Moniaci, W.; Meindl, T.; Montuori, A. [Polytechnic of Turin (Italy). Dept. of Electronics

    2004-07-01

    Artificial Neural Systems are a well-known technique used to classify and recognize objects. Introducing the time dimension they can be used to forecast numerical series. NEMEFO is a ''nowcasting'' tool, which uses both statistical and neural systems to forecast meteorological data in a restricted area close to a meteorological weather station in a short time range (3 hours). Ice, fog, rain are typical events which can be anticipated by NEMEFO. (orig.)

  12. Impact of Global and Segmental Hypertrophy on Two-Dimensional Strain Derived from Three-Dimensional Echocardiography in Hypertrophic Cardiomyopathy: Comparison with Healthy Subjects.

    Science.gov (United States)

    Voilliot, Damien; Huttin, Olivier; Hammache, Néfissa; Filippetti, Laura; Vaugrenard, Thibaud; Aliot, Etienne; Sadoul, Nicolas; Juillière, Yves; Selton-Suty, Christine

    2015-09-01

    Patients with hypertrophic cardiomyopathy (HCM) present unusual myocardial mechanics. The aim of this study was to assess the impact of hypertrophy on global and regional two-dimensional (2D) strain derived from both tomographic images (2D/2D) and volumetric image acquisition (2D/three-dimensional [3D]) in patients with HCM compared with control subjects. Comprehensive resting 2D and 3D echocardiography was performed in 40 patients with HCM and in 53 control subjects, with comparable distributions of age, gender, and left ventricular (LV) ejection fraction. LV global and segmental measurements of all 2D/2D and 2D/3D peak strain components (global and segmental longitudinal strain, global and segmental circumferential strain, global and segmental radial strain, and global and segmental area strain) and 3D indexed LV end-diastolic myocardial mass were obtained from all patients. LV wall thickness was assessed in short-axis views and classified in four quartiles (16.5 mm). The reproducibility of 2D/3D strain was similar or greater and more consistent for all components compared with 2D/2D strain analysis. There was a significant correlation between 3D LV end-diastolic mass and all 2D/3D strain components (P < .05). Two-dimensional/3D global circumferential strain had the strongest association with 3D LV ejection fraction (r = 0.50, P = .001). For segmental deformation, patients with HCM had lower longitudinal deformation whatever the LV wall thickness, whereas circumferential function was increased in nonhypertrophied and poorly hypertrophied segments compared with control subjects. Two-dimensional/3D strain is a reliable technique to assess myocardial deformation. Myocardial mass is related to 2D/3D strain components in patients with HCM. Circumferential deformation, compared with longitudinal deformation, seems to be the main component of the maintenance of systolic function in HCM. Copyright © 2015 American Society of Echocardiography. Published by Elsevier

  13. Downscaling Wind Forecasts via Clustering and Regression

    Science.gov (United States)

    Lee, H. S.; Zhang, Y.; Liu, Y.; Wu, L.; He, Y.; Schaake, J. C.

    2016-12-01

    Wind is an important weather variable and a key determinant of evaporation, snowfall and coastal flooding. At present, wind information from medium-range weather forecast is of limited accuracy, and the associated resolution is often too coarse to be used directly for hydrologic prediction purposes. This work presents a statistical post-processing framework that will be used to generate fine-scale wind products to serve the NOAA's National Water Model effort. The prototype of this framework consists of two components: a) a cluster analysis module that classifies Automated Surface Observing System (ASOS) stations into multiple groups based on elevation and/or surface roughness lengths derived from National Land Cover Database 2011 (NLCD2011), and b) a regression module based on the Heteroscedastic Extended Logistic Regression (HXLR) technique that statistically downscales GEFS wind hindcasts to the location of the closest station within each identified cluster. The efficacy of the framework is assessed for a region that is roughly the service area of NOAA's Middle Atlantic River Forecast Center (MARFC). For this region, wind hindcasts generated from Global Ensemble Forecast System (GEFS) are downscaled and corrected using digital elevation model and National Land Cover Database; observations from ASOS serve both as the predictands for establishing the relationship, and as the reference for validation. Our results showed that this framework considerably enhance the quality of wind forecast, with Nash-Sutcliffe efficiency of the downscaled wind speed improved by 0.2 - 0.4 relative to raw GEFS forecast.

  14. Forecasting the Brazilian real and the Mexican peso: Asymmetric loss, forecast rationality, and forecaster herding

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Fritsche, Ulrich; Pierdzioch, Christian

    2015-01-01

    Using forecasts of exchange rates of the Brazilian real and the Mexican peso against the US dollar, we analyze the symmetry of the loss function of exchange-rate forecasters and the rationality of their forecasts. Symmetry of the loss function can be rejected for some forecasters but not all. Even...... when allowing for asymmetric loss functions, the predictions of some forecasters do not fit the traditional definition of rational forecasts. We interpret our results in terms of recent research on forecaster (anti-)herding....

  15. 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 ......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...

  16. Forecasting scintillation activity and equatorial spread F

    Science.gov (United States)

    Anderson, David N.; Redmon, Robert J.

    2017-03-01

    When transionospheric radio waves propagate through an irregular ionosphere with plasma depletions or "bubbles," they are subject to sporadic enhancement and fading, which is referred to as scintillation. Communication and navigation systems may be subject to these detrimental effects if the scintillation is strong enough. It is critical to have knowledge of the current ionospheric conditions so that system operators can distinguish between the natural radio environment and system-induced failures. In this paper we briefly describe the Forecasting Ionospheric Real-time Scintillation Tool UHF scintillation forecasting technique, which utilizes the observed characteristic parameter h'F from a ground-based, ionospheric sounder near the magnetic equator. The prereversal enhancement in vertical E × B drift velocity after sunset is the prime driver for creating plasma depletions and bubbles. In addition, there exists a "threshold" in the h'F value at 1930 LT, h'Fthr, such that, on any given evening, if h'F is significantly above h'Fthr, then scintillation activity is likely to occur, and if it is below h'Fthr, scintillation activity is unlikely to occur. We use this technique to explain the lack of scintillation activity prior to the Halloween storm in October 2003 in the Peruvian longitude sector. In addition, we have carried out a study which forecasts the occurrence or nonoccurrence of equatorial spread F (ESF), on a night-to-night basis, in five longitude sectors. The overall forecasting success is greater than 80% for each of the five longitude sectors.

  17. Heat transfer analysis of fractional second-grade fluid subject to Newtonian heating with Caputo and Caputo-Fabrizio fractional derivatives: A comparison

    Science.gov (United States)

    Asjad, Muhammad Imran; Shah, Nehad Ali; Aleem, Maryam; Khan, Ilyas

    2017-08-01

    The present study is a comparative analysis of unsteady flows of a second-grade fluid with Newtonian heating and time-fractional derivatives, namely, the Caputo fractional derivative (singular kernel) and the Caputo-Fabrizio fractional derivative (non-singular kernel). A physical model for second-grade fluids is developed with fractional derivatives. The expressions for temperature and velocity fields in dimensionless form as well as rates of heat transfer are determined by means of the Laplace transform technique. Solutions for ordinary cases corresponding to integer order derivatives are also obtained. Numerical computations for a comparison between the solutions of the problem with the Caputo time-fractional derivative, problem with Caputo-Fabrizio time-fractional derivative and of the ordinary fluid problem were made. The influence of some flow parameters and fractional parameter α on temperature field as well as velocity field was presented graphically and in tabular forms.

  18. 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.)

  19. Forecasting cyanobacteria dominance in Canadian temperate lakes.

    Science.gov (United States)

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

    2015-03-15

    Predictive models based on broad scale, spatial surveys typically identify nutrients and climate as the most important predictors of cyanobacteria abundance; however these models generally have low predictive power because at smaller geographic scales numerous other factors may be equally or more important. At the lake level, for example, the ability to forecast cyanobacteria dominance is of tremendous value to lake managers as they can use such models to communicate exposure risks associated with recreational and drinking water use, and possible exposure to algal toxins, in advance of bloom occurrence. We used detailed algal, limnological and meteorological data from two temperate lakes in south-central Ontario, Canada to determine the factors that are closely linked to cyanobacteria dominance, and to develop easy to use models to forecast cyanobacteria biovolume. For Brandy Lake (BL), the strongest and most parsimonious model for forecasting % cyanobacteria biovolume (% CB) included water column stability, hypolimnetic TP, and % cyanobacteria biovolume two weeks prior. For Three Mile Lake (TML), the best model for forecasting % CB included water column stability, hypolimnetic TP concentration, and 7-d mean wind speed. The models for forecasting % CB in BL and TML are fundamentally different in their lag periods (BL = lag 1 model and TML = lag 2 model) and in some predictor variables despite the close proximity of the study lakes. We speculate that three main factors (nutrient concentrations, water transparency and lake morphometry) may have contributed to differences in the models developed, and may account for variation observed in models derived from large spatial surveys. Our results illustrate that while forecast models can be developed to determine when cyanobacteria will dominate within two temperate lakes, the models require detailed, lake-specific calibration to be effective as risk-management tools. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Olympian weather forecasting

    Science.gov (United States)

    Showstack, Randy

    A unique public-private partnership will provide detailed weather information at the 2002 Winter Olympics in Utah, 8-24 February About 50 meteorologists with the National Weather Service (NWS) and several private groups will work in the background to provide accurate forecasts.This is the first time that U.S. government and private meteorologists will share forecasting responsibilities for the Olympics, according to the Salt Lake Organizing Committee for the Olympic Games. The partnership includes meteorologists with the University of Utah and KSL-TV in Salt Lake City.

  1. Combining forecasts in short term load forecasting: Empirical ...

    Indian Academy of Sciences (India)

    We present an empirical analysis to show that combination of short term load forecasts leads to better accuracy. We also discuss other aspects of combination, i.e.,distribution of weights, effect of variation in the historical window and distribution of forecast errors. The distribution of forecast errors is analyzed in order to get a ...

  2. Survey Forecasts and Money Demand Functions: Some International Evidence

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch, Christian; Rülke, Jan

    2011-01-01

    We derive a money demand function from a dynamic macroeconomic general equilibrium model to analyze the correlations between professional economists’ forecasts of the growth rate of money supply, the inflation rate, the growth rate of real output, and the nominal interest rate. Upon estimating...... the money demand function on survey data of professional economists’ forecasts for fourteen Asian-Pacific and Central and South-Eastern European countries, we find that the correlations between professional economists’ forecasts are broadly consistent with the money demand function implied...

  3. Persistent forecasting of disruptive technologies

    National Research Council Canada - National Science Library

    Committee on Forecasting Future Disruptive Technologies; National Research Council

    ...) and the Defense Intelligence Agency (DIA) tasked the Committee for Forecasting Future Disruptive Technologies with providing guidance and insight on how to build a persistent forecasting system to predict, analyze, and reduce the impact...

  4. 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...

  5. Functional dynamic factor models with application to yield curve forecasting

    OpenAIRE

    Hays, Spencer; Shen, Haipeng; Huang, Jianhua Z.

    2012-01-01

    Accurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM wit...

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

    Directory of Open Access Journals (Sweden)

    M. Rautenhaus

    2015-07-01

    Full Text Available We present the application of interactive three-dimensional (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 (THORPEX – North Atlantic Waveguide and Downstream Impact Experiment campaign, a method to predict 3-D probabilities of the spatial occurrence of warm conveyor belts (WCBs has been developed. Probabilities are derived from Lagrangian particle trajectories computed on the forecast wind fields of the European Centre for Medium Range Weather Forecasts (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 grid spacing of the forecast wind field. 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 (3 to 7 days before take-off.

  7. Operational seasonal forecast system development in South Africa

    CSIR Research Space (South Africa)

    Landman, WA

    2011-09-01

    Full Text Available -Normal Above-Normal New objective multi-model forecast Old subjective consensus forecast MOS post-processing and forecast combination Multi-model ensemble of N1+N2+N3+N4 +N5 +N6 +N7 +N8 +N9 members Ensemble 1 CCAM at CSIR NRE N1 members Ensemble 2... ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?? Example of coupled model work: The state-of-the-art Coupled GCM Implementation: ? ? Coupling procedure: ? ? ? ? Initialization strategy: ? Initialized using best available information of the ocean and atmosphere state ? Each hindcast run...

  8. Forecasting long memory time series under a break in persistence

    DEFF Research Database (Denmark)

    Heinen, Florian; Sibbertsen, Philipp; Kruse, Robinson

    of this effect depends on whether the memory parameter is increasing or decreasing over time. A comparison of six forecasting strategies allows us to conclude that pre-testing for a change in persistence is highly recommendable in our setting. In addition we provide an empirical example which underlines......We consider the problem of forecasting time series with long memory when the memory parameter is subject to a structural break. By means of a large-scale Monte Carlo study we show that ignoring such a change in persistence leads to substantially reduced forecasting precision. The strength...

  9. Forecasts: uncertain, inaccurate and biased?

    DEFF Research Database (Denmark)

    Nicolaisen, Morten Skou; Ambrasaite, Inga; Salling, Kim Bang

    2012-01-01

    of construction costs, which account for the majority of total project costs. Second are the forecasts of travel time savings, which account for the majority of total project benefits. The latter of these is, inter alia, determined by forecasts of travel demand, which we shall use as a proxy for the forecasting...

  10. GEOS-5 seasonal forecast system

    Science.gov (United States)

    Borovikov, Anna; Cullather, Richard; Kovach, Robin; Marshak, Jelena; Vernieres, Guillaume; Vikhliaev, Yury; Zhao, Bin; Li, Zhao

    2017-09-01

    Ensembles of numerical forecasts based on perturbed initial conditions have long been used to improve estimates of both weather and climate forecasts. The Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model, Version 5 (GEOS-5 AOGCM) Seasonal-to-Interannual Forecast System has been used routinely by the GMAO since 2008, the current version since 2012. A coupled reanalysis starting in 1980 provides the initial conditions for the 9-month experimental forecasts. Once a month, sea surface temperature from a suite of 11 ensemble forecasts is contributed to the North American Multi-Model Ensemble (NMME) consensus project, which compares and distributes seasonal forecasts of ENSO events. Since June 2013, GEOS-5 forecasts of the Arctic sea-ice distribution were provided to the Sea-Ice Outlook project. The seasonal forecast output data includes surface fields, atmospheric and ocean fields, as well as sea ice thickness and area, and soil moisture variables. The current paper aims to document the characteristics of the GEOS-5 seasonal forecast system and to highlight forecast biases and skills of selected variables (sea surface temperature, air temperature at 2 m, precipitation and sea ice extent) to be used as a benchmark for the future GMAO seasonal forecast systems and to facilitate comparison with other global seasonal forecast systems.

  11. Evolving forecasting classifications and applications in health forecasting

    Science.gov (United States)

    Soyiri, Ireneous N; Reidpath, Daniel D

    2012-01-01

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

  12. The Effect of Music on the Test Scores of the Students in Limits and Derivatives Subject in the Mathematics Exams Done with Music

    Science.gov (United States)

    Kesan, Cenk; Ozkalkan, Zuhal; Iric, Hamdullah; Kaya, Deniz

    2012-01-01

    In the exams based on limits and derivatives, in this study, it was tried to determine that if there was any difference in students' test scores according to the type of music listened to and environment without music. For this purpose, the achievement test including limits and derivatives and whose reliability coefficient of Cronbach Alpha is…

  13. Forecasting freight flows

    DEFF Research Database (Denmark)

    Lyk-Jensen, Stéphanie

    2011-01-01

    model. The analysis uses a structural relationship to explain the structure of the exchange of the goods—a relationship that can be used in the year of forecast. This article also provides a new methodology for converting monetary aggregates into quantity aggregates. The resulting commodity growth rates...

  14. Forecasters' Objectives and Strategies

    DEFF Research Database (Denmark)

    Marinovic, Iván; Ottaviani, Marco; Sørensen, Peter Norman

    2013-01-01

    This chapter develops a unified modeling framework for analyzing the strategic behavior of forecasters. The theoretical model encompasses reputational objectives, competition for the best accuracy, and bias. Also drawing from the extensive lit- erature on analysts, we review the empirical evidenc...

  15. Peak Wind Tool for General Forecasting

    Science.gov (United States)

    Barrett, Joe H., III

    2010-01-01

    again by six years, from October 1996 to April 2002, by interpolating 1000-ft sounding data to 100-ft increments. The Phase II developmental data set included observations for the cool season months of October 1996 to February 2007. The AMU calculated 68 candidate predictors from the XMR soundings, to include 19 stability parameters, 48 wind speed parameters and one wind shear parameter. Each day in the data set was stratified by synoptic weather pattern, low-level wind direction, precipitation and Richardson Number, for a total of 60 stratification methods. Linear regression equations, using the 68 predictors and 60 stratification methods, were created for the tool's three forecast parameters: the highest peak wind speed of the day (PWSD), 5-minute average speed at the same time (A WSD), and timing of the PWSD. For PWSD and A WSD, 30 Phase II methods were selected for evaluation in the verification data set. For timing of the PWSD, 12 Phase\\I methods were selected for evaluation. The verification data set contained observations for the cool season months of March 2007 to April 2009. The data set was used to compare the Phase I and II forecast methods to climatology, model forecast winds and wind advisories issued by the 45 WS. The model forecast winds were derived from the 0000 and 1200 UTC runs of the 12-km North American Mesoscale (MesoNAM) model. The forecast methods that performed the best in the verification data set were selected for the Phase II version of the tool. For PWSD and A WSD, linear regression equations based on MesoNAM forecasts performed significantly better than the Phase I and II methods. For timing of the PWSD, none of the methods performed significantly bener than climatology. The AMU then developed the Microsoft Excel and MIDDS GUls. The GUIs display the forecasts for PWSD, AWSD and the probability the PWSD will meet or exceed 25 kt, 35 kt and 50 kt. Since none of the prediction methods for timing of the PWSD performed significantly better

  16. Indium-labelled human gut-derived T cells from healthy subjects with strong in vitro adhesion to MAdCAM-1 show no detectable homing to the gut in vivo

    DEFF Research Database (Denmark)

    Rømer, Johanne Lade

    2004-01-01

    assay. We studied the homing pattern after autologous infusion of 3 x 10(8 111)Indium ((111)In)-labelled T cells in five healthy subjects using scintigraphic imaging. The cultured CD4(+)CD45RO(+) gut-derived T cells express higher levels of integrin alpha4beta 7 than peripheral blood lymphocytes (PBLs...

  17. Skill prediction of local weather forecasts based on the ECMWF ensemble

    Directory of Open Access Journals (Sweden)

    C. Ziehmann

    2001-01-01

    Full Text Available Ensemble Prediction has become an essential part of numerical weather forecasting. In this paper we investigate the ability of ensemble forecasts to provide an a priori estimate of the expected forecast skill. Several quantities derived from the local ensemble distribution are investigated for a two year data set of European Centre for Medium-Range Weather Forecasts (ECMWF temperature and wind speed ensemble forecasts at 30 German stations. The results indicate that the population of the ensemble mode provides useful information for the uncertainty in temperature forecasts. The ensemble entropy is a similar good measure. This is not true for the spread if it is simply calculated as the variance of the ensemble members with respect to the ensemble mean. The number of clusters in the C regions is almost unrelated to the local skill. For wind forecasts, the results are less promising.

  18. Load forecasting for supermarket refrigeration

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Aalborg Nielsen, Henrik

    This report presents a study of models for forecasting the load for supermarket refrigeration. The data used for building the forecasting models consists of load measurements, local climate measurements and weather forecasts. The load measurements are from a supermarket located in a village...... in Denmark. The load for refrigeration is the sum of all cabinets in the supermarket, both low and medium temperature cabinets, and spans a period of one year. As input to the forecasting models the ambient temperature observed near the supermarket together with weather forecasts are used. Every hour...... the hourly load for refrigeration for the following 42 hours is forecasted. The forecast models are adaptive linear time-series models which are fitted with a computationally efficient recursive least squares scheme. The dynamic relations between the inputs and the load is modeled by simple transfer...

  19. Forecasting Long-Term Crude Oil Prices Using a Bayesian Model with Informative Priors

    Directory of Open Access Journals (Sweden)

    Chul-Yong Lee

    2017-01-01

    Full Text Available In the long-term, crude oil prices may impact the economic stability and sustainability of many countries, especially those depending on oil imports. This study thus suggests an alternative model for accurately forecasting oil prices while reflecting structural changes in the oil market by using a Bayesian approach. The prior information is derived from the recent and expected structure of the oil market, using a subjective approach, and then updated with available market data. The model includes as independent variables factors affecting oil prices, such as world oil demand and supply, the financial situation, upstream costs, and geopolitical events. To test the model’s forecasting performance, it is compared with other models, including a linear ordinary least squares model and a neural network model. The proposed model outperforms on the forecasting performance test even though the neural network model shows the best results on a goodness-of-fit test. The results show that the crude oil price is estimated to increase to $169.3/Bbl by 2040.

  20. What is the relative role of initial hydrological conditions and meteorological forcing to the seasonal hydrological forecasting skill? Analysis along Europe's hydro-climatic gradient

    Science.gov (United States)

    Pechlivanidis, Ilias; Crochemore, Louise

    2017-04-01

    Recent advances in understanding and forecasting of climate have led into skilful seasonal meteorological predictions, which can consequently increase the confidence of hydrological prognosis. The majority of seasonal impact modelling has commonly been conducted at only one or a limited number of basins limiting the potential to understand large systems. Nevertheless, there is a necessity to develop operational seasonal forecasting services at the pan-European scale, capable of addressing the end-user needs. The skill of such forecasting services is subject to a number of sources of uncertainty, i.e. model structure, parameters, and forcing input. In here, we complement the "deep" knowledge from basin based modelling by investigating the relative contributions of initial hydrological conditions (IHCs) and meteorological forcing (MF) to the skill of a seasonal pan-European hydrological forecasting system. We use the Ensemble Streamflow Prediction (ESP) and reverse ESP (revESP) procedure to show a proxy of hydrological forecasting uncertainty due to MF and IHC uncertainties respectively. We further calculate the critical lead time (CLT), as a proxy of the river memory, after which the importance of MFs surpasses the importance of IHCs. We analyze these results in the context of prevailing hydro-climatic conditions for about 35000 European basins. Both model state initialisation (level in surface water, i.e. reservoirs, lakes and wetlands, soil moisture, snow depth) and provision of climatology are based on forcing input derived from the WFDEI product for the period 1981-2010. The analysis shows that the contribution of ICs and MFs to the hydrological forecasting skill varies considerably according to location, season and lead time. This analysis allows clustering of basins in which hydrological forecasting skill may be improved by better estimation of IHCs, e.g. via data assimilation of in-situ and/or satellite observations; whereas in other basins skill improvement

  1. Methodical bases of geodemographic forecasting

    Directory of Open Access Journals (Sweden)

    Катерина Сегіда

    2016-10-01

    Full Text Available The article deals with methodological features of the forecast of population size and composition. The essence and features of probabilistic demographic forecasting, methods, a component and dynamic ranks are considered; requirements to initial indicators for each type of the forecast are provided. It is noted that geo-demographic forecast is an important component of regional geo-demographic characteristic. Features of the demographic forecast development by component method (recursors of age are given, basic formulae of calculation, including the equation of demographic balance, a formula recursors taking into account gender and age indicators, survival coefficient are presented. The basic methodical principles of the demographic forecast are given by an extrapolation method (dynamic ranks, calculation features by means of the generalized indicators, such as extrapolation on the basis of indicators of an average pure gain, average growth rate and average rate of a gain are presented. To develop population forecast, the method of retrospective extrapolation (for the short-term forecast and a component method (for the mid-term forecast are mostly used. The example of such development by component method for gender and age structure of the population of Kharkiv region with step-by-step explanation of calculation is provided. The example of Kharkiv region’s population forecast development is provided by the method of dynamic ranks. Having carried out calculations of the main forecast indicators by administrative units, it is possible to determine features of further regional demographic development, to reveal internal territorial distinctions in demographic development. Application of separate forecasting methods allows to develop the forecast for certain indicators, however essential a variety, nonlinearity and not stationarity of the processes constituting demographic development forces to look +for new approaches and

  2. An experimental system for flood risk forecasting at global scale

    Science.gov (United States)

    Alfieri, L.; Dottori, F.; Kalas, M.; Lorini, V.; Bianchi, A.; Hirpa, F. A.; Feyen, L.; Salamon, P.

    2016-12-01

    Global flood forecasting and monitoring systems are nowadays a reality and are being applied by an increasing range of users and practitioners in disaster risk management. Furthermore, there is an increasing demand from users to integrate flood early warning systems with risk based forecasts, combining streamflow estimations with expected inundated areas and flood impacts. To this end, we have developed an experimental procedure for near-real time flood mapping and impact assessment based on the daily forecasts issued by the Global Flood Awareness System (GloFAS). The methodology translates GloFAS streamflow forecasts into event-based flood hazard maps based on the predicted flow magnitude and the forecast lead time and a database of flood hazard maps with global coverage. Flood hazard maps are then combined with exposure and vulnerability information to derive flood risk. Impacts of the forecasted flood events are evaluated in terms of flood prone areas, potential economic damage, and affected population, infrastructures and cities. To further increase the reliability of the proposed methodology we integrated model-based estimations with an innovative methodology for social media monitoring, which allows for real-time verification of impact forecasts. The preliminary tests provided good results and showed the potential of the developed real-time operational procedure in helping emergency response and management. In particular, the link with social media is crucial for improving the accuracy of impact predictions.

  3. Forecasting carbon dioxide emissions.

    Science.gov (United States)

    Zhao, Xiaobing; Du, Ding

    2015-09-01

    This study extends the literature on forecasting carbon dioxide (CO2) emissions by applying the reduced-form econometrics approach of Schmalensee et al. (1998) to a more recent sample period, the post-1997 period. Using the post-1997 period is motivated by the observation that the strengthening pace of global climate policy may have been accelerated since 1997. Based on our parameter estimates, we project 25% reduction in CO2 emissions by 2050 according to an economic and population growth scenario that is more consistent with recent global trends. Our forecasts are conservative due to that we do not have sufficient data to fully take into account recent developments in the global economy. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Methods of Technological Forecasting,

    Science.gov (United States)

    1977-05-01

    i dh dt e ’ ve ’ lccp isie ’u i ( s trLttegv , LI ( ietwork ucf pcc ’.st hile SI/uges ,utuc l s teps ts uisLuppc’ dh , Ic c d c termui iuue (he opt...to use its tiny e’irc u mt u ss( L utu c ’e’s will ele ’pe’usc l upoui (lie purpcmse’ ( ‘t im w h ich (hue lonc’cL mst is mu LIdIc ’ Lltid h (lie in...L . Perspecti ve Tru e’. Met/ mod Jor (‘real ively Us/p ig Forecasts. ‘fechnological Forecasting and Social Change . No.4 . 1973. Gerardin , L. Studi

  5. Forecasting military expenditure

    Directory of Open Access Journals (Sweden)

    Tobias Böhmelt

    2014-05-01

    Full Text Available To what extent do frequently cited determinants of military spending allow us to predict and forecast future levels of expenditure? The authors draw on the data and specifications of a recent model on military expenditure and assess the predictive power of its variables using in-sample predictions, out-of-sample forecasts and Bayesian model averaging. To this end, this paper provides guidelines for prediction exercises in general using these three techniques. More substantially, however, the findings emphasize that previous levels of military spending as well as a country’s institutional and economic characteristics particularly improve our ability to predict future levels of investment in the military. Variables pertaining to the international security environment also matter, but seem less important. In addition, the results highlight that the updated model, which drops weak predictors, is not only more parsimonious, but also slightly more accurate than the original specification.

  6. Ensemble global ocean forecasting

    Science.gov (United States)

    Brassington, G. B.

    2016-02-01

    A novel time-lagged ensemble system based on multiple independent cycles has been performed in operations at the Australian Bureau of Meteorology for the past 3 years. Despite the use of only four cycles the ensemble mean provided robustly higher skill and the ensemble variance was a reliable predictor of forecast errors. A spectral analysis comparing the ensemble mean with the members demonstrated the gradual increase in power of random errors with wavenumber up to a saturation length scale imposed by the resolution of the observing system. This system has been upgraded to a near-global 0.1 degree system in a new hybrid six-member ensemble system configuration including a new data assimilation system, cycling pattern and initialisation. The hybrid system consists of two ensemble members per day each with a 3 day cycle. We will outline the performance of both the deterministic and ensemble ocean forecast system.

  7. 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...... accumulations, which have not been seen in observations. In addition to the model evaluation we were able to investigate the potential occurrence of ice induced power loss at two wind parks in Europe using observed data. We found that the potential loss during an icing event is large even when the turbine...

  8. Forecasting Turbine Icing Events

    DEFF Research Database (Denmark)

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

    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...... accumulations, which have not been seen in observations. In addition to the model evaluation we were able to investigate the potential occurrence of ice induced power loss at two wind parks in Europe using observed data. We found that the potential loss during an icing event is large even when the turbine...

  9. 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......, the most sustainable innovation stems from the dialogical interaction between practitioner foresight and societal forecasting, requiring continued development of participatory design as it moves into new contexts....... of an ongoing project. We examine the nature of participation in design on three levels: in the sterilization ward, this particular project and society in general. From our case, we suggest that while innovation projects proceeding from a certain technological perspective can succeed at building excitement...

  10. Analysing UK real estate market forecast disagreement

    OpenAIRE

    McAllister, Patrick; Newell, G.; Matysiak, George

    2005-01-01

    Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters, these real estate forecasts are compared with actual real estate performance to assess a number of real estate forecasting issues in the UK over 1999-2004, including real estate forecast error, bias and consensus. The re...

  11. 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 ...

  12. PyForecastTools

    Energy Technology Data Exchange (ETDEWEB)

    2017-09-22

    The PyForecastTools package provides Python routines for calculating metrics for model validation, forecast verification and model comparison. For continuous predictands the package provides functions for calculating bias (mean error, mean percentage error, median log accuracy, symmetric signed bias), and for calculating accuracy (mean squared error, mean absolute error, mean absolute scaled error, normalized RMSE, median symmetric accuracy). Convenience routines to calculate the component parts (e.g. forecast error, scaled error) of each metric are also provided. To compare models the package provides: generic skill score; percent better. Robust measures of scale including median absolute deviation, robust standard deviation, robust coefficient of variation and the Sn estimator are all provided by the package. Finally, the package implements Python classes for NxN contingency tables. In the case of a multi-class prediction, accuracy and skill metrics such as proportion correct and the Heidke and Peirce skill scores are provided as object methods. The special case of a 2x2 contingency table inherits from the NxN class and provides many additional metrics for binary classification: probability of detection, probability of false detection, false alarm ration, threat score, equitable threat score, bias. Confidence intervals for many of these quantities can be calculated using either the Wald method or Agresti-Coull intervals.

  13. Evolving forecasting classifications and applications in health forecasting

    Directory of Open Access Journals (Sweden)

    Soyiri IN

    2012-05-01

    Full Text Available Ireneous N Soyiri1,2, Daniel D Reidpath11Global Public Health, JCSMHS, MONASH University, Selangor, Malaysia; 2School of Public Health, University of Ghana, Legon, Accra, GhanaAbstract: Health forecasting forewarns the health community about future health situations and disease episodes so that health systems can better allocate resources and manage demand. The tools used for developing and measuring the accuracy and validity of health forecasts commonly are not defined although they are usually adapted forms of statistical procedures. This review identifies previous typologies used in classifying the forecasting methods commonly used in forecasting health conditions or situations. It then discusses the strengths and weaknesses of these methods and presents the choices available for measuring the accuracy of health-forecasting models, including a note on the discrepancies in the modes of validation.Keywords: health forecast, health data, electronic health records, accuracy, cross validation, method, strengths and limitations

  14. Modelling data uncertainty in growth forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Karmeshu; Lara-Rosano, F.

    1987-02-01

    A probabilistic methodology within a dynamic framework is proposed for the study of moments of errors in growth forecasts resulting from data uncertainty. This methodology is applied to well-known evolutionary models of growth, namely exponential and logistic. Explicit expressions for moments of the stochastic variable are derived. The paper explores methods based on two-point distribution approach, second-moment analysis, and probability distribution of parameters. Of these, the two-point distribution is found to be computationally advantageous. An interesting feature emerging from the analysis is that the mean and relative fluctuations in the projected variable of interest are numerically not much different from the respective ones when the uncertainties in the growth parameters are characterized by Gaussian, uniform or two-point distribution. This, however, holds for forecasting periods which are short in comparison with the time-scale of the process under study. 17 refs. (authors).

  15. Electricity price forecasting accounting for renewable energies: optimal combined forecasts

    OpenAIRE

    García-Martos, Carolina; Caro Huertas, Eduardo; Sánchez Naranjo, María Jesús

    2015-01-01

    Electricity price forecasting is an interesting problem for all the agents involved in electricity market operation. For instance, every profit maximisation strategy is based on the computation of accurate one-day-ahead forecasts, which is why electricity price forecasting has been a growing field of research in recent years. In addition, the increasing concern about environmental issues has led to a high penetration of renewable energies, particularly wind. In some European countries such as...

  16. A Brand New CROLEI: Do We Need a New Forecasting Index?

    Directory of Open Access Journals (Sweden)

    Katarina Bačić

    2006-12-01

    Full Text Available The aim of this paper is to determine whether the existing leading indicators system CROLEI (CROatian Leading Economic Indicators and its derivative, the CROLEI forecasting index, predict overall Croatian economic activity reliably. The need to evaluate the CROLEI system and the index stems from the modification of the barometric method on which the system and the index are founded on in its application in Croatia. The evaluation of the forecasting power involved the construction of six alternative forecasting indices, which not only challenge the original CROLEI index, but also enable comparisons of forecasting power. The construction of the alternative forecasting indices is also based on the barometric method. The authors then proceed to adjust more complex measurements i.e. forecasting power evaluation matrix, in order to obtain credible forecasting power estimates. Forecasting power is also estimated using two regression models that allow for the forecasting of reference series and yield measurements of forecasting power. The results of both approaches indicate not only that the original CROLEI has by far the greatest forecasting power, but also that it is able to predict the turning points in the economic cycle with the highest probability.

  17. EU pharmaceutical expenditure forecast

    Science.gov (United States)

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

    2014-01-01

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

  18. Frost Monitoring and Forecasting Using MODIS Land Surface Temperature Data and a Numerical Weather Prediction Model Forecasts for Eastern Africa

    Science.gov (United States)

    Kabuchanga, Eric; Flores, Africa; Malaso, Susan; Mungai, John; Sakwa, Vincent; Shaka, Ayub; Limaye, Ashutosh

    2014-01-01

    Frost is a major challenge across Eastern Africa, severely impacting agricultural farms. Frost damages have wide ranging economic implications on tea and coffee farms, which represent a major economic sector. Early monitoring and forecasting will enable farmers to take preventive actions to minimize the losses. Although clearly important, timely information on when to protect crops from freezing is relatively limited. MODIS Land Surface Temperature (LST) data, derived from NASA's Terra and Aqua satellites, and 72-hr weather forecasts from the Kenya Meteorological Service's operational Weather Research Forecast model are enabling the Regional Center for Mapping of Resources for Development (RCMRD) and the Tea Research Foundation of Kenya to provide timely information to farmers in the region. This presentation will highlight an ongoing collaboration among the Kenya Meteorological Service, RCMRD, and the Tea Research Foundation of Kenya to identify frost events and provide farmers with potential frost forecasts in Eastern Africa.

  19. Towards Developing a Travel Time Forecasting Model for Location-Based Services: a Review

    OpenAIRE

    You, Jinsoo; Kim, Tschangho John

    2003-01-01

    Travel time forecasting models have been studied intensively as a subject of Intelligent Transportation Systems (ITS), particularly in the topics of advanced traffic management systems (ATMS), advanced traveler information systems (ATIS), and commercial vehicle operations (CVO). While the concept of travel time forecasting is relatively simple, it involves a notably complicated task of implementing even a simple model. Thus, existing forecasting models are diverse in their original formulatio...

  20. Probabilistic forecasting and Bayesian data assimilation

    CERN Document Server

    Reich, Sebastian

    2015-01-01

    In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in ap...

  1. Effects of therapeutic lifestyle change diets high and low in dietary fish-derived fatty acids on lipoprotein metabolism in middle-aged and elderly subjects

    Science.gov (United States)

    The effects of Therapeutic Lifestyle Change (TLC) diets, low and high in dietary fish on apolipoprotein metabolism were examined. Subjects were provided with a Western diet for 6-weeks followed by 24-weeks of either of two TLC diets (10/group). Apolipoprotein kinetics were determined in the fed stat...

  2. Influenza forecasting in human populations: a scoping review.

    Science.gov (United States)

    Chretien, Jean-Paul; George, Dylan; Shaman, Jeffrey; Chitale, Rohit A; McKenzie, F Ellis

    2014-01-01

    Forecasts of influenza activity in human populations could help guide key preparedness tasks. We conducted a scoping review to characterize these methodological approaches and identify research gaps. Adapting the PRISMA methodology for systematic reviews, we searched PubMed, CINAHL, Project Euclid, and Cochrane Database of Systematic Reviews for publications in English since January 1, 2000 using the terms "influenza AND (forecast* OR predict*)", excluding studies that did not validate forecasts against independent data or incorporate influenza-related surveillance data from the season or pandemic for which the forecasts were applied. We included 35 publications describing population-based (N = 27), medical facility-based (N = 4), and regional or global pandemic spread (N = 4) forecasts. They included areas of North America (N = 15), Europe (N = 14), and/or Asia-Pacific region (N = 4), or had global scope (N = 3). Forecasting models were statistical (N = 18) or epidemiological (N = 17). Five studies used data assimilation methods to update forecasts with new surveillance data. Models used virological (N = 14), syndromic (N = 13), meteorological (N = 6), internet search query (N = 4), and/or other surveillance data as inputs. Forecasting outcomes and validation metrics varied widely. Two studies compared distinct modeling approaches using common data, 2 assessed model calibration, and 1 systematically incorporated expert input. Of the 17 studies using epidemiological models, 8 included sensitivity analysis. This review suggests need for use of good practices in influenza forecasting (e.g., sensitivity analysis); direct comparisons of diverse approaches; assessment of model calibration; integration of subjective expert input; operational research in pilot, real-world applications; and improved mutual understanding among modelers and public health officials.

  3. Influenza Forecasting in Human Populations: A Scoping Review

    Science.gov (United States)

    Chretien, Jean-Paul; George, Dylan; Shaman, Jeffrey; Chitale, Rohit A.; McKenzie, F. Ellis

    2014-01-01

    Forecasts of influenza activity in human populations could help guide key preparedness tasks. We conducted a scoping review to characterize these methodological approaches and identify research gaps. Adapting the PRISMA methodology for systematic reviews, we searched PubMed, CINAHL, Project Euclid, and Cochrane Database of Systematic Reviews for publications in English since January 1, 2000 using the terms “influenza AND (forecast* OR predict*)”, excluding studies that did not validate forecasts against independent data or incorporate influenza-related surveillance data from the season or pandemic for which the forecasts were applied. We included 35 publications describing population-based (N = 27), medical facility-based (N = 4), and regional or global pandemic spread (N = 4) forecasts. They included areas of North America (N = 15), Europe (N = 14), and/or Asia-Pacific region (N = 4), or had global scope (N = 3). Forecasting models were statistical (N = 18) or epidemiological (N = 17). Five studies used data assimilation methods to update forecasts with new surveillance data. Models used virological (N = 14), syndromic (N = 13), meteorological (N = 6), internet search query (N = 4), and/or other surveillance data as inputs. Forecasting outcomes and validation metrics varied widely. Two studies compared distinct modeling approaches using common data, 2 assessed model calibration, and 1 systematically incorporated expert input. Of the 17 studies using epidemiological models, 8 included sensitivity analysis. This review suggests need for use of good practices in influenza forecasting (e.g., sensitivity analysis); direct comparisons of diverse approaches; assessment of model calibration; integration of subjective expert input; operational research in pilot, real-world applications; and improved mutual understanding among modelers and public health officials. PMID:24714027

  4. On the Influence of Weather Forecast Errors in Short-Term Load Forecasting Models

    OpenAIRE

    Fay, D.; Ringwood, John; Condon, M.

    2004-01-01

    Weather information is an important factor in load forecasting models. This weather information usually takes the form of actual weather readings. However, online operation of load forecasting models requires the use of weather forecasts, with associated weather forecast errors. A technique is proposed to model weather forecast errors to reflect current accuracy. A load forecasting model is then proposed which combines the forecasts of several load forecasting models. This approach allows the...

  5. Hydrologic Forecasting and Hydropower Production

    Science.gov (United States)

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

    2011-12-01

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

  6. Load forecasting of supermarket refrigeration

    DEFF Research Database (Denmark)

    Rasmussen, Lisa Buth; Bacher, Peder; Madsen, Henrik

    2016-01-01

    This paper presents a novel study of models for forecasting the electrical load for supermarket refrigeration. The data used for building the models consists of load measurements, local climate measurements and weather forecasts. The load measurements are from a supermarket located in a village...... in Denmark. Every hour the hourly electrical load for refrigeration is forecasted for the following 42 h. The forecast models are adaptive linear time series models. The model has two regimes; one for opening hours and one for closing hours, this is modeled by a regime switching model and two different...

  7. IEA Wind Task 36 Forecasting

    Science.gov (United States)

    Giebel, Gregor; Cline, Joel; Frank, Helmut; Shaw, Will; Pinson, Pierre; Hodge, Bri-Mathias; Kariniotakis, Georges; Sempreviva, Anna Maria; Draxl, Caroline

    2017-04-01

    Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Wind Power Forecasting tries to organise international collaboration, among national weather centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, UK MetOffice, …) and operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets for verification. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts aiming at industry and forecasters alike. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions, especially probabilistic ones. The Operating Agent is Gregor Giebel of DTU, Co-Operating Agent is Joel Cline of the US Department of Energy. Collaboration in the task is solicited from everyone interested in the forecasting business. We will collaborate with IEA Task 31 Wakebench, which developed the Windbench benchmarking platform, which this task will use for forecasting benchmarks. The task runs for three years, 2016-2018. Main deliverables are an up-to-date list of current projects and main project results, including datasets which can be used by researchers around the world to improve their own models, an IEA Recommended Practice on performance evaluation of probabilistic forecasts, a position paper regarding the use of probabilistic forecasts

  8. Solar Indices Forecasting Tool

    Science.gov (United States)

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

    2016-05-01

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

  9. Zinc monotherapy increases serum brain-derived neurotrophic factor (BDNF) levels and decreases depressive symptoms in overweight or obese subjects: a double-blind, randomized, placebo-controlled trial.

    Science.gov (United States)

    Solati, Zahra; Jazayeri, Shima; Tehrani-Doost, Mehdi; Mahmoodianfard, Salma; Gohari, Mahmood Reza

    2015-05-01

    Previous studies have shown a positive effect of zinc as an adjunctive therapy on reducing depressive symptoms. However, to our knowledge, no study has examined the effect of zinc monotherapy on mood. The aim of the present study was to determine the effects of zinc monotherapy on depressive symptoms and serum brain-derived neurotrophic factor (BDNF) levels in overweight or obese subjects. Fifty overweight or obese subjects were randomly assigned into two groups and received either 30 mg zinc or placebo daily for 12 weeks. At baseline and post-intervention, depression severity was assessed using Beck depression inventory II (BDI II), and serum BDNF and zinc levels were determined by enzyme-linked immunosorbent assay and atomic absorption spectrophotometry, respectively. The trial was completed with 46 subjects. After a 12-week supplementation, serum zinc and BDNF levels increased significantly in the zinc-supplemented group compared with the placebo group. BDI scores declined in both the groups at the end of the study, but reduction in the zinc-supplemented group was significantly higher than the placebo group. More analysis revealed that following supplementation, BDI scores decreased in subgroup of subjects with depressive symptoms (BDI ≥ 10) (n = 30), but did not change in the subgroup of non-depressed subjects (BDI BDNF levels and depression severity in all participants. Interestingly, a significant positive correlation was found between serum BDNF and zinc levels at baseline. Zinc monotherapy improves mood in overweight or obese subjects most likely through increasing BDNF levels.

  10. Utility usage forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Hosking, Jonathan R. M.; Natarajan, Ramesh

    2017-08-22

    The computer creates a utility demand forecast model for weather parameters by receiving a plurality of utility parameter values, wherein each received utility parameter value corresponds to a weather parameter value. Determining that a range of weather parameter values lacks a sufficient amount of corresponding received utility parameter values. Determining one or more utility parameter values that corresponds to the range of weather parameter values. Creating a model which correlates the received and the determined utility parameter values with the corresponding weather parameters values.

  11. Reference class forecasting

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent

    Underbudgettering og budgetoverskridelser forekommer i et flertal af større bygge- og anlægsprojekter. Problemet skyldes optimisme og/eller strategisk misinformation i budgetteringsprocessen. Reference class forecasting (RCF) er en prognosemetode, som er udviklet for at reducere eller eliminere...... projekterne er almindelige nationalt eller internationalt, er det muligt at etablere en reference-klasse af tilsvarende projekter og dermed alligevel opnå et pålideligt lokalt budget. Denne projekttype er relativt almindelig. RCF kan ikke anvendes på projekter som er reelt unikke, d.v.s. projekter for hvilke...

  12. Housing Price Forecastability

    DEFF Research Database (Denmark)

    Bork, Lasse; Møller, Stig Vinther

    2016-01-01

    We examine U.S. housing price forecastability using principal component analysis (PCA), partial least squares (PLS), and sparse PLS (SPLS). We incorporate information from a large panel of 128 economic time series and show that macroeconomic fundamentals have strong predictive power for future...... movements in housing prices. We find that (S)PLS models systematically dominate PCA models. (S)PLS models also generate significant out-of-sample predictive power over and above the predictive power contained by the price-rent ratio, autoregressive benchmarks, and regression models based on small datasets....

  13. Interactive Forecasting with the National Weather Service River Forecast System

    Science.gov (United States)

    Smith, George F.; Page, Donna

    1993-01-01

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

  14. Probabilistic forecasting using stochastic diffusion models, with applications to cohort processes of marriage and fertility.

    Science.gov (United States)

    Myrskylä, Mikko; Goldstein, Joshua R

    2013-02-01

    In this article, we show how stochastic diffusion models can be used to forecast demographic cohort processes using the Hernes, Gompertz, and logistic models. Such models have been used deterministically in the past, but both behavioral theory and forecast utility are improved by introducing randomness and uncertainty into the standard differential equations governing population processes. Our approach is to add time-series stochasticity to linearized versions of each process. We derive both Monte Carlo and analytic methods for estimating forecast uncertainty. We apply our methods to several examples of marriage and fertility, extending them to simultaneous forecasting of multiple cohorts and to processes restricted by factors such as declining fecundity.

  15. L-carnitine Effectively Induces hTERT Gene Expression of Human Adipose Tissue-derived Mesenchymal Stem Cells Obtained from the Aged Subjects

    Science.gov (United States)

    Farahzadi, Raheleh; Mesbah-Namin, Seyed Alireza; Zarghami, Nosratollah; Fathi, Ezzatollah

    2016-01-01

    Background and Objectives Human mesenchymal stem cells (hMSCs) are attractive candidates for cell therapy and regenerative medicine due to their multipotency and ready availability, but their application can be complicated by the factors such as age of the donors and senescence-associated growth arrest during culture conditions. The latter most likely reflects the fact that aging of hMSCs is associated with a rise in intracellular reactive oxygen species, loss of telomerase activity, decrease in human telomerase reverse transcriptase (hTERT) expression and finally eroded telomere ends. Over-expression of telomerase in hMSCs leads to telomere elongation and may help to maintain replicative life–span of these cells. The aim of this study was to evaluate of the effect of L-carnitine (LC) as an antioxidant on the telomerase gene expression and telomere length in aged adipose tissue-derived hMSCs. Methods For this purpose, cells were isolated from healthy aged volunteers and their viabilities were assessed by MTT assay. Quantitative gene expression of hTERT and absolute telomere length measurement were also performed by real-time PCR in the absence and presence of different doses of LC (0.1, 0.2 and 0.4 mM). Results The results indicated that LC could significantly increase the hTERT gene expression and telomere length, especially in dose of 0.2 mM of LC and in 48 h treatment for the aged adipose tissue-derived hMSCs samples. Conclusion It seems that LC would be a good candidate to improve the lifespan of the aged adipose tissue-derived hMSCs due to over-expression of telomerase and lengthening of the telomeres. PMID:27426092

  16. Rebuttal of "Polar bear population forecasts: a public-policy forecasting audit"

    Science.gov (United States)

    Amstrup, Steven C.; Caswell, Hal; DeWeaver, Eric; Stirling, Ian; Douglas, David C.; Marcot, Bruce G.; Hunter, Christine M.

    2009-01-01

    Observed declines in the Arctic sea ice have resulted in a variety of negative effects on polar bears (Ursus maritimus). Projections for additional future declines in sea ice resulted in a proposal to list polar bears as a threatened species under the United States Endangered Species Act. To provide information for the Department of the Interior's listing-decision process, the US Geological Survey (USGS) produced a series of nine research reports evaluating the present and future status of polar bears throughout their range. In response, Armstrong et al. [Armstrong, J. S., K. C. Green, W. Soon. 2008. Polar bear population forecasts: A public-policy forecasting audit. Interfaces 38(5) 382–405], which we will refer to as AGS, performed an audit of two of these nine reports. AGS claimed that the general circulation models upon which the USGS reports relied were not valid forecasting tools, that USGS researchers were not objective or lacked independence from policy decisions, that they did not utilize all available information in constructing their forecasts, and that they violated numerous principles of forecasting espoused by AGS. AGS (p. 382) concluded that the two USGS reports were "unscientific and inconsequential to decision makers." We evaluate the AGS audit and show how AGS are mistaken or misleading on every claim. We provide evidence that general circulation models are useful in forecasting future climate conditions and that corporate and government leaders are relying on these models to do so. We clarify the strict independence of the USGS from the listing decision. We show that the allegations of failure to follow the principles of forecasting espoused by AGS are either incorrect or are based on misconceptions about the Arctic environment, polar bear biology, or statistical and mathematical methods. We conclude by showing that the AGS principles of forecasting are too ambiguous and subjective to be used as a reliable basis for auditing scientific

  17. Improving Local Weather Forecasts for Agricultural Applications

    NARCIS (Netherlands)

    Doeswijk, T.G.; Keesman, K.J.

    2005-01-01

    For controlling agricultural systems, weather forecasts can be of substantial importance. Studies have shown that forecast errors can be reduced in terms of bias and standard deviation using forecasts and meteorological measurements from one specific meteorological station. For agricultural systems

  18. k36u 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. Global Ensemble Forecast System (GEFS) [1 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  20. The E-wave propagation index (EPI): A novel echocardiographic parameter for prediction of left ventricular thrombus. Derivation from computational fluid dynamic modeling and validation on human subjects.

    Science.gov (United States)

    Harfi, Thura T; Seo, Jung-Hee; Yasir, Hayder S; Welsh, Nathaniel; Mayer, Susan A; Abraham, Theodore P; George, Richard T; Mittal, Rajat

    2017-01-15

    To describe the derivation and validation of a novel echocardiographic metric for prediction of left ventricle thrombus (LVT). Computational fluid dynamic modeling using cardiac CT images was used to derive a novel echocardiography-based metric to predict the presence of LVT. We retrospectively reviewed 25 transthoracic echocardiograms showing definite LVT (LVT group). We then randomly selected 25 patients with LVEF ≥55% (Normal EF group) and 25 patients with severe cardiomyopathy (CMP) with LVEF ≤40% without evidence of LVT (CMP group). The E-wave Propagation Index (EPI) was measured as the E-wave velocity time-integral divided by the LV length. An EPI>1 indicates penetration of the mitral jet into the apex whereas an EPIEPI was compared between the three groups. Crude and adjusted odd ratios of EPI and LVT association were also measured. Mean EPI was highest for the normal EF group and lowest in the LVT group (1.7 vs. 0.8; pEPI also differed significantly between LVT and CMP groups (0.8 vs. 1.2; pEPI EPI EPI of less than 1 is an independent predictor of LVT formation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  1. Quality Metrics of Digitally Derived Imagery and Their Relation to Interpreter Performance. III. Subjective Scaling of Hard-Copy Digital Imagery.

    Science.gov (United States)

    1982-02-01

    tCnrv11nwo ort ieee,.. oad. It nereesrr and identitv , b , lock- etvr - - Hard-copy digital Imagery was studied witht respect to subjective imare quality...40 20. The eff.e- ct of Blur x Noise on NATO scale value, Scene 10 .......... ................... 4U 21. The relationship between stress...8217 LUJ S33- 2 3 4 5 6 7 8 9 IC SCENE Fi JlJr,2 5: The ef f ( ct o f Scene on NATO scale vilu- 131 jr x Noise . The Blur x Noise interaction is shown in

  2. Forecasting space weather: Can new econometric methods improve accuracy?

    Science.gov (United States)

    Reikard, Gordon

    2011-06-01

    Space weather forecasts are currently used in areas ranging from navigation and communication to electric power system operations. The relevant forecast horizons can range from as little as 24 h to several days. This paper analyzes the predictability of two major space weather measures using new time series methods, many of them derived from econometrics. The data sets are the A p geomagnetic index and the solar radio flux at 10.7 cm. The methods tested include nonlinear regressions, neural networks, frequency domain algorithms, GARCH models (which utilize the residual variance), state transition models, and models that combine elements of several techniques. While combined models are complex, they can be programmed using modern statistical software. The data frequency is daily, and forecasting experiments are run over horizons ranging from 1 to 7 days. Two major conclusions stand out. First, the frequency domain method forecasts the A p index more accurately than any time domain model, including both regressions and neural networks. This finding is very robust, and holds for all forecast horizons. Combining the frequency domain method with other techniques yields a further small improvement in accuracy. Second, the neural network forecasts the solar flux more accurately than any other method, although at short horizons (2 days or less) the regression and net yield similar results. The neural net does best when it includes measures of the long-term component in the data.

  3. Forecasting wind power production from a wind farm using the RAMS model

    DEFF Research Database (Denmark)

    Tiriolo, L.; Torcasio, R. C.; Montesanti, S.

    2015-01-01

    The importance of wind power forecast is commonly recognized because it represents a useful tool for grid integration and facilitates the energy trading. This work considers an example of power forecast for a wind farm in the Apennines in Central Italy. The orography around the site is complex...... and the horizontal resolution of the wind forecast has an important role. To explore this point we compared the performance of two 48 h wind power forecasts using the winds predicted by the Regional Atmospheric Modeling System (RAMS) for the year 2011. The two forecasts differ only for the horizontal resolution...... of the ECMWF Integrated Forecasting System (IFS), whose horizontal resolution over Central Italy is about 25 km at the time considered in this paper. Because wind observations were not available for the site, the power curve for the whole wind farm was derived from the ECMWF wind operational analyses available...

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

    Science.gov (United States)

    Richardson, Mathew

    2013-01-01

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

  5. (MRF) analysis-forecast system

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    Systematic and random error and their growth rate and different components of growth rate bud- get in energy/variance form are investigated at wavenumber domain for medium range tropical. (30◦S–30◦N) weather forecast using daily horizontal wind field of 850 hPa up to 5-day forecast for the month of June, 2000 of NCEP ...

  6. Forecasting Using Random Subspace Methods

    NARCIS (Netherlands)

    T. Boot (Tom); D. Nibbering (Didier)

    2016-01-01

    textabstractRandom subspace methods are a novel approach to obtain accurate forecasts in high-dimensional regression settings. We provide a theoretical justification of the use of random subspace methods and show their usefulness when forecasting monthly macroeconomic variables. We focus on two

  7. Regional-seasonal weather forecasting

    Energy Technology Data Exchange (ETDEWEB)

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

    1980-08-01

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

  8. Advances in time series forecasting

    CERN Document Server

    Cagdas, Hakan Aladag

    2012-01-01

    Readers will learn how these methods work and how these approaches can be used to forecast real life time series. The hybrid forecasting model is also explained. Data presented in this e-book is problem based and is taken from real life situations. It is a valuable resource for students, statisticians and working professionals interested in advanced time series analysis.

  9. Probabilistic Flash Flood Forecasting using Stormscale Ensembles

    Science.gov (United States)

    Hardy, J.; Gourley, J. J.; Kain, J. S.; Clark, A.; Novak, D.; Hong, Y.

    2013-12-01

    Flash flooding is one of the most costly and deadly natural hazards in the US and across the globe. The loss of life and property from flash floods could be mitigated with better guidance from hydrological models, but these models have limitations. For example, they are commonly initialized using rainfall estimates derived from weather radars, but the time interval between observations of heavy rainfall and a flash flood can be on the order of minutes, particularly for small basins in urban settings. Increasing the lead time for these events is critical for protecting life and property. Therefore, this study advances the use of quantitative precipitation forecasts (QPFs) from a stormscale NWP ensemble system into a distributed hydrological model setting to yield basin-specific, probabilistic flash flood forecasts (PFFFs). Rainfall error characteristics of the individual members are first diagnosed and quantified in terms of structure, amplitude, and location (SAL; Wernli et al., 2008). Amplitude and structure errors are readily correctable due to their diurnal nature, and the fine scales represented by the CAPS QPF members are consistent with radar-observed rainfall, mainly showing larger errors with afternoon convection. To account for the spatial uncertainty of the QPFs, we use an elliptic smoother, as in Marsh et al. (2012), to produce probabilistic QPFs (PQPFs). The elliptic smoother takes into consideration underdispersion, which is notoriously associated with stormscale ensembles, and thus, is good for targeting the approximate regions that may receive heavy rainfall. However, stormscale details contained in individual members are still needed to yield reasonable flash flood simulations. Therefore, on a case study basis, QPFs from individual members are then run through the hydrological model with their predicted structure and corrected amplitudes, but the locations of individual rainfall elements are perturbed within the PQPF elliptical regions using Monte

  10. Forecasting for dynamic line rating

    DEFF Research Database (Denmark)

    Michiorri, Andrea; Nguyen, Huu-Minh; Alessandrini, Stefano

    2015-01-01

    This paper presents an overview of the state of the art on the research on Dynamic Line Rating forecasting. It is directed at researchers and decision-makers in the renewable energy and smart grids domain, and in particular at members of both the power system and meteorological community. Its aim...... sensors on the line that measure conductor temperature, tension, sag or environmental parameters such as wind speed and air temperature. Because of the conservative assumptions used to calculate static seasonal ampacity limits and the variability of weather parameters, DLRs are considerably higher than....... In order to facilitate the integration of DLR into power system operations, research has been launched into DLR forecasting, following a similar avenue to IRS production forecasting, i.e. based on a mix of statistical methods and meteorological forecasts. The development of reliable DLR forecasts...

  11. Personalized glucose forecasting for type 2 diabetes using data assimilation.

    Science.gov (United States)

    Albers, David J; Levine, Matthew; Gluckman, Bruce; Ginsberg, Henry; Hripcsak, George; Mamykina, Lena

    2017-04-01

    and match or exceed in accuracy expert forecasts. We conclude by examining ways to present predictions as forecast-derived range quantities and evaluate the comparative advantages of these ranges.

  12. Drought forecasting in Luanhe River basin involving climatic indices

    Science.gov (United States)

    Ren, Weinan; Wang, Yixuan; Li, Jianzhu; Feng, Ping; Smith, Ronald J.

    2017-11-01

    Drought is regarded as one of the most severe natural disasters globally. This is especially the case in Tianjin City, Northern China, where drought can affect economic development and people's livelihoods. Drought forecasting, the basis of drought management, is an important mitigation strategy. In this paper, we evolve a probabilistic forecasting model, which forecasts transition probabilities from a current Standardized Precipitation Index (SPI) value to a future SPI class, based on conditional distribution of multivariate normal distribution to involve two large-scale climatic indices at the same time, and apply the forecasting model to 26 rain gauges in the Luanhe River basin in North China. The establishment of the model and the derivation of the SPI are based on the hypothesis of aggregated monthly precipitation that is normally distributed. Pearson correlation and Shapiro-Wilk normality tests are used to select appropriate SPI time scale and large-scale climatic indices. Findings indicated that longer-term aggregated monthly precipitation, in general, was more likely to be considered normally distributed and forecasting models should be applied to each gauge, respectively, rather than to the whole basin. Taking Liying Gauge as an example, we illustrate the impact of the SPI time scale and lead time on transition probabilities. Then, the controlled climatic indices of every gauge are selected by Pearson correlation test and the multivariate normality of SPI, corresponding climatic indices for current month and SPI 1, 2, and 3 months later are demonstrated using Shapiro-Wilk normality test. Subsequently, we illustrate the impact of large-scale oceanic-atmospheric circulation patterns on transition probabilities. Finally, we use a score method to evaluate and compare the performance of the three forecasting models and compare them with two traditional models which forecast transition probabilities from a current to a future SPI class. The results show that the

  13. Suppression cost forecasts in advance of wildfire seasons

    Science.gov (United States)

    Jeffrey P. Prestemon; Karen Abt; Krista Gebert

    2008-01-01

    Approaches for forecasting wildfire suppression costs in advance of a wildfire season are demonstrated for two lead times: fall and spring of the current fiscal year (Oct. 1–Sept. 30). Model functional forms are derived from aggregate expressions of a least cost plus net value change model. Empirical estimates of these models are used to generate advance-of-season...

  14. Short-term ensemble radar rainfall forecasts for hydrological applications

    Science.gov (United States)

    Codo de Oliveira, M.; Rico-Ramirez, M. A.

    2016-12-01

    Flooding is a very common natural disaster around the world, putting local population and economy at risk. Forecasting floods several hours ahead and issuing warnings are of main importance to permit proper response in emergency situations. However, it is important to know the uncertainties related to the rainfall forecasting in order to produce more reliable forecasts. Nowcasting models (short-term rainfall forecasts) are able to produce high spatial and temporal resolution predictions that are useful in hydrological applications. Nonetheless, they are subject to uncertainties mainly due to the nowcasting model used, errors in radar rainfall estimation, temporal development of the velocity field and to the fact that precipitation processes such as growth and decay are not taken into account. In this study an ensemble generation scheme using rain gauge data as a reference to estimate radars errors is used to produce forecasts with up to 3h lead-time. The ensembles try to assess in a realistic way the residual uncertainties that remain even after correction algorithms are applied in the radar data. The ensembles produced are compered to a stochastic ensemble generator. Furthermore, the rainfall forecast output was used as an input in a hydrodynamic sewer network model and also in hydrological model for catchments of different sizes in north England. A comparative analysis was carried of how was carried out to assess how the radar uncertainties propagate into these models. The first named author is grateful to CAPES - Ciencia sem Fronteiras for funding this PhD research.

  15. Advances in electric power and energy systems load and price forecasting

    CERN Document Server

    2017-01-01

    A comprehensive review of state-of-the-art approaches to power systems forecasting from the most respected names in the field, internationally. Advances in Electric Power and Energy Systems is the first book devoted exclusively to a subject of increasing urgency to power systems planning and operations. Written for practicing engineers, researchers, and post-grads concerned with power systems planning and forecasting, this book brings together contributions from many of the world’s foremost names in the field who address a range of critical issues, from forecasting power system load to power system pricing to post-storm service restoration times, river flow forecasting, and more. In a time of ever-increasing energy demands, mounting concerns over the environmental impacts of power generation, and the emergence of new, smart-grid technologies, electricity price forecasting has assumed a prominent role within both the academic and industrial ar nas. Short-run forecasting of electricity prices has become nece...

  16. Fel d 1-derived synthetic peptide immuno-regulatory epitopes show a long-term treatment effect in cat allergic subjects.

    Science.gov (United States)

    Couroux, P; Patel, D; Armstrong, K; Larché, M; Hafner, R P

    2015-05-01

    Cat-PAD, the first in a new class of synthetic peptide immuno-regulatory epitopes (SPIREs), was shown to significantly improve rhinoconjunctivitis symptoms in subjects with cat allergy up to 1 year after the start of a short course of treatment. To evaluate the long-term effects of Cat-PAD on rhinoconjunctivitis symptoms following standardized allergen challenge 2 years after treatment. In a randomized, double-blind, placebo-controlled, parallel group study, subjects were exposed to cat allergen in an environmental exposure chamber (EEC) before and after treatment with two regimens of Cat-PAD (either eight doses of 3 nmol or four doses of 6 nmol) given intradermally over a 3-month period. In this follow-up study, changes from baseline in rhinoconjunctivitis symptoms were reassessed 2 years after the start of treatment. The primary endpoint showed a mean reduction in total rhinoconjunctivitis symptom scores of 3.85 units in the 4 × 6 nmol Cat-PAD group compared to placebo 2 years after the start of treatment (P = 0.13), and this difference was statistically significant in the secondary endpoint at the end of day 4 when the cumulative allergen challenge was greatest (P = 0.02). Consistent reductions in nasal symptoms of between 2 and 3 units were observed for 4 × 6 nmol Cat-PAD compared to placebo between the 2 and 3 h time points on days 1-4 of EEC challenge at 2 years (P Cat-PAD. This study is the first to provide evidence of a long-term therapeutic effect with this new class of SPIREs. © 2015 The Authors. Clinical & Experimental Allergy Published by John Wiley & Sons Ltd.

  17. Assessment of Glomerular Filtration Rate Based on Alterations of Serum Brain-Derived Neurotrophic Factor in Type 2 Diabetic Subjects Treated with Amlodipine/Benazepril or Valsartan/Hydrochlorothiazide

    Directory of Open Access Journals (Sweden)

    I-Te Lee

    2015-01-01

    Full Text Available Background. Brain-derived neurotrophic factor (BDNF is associated with sympathetic activation. However, the effects of BDNF on diabetic nephropathy are unknown. The aim of this study was to assess the estimated glomerular filtration rates (eGFRs and changes in serum BDNF levels in type 2 diabetic subjects treated with antihypertensive medications. Methods. In this randomized, double-blind clinical trial, type 2 diabetic subjects with hypertension were assigned to either the benazepril/amlodipine or valsartan/hydrochlorothiazide treatment groups for a 16-week period. The post hoc analyses were based on increased or decreased serum BDNF levels. Results. Of the 153 enrolled subjects, the changes in eGFR were significantly and inversely correlated with those in BDNF in the 76 subjects treated with valsartan/hydrochlorothiazide (r=-0.264, P=0.021 but not in the 77 subjects treated with benazepril/amlodipine (r=-0.025, P=0.862. The 45 subjects with increased BDNF following valsartan/hydrochlorothiazide treatment exhibited a significantly reduced eGFR (-8.8±14.9 mL/min/1.73 m2; P<0.001. Multivariate regression analysis revealed that increased serum BDNF represents an independent factor for reduced eGFR (95% confidence interval between −0.887 and −0.076, P=0.020. Conclusions. Increased serum BDNF is associated with reduced eGFR in type 2 diabetic subjects treated with valsartan/hydrochlorothiazide but not with amlodipine/benazepril.

  18. Forecasting global atmospheric CO2

    Science.gov (United States)

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

    2014-11-01

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

  19. Value of medium range weather forecasts in the improvement of seasonal hydrologic prediction skill

    Directory of Open Access Journals (Sweden)

    S. Shukla

    2012-08-01

    Full Text Available We investigated the contribution of medium range weather forecasts with lead times of up to 14 days to seasonal hydrologic prediction skill over the conterminous United States (CONUS. Three different Ensemble Streamflow Prediction (ESP based experiments were performed for the period 1980–2003 using the Variable Infiltration Capacity (VIC hydrology model to generate forecasts of monthly runoff and soil moisture (SM at lead-1 (first month of the forecast period to lead-3. The first experiment (ESP used a resampling from the retrospective period 1980–2003 and represented full climatological uncertainty for the entire forecast period. In the second and third experiments, the first 14 days of each ESP ensemble member were replaced by either observations (perfect 14-day forecast or by a deterministic 14-day weather forecast. We used Spearman rank correlations of forecasts and observations as the forecast skill score. We estimated the potential and actual improvement in baseline skill as the difference between the skill of experiments 2 and 3 relative to ESP, respectively. We found that useful runoff and SM forecast skill at lead-1 to -3 months can be obtained by exploiting medium range weather forecast skill in conjunction with the skill derived by the knowledge of initial hydrologic conditions. Potential improvement in baseline skill by using medium range weather forecasts for runoff [SM] forecasts generally varies from 0 to 0.8 [0 to 0.5] as measured by differences in correlations, with actual improvement generally from 0 to 0.8 of the potential improvement. With some exceptions, most of the improvement in runoff is for lead-1 forecasts, although some improvement in SM was achieved at lead-2.

  20. Forecasting individual breast cancer risk using plasma metabolomics and biocontours

    DEFF Research Database (Denmark)

    Bro, Rasmus; Kamstrup-Nielsen, Maja Hermann; Engelsen, Søren Balling

    2015-01-01

    in a subject 2–5 years after the sample is taken with sensitivity and specificity well above 80 %. The model was built on data obtained in 1993–1996 and tested on persons sampled a year later in 1997. Metabolic forecasting of cancer by biocontours opens new possibilities for early prediction of individual...

  1. Intelligent systems for demand forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Majithia, S.; Kiernan, L.; Hannan, J.

    1997-12-31

    The electricity industry is a huge and growing business, centring around the supply and demand of electricity. There are many benefits in knowing the future load on the system by way of forecasting future demand for electricity. Demand forecasts are of use in a wide range of issues relating to system control, maintenance and planning. Short term demand forecasting (1-7 days ahead) allows unit scheduling to be planned, preparing the industry to meet the demand for electricity. There are large financial benefits in improving forecasts even by a small percentage, so it is always worth investigating new techniques that may help the forecaster. ISs offer a range of new approaches that can help improve demand forecasts. There are two major benefits of using ISs rather than the more traditional modelling techniques. Firstly, intelligent systems offer powerful modelling techniques with very different strengths from those currently available. ESs can be used to encapsulate knowledge and experience, to track not just the general trends in demand but also many of the irregularities. They can easily be updated to include any new relationships. Fuzzy sets permit the linguistic rules that are often present in human descriptions to be incorporated into the model. ANNs offer the ability to model the non-linearities that are known to be part of the demand pattern. The second benefit is the ability of intelligent systems to automate the process of constructing a forecasting model. (UK)

  2. Qualitative and quantitative descriptions of temperature: a study of the terminology used by local television weather forecasters to describe thermal sensation.

    Science.gov (United States)

    Brunskill, Jeffrey C

    2010-03-01

    This paper presents a study of the relationship between quantitative and qualitative descriptions of temperature. Online weather forecast narratives produced by local television forecasters were collected from affiliates in 23 cities throughout the northeastern, central and southern portions of the United States from August 2007 to July 2008. The narratives were collected to study the terminology and reference frames that local forecasters use to describe predicted temperatures for the following day. The main objectives were to explore the adjectives used to describe thermal conditions and the impact that geographical and seasonal variations in thermal conditions have on these descriptions. The results of this empirical study offer some insights into the structure of weather narratives and suggest that spatiotemporal variations in the weather impact how forecasters describe the temperature to their local audiences. In a broader sense, this investigation builds upon research in biometeorology, urban planning and linguistics that has explored the physiological and psychological factors that influence subjective assessments of thermal sensation and comfort. The results of this study provide a basis to reason about how thermal comfort is conveyed in meteorological communications and how experiential knowledge derived from daily observations of the weather influence how we think about and discuss the weather.

  3. Qualitative and quantitative descriptions of temperature: a study of the terminology used by local television weather forecasters to describe thermal sensation

    Science.gov (United States)

    Brunskill, Jeffrey C.

    2010-03-01

    This paper presents a study of the relationship between quantitative and qualitative descriptions of temperature. Online weather forecast narratives produced by local television forecasters were collected from affiliates in 23 cities throughout the northeastern, central and southern portions of the United States from August 2007 to July 2008. The narratives were collected to study the terminology and reference frames that local forecasters use to describe predicted temperatures for the following day. The main objectives were to explore the adjectives used to describe thermal conditions and the impact that geographical and seasonal variations in thermal conditions have on these descriptions. The results of this empirical study offer some insights into the structure of weather narratives and suggest that spatiotemporal variations in the weather impact how forecasters describe the temperature to their local audiences. In a broader sense, this investigation builds upon research in biometeorology, urban planning and linguistics that has explored the physiological and psychological factors that influence subjective assessments of thermal sensation and comfort. The results of this study provide a basis to reason about how thermal comfort is conveyed in meteorological communications and how experiential knowledge derived from daily observations of the weather influence how we think about and discuss the weather.

  4. Forecasting temperature fluctuations of brake discs on a hoisting machine

    Energy Technology Data Exchange (ETDEWEB)

    Barecki, Z.; Jankowski, A.

    1987-01-01

    Evaluates a method for forecasting temperature of brake discs on hoists used in underground coal mines. Formulae describing the following phenomena are derived: energy of mechanical braking, density of energy stream absorbed by the friction liners on disc brakes, temperature increase of a disc brake caused by braking, disc cooling intensity, disc temperature during repeated braking, minimum disc mass and surface. Use of the forecasting formulae is explained with the example of disc brake operation on 2 hoists. Temperature increase on disc surface and temperature increase of disc volume are treated as 2 basic indices characterizing disc brake operation. 11 refs.

  5. Climate Forecast System Version 2 (CFSv2) Operational Forecasts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Forecast System Version 2 (CFSv2) produced by the NOAA National Centers for Environmental Prediction (NCEP) is a fully coupled model representing the...

  6. Predicting survival in heart failure case and control subjects by use of fully automated methods for deriving nonlinear and conventional indices of heart rate dynamics

    Science.gov (United States)

    Ho, K. K.; Moody, G. B.; Peng, C. K.; Mietus, J. E.; Larson, M. G.; Levy, D.; Goldberger, A. L.

    1997-01-01

    BACKGROUND: Despite much recent interest in quantification of heart rate variability (HRV), the prognostic value of conventional measures of HRV and of newer indices based on nonlinear dynamics is not universally accepted. METHODS AND RESULTS: We have designed algorithms for analyzing ambulatory ECG recordings and measuring HRV without human intervention, using robust methods for obtaining time-domain measures (mean and SD of heart rate), frequency-domain measures (power in the bands of 0.001 to 0.01 Hz [VLF], 0.01 to 0.15 Hz [LF], and 0.15 to 0.5 Hz [HF] and total spectral power [TP] over all three of these bands), and measures based on nonlinear dynamics (approximate entropy [ApEn], a measure of complexity, and detrended fluctuation analysis [DFA], a measure of long-term correlations). The study population consisted of chronic congestive heart failure (CHF) case patients and sex- and age-matched control subjects in the Framingham Heart Study. After exclusion of technically inadequate studies and those with atrial fibrillation, we used these algorithms to study HRV in 2-hour ambulatory ECG recordings of 69 participants (mean age, 71.7+/-8.1 years). By use of separate Cox proportional-hazards models, the conventional measures SD (P.3), were not. In multivariable models, DFA was of borderline predictive significance (P=.06) after adjustment for the diagnosis of CHF and SD. CONCLUSIONS: These results demonstrate that HRV analysis of ambulatory ECG recordings based on fully automated methods can have prognostic value in a population-based study and that nonlinear HRV indices may contribute prognostic value to complement traditional HRV measures.

  7. Black Sea coastal forecasting system

    Directory of Open Access Journals (Sweden)

    A. I. Kubryakov

    2012-03-01

    Full Text Available The Black Sea coastal nowcasting and forecasting system was built within the framework of EU FP6 ECOOP (European COastalshelf sea OPerational observing and forecasting system project for five regions: the south-western basin along the coasts of Bulgaria and Turkey, the north-western shelf along the Romanian and Ukrainian coasts, coastal zone around of the Crimea peninsula, the north-eastern Russian coastal zone and the coastal zone of Georgia. The system operates in the real-time mode during the ECOOP project and afterwards. The forecasts include temperature, salinity and current velocity fields. Ecosystem model operates in the off-line mode near the Crimea coast.

  8. Different pattern of immunoglobulin gene usage by HIV-1 compared to non-HIV-1 antibodies derived from the same infected subject.

    Science.gov (United States)

    Li, Liuzhe; Wang, Xiao-Hong; Banerjee, Sagarika; Volsky, Barbara; Williams, Constance; Virland, Diana; Nadas, Arthur; Seaman, Michael S; Chen, Xuemin; Spearman, Paul; Zolla-Pazner, Susan; Gorny, Miroslaw K

    2012-01-01

    A biased usage of immunoglobulin (Ig) genes is observed in human anti-HIV-1 monoclonal antibodies (mAbs) resulting probably from compensation to reduced usage of the VH3 family genes, while the other alternative suggests that this bias usage is due to antigen requirements. If the antigen structure is responsible for the preferential usage of particular Ig genes, it may have certain implications for HIV vaccine development by the targeting of particular Ig gene-encoded B cell receptors to induce neutralizing anti-HIV-1 antibodies. To address this issue, we have produced HIV-1 specific and non-HIV-1 mAbs from an infected individual and analyzed the Ig gene usage. Green-fluorescence labeled virus-like particles (VLP) expressing HIV-1 envelope (Env) proteins of JRFL and BaL and control VLPs (without Env) were used to select single B cells for the production of 68 recombinant mAbs. Ten of these mAbs were HIV-1 Env specific with neutralizing activity against V3 and the CD4 binding site, as well as non-neutralizing mAbs to gp41. The remaining 58 mAbs were non-HIV-1 Env mAbs with undefined specificities. Analysis revealed that biased usage of Ig genes was restricted only to anti-HIV-1 but not to non-HIV-1 mAbs. The VH1 family genes were dominantly used, followed by VH3, VH4, and VH5 among anti-HIV-1 mAbs, while non-HIV-1 specific mAbs preferentially used VH3 family genes, followed by VH4, VH1 and VH5 families in a pattern identical to Abs derived from healthy individuals. This observation suggests that the biased usage of Ig genes by anti-HIV-1 mAbs is driven by structural requirements of the virus antigens rather than by compensation to any depletion of VH3 B cells due to autoreactive mechanisms, according to the gp120 superantigen hypothesis.

  9. Different pattern of immunoglobulin gene usage by HIV-1 compared to non-HIV-1 antibodies derived from the same infected subject.

    Directory of Open Access Journals (Sweden)

    Liuzhe Li

    Full Text Available A biased usage of immunoglobulin (Ig genes is observed in human anti-HIV-1 monoclonal antibodies (mAbs resulting probably from compensation to reduced usage of the VH3 family genes, while the other alternative suggests that this bias usage is due to antigen requirements. If the antigen structure is responsible for the preferential usage of particular Ig genes, it may have certain implications for HIV vaccine development by the targeting of particular Ig gene-encoded B cell receptors to induce neutralizing anti-HIV-1 antibodies. To address this issue, we have produced HIV-1 specific and non-HIV-1 mAbs from an infected individual and analyzed the Ig gene usage. Green-fluorescence labeled virus-like particles (VLP expressing HIV-1 envelope (Env proteins of JRFL and BaL and control VLPs (without Env were used to select single B cells for the production of 68 recombinant mAbs. Ten of these mAbs were HIV-1 Env specific with neutralizing activity against V3 and the CD4 binding site, as well as non-neutralizing mAbs to gp41. The remaining 58 mAbs were non-HIV-1 Env mAbs with undefined specificities. Analysis revealed that biased usage of Ig genes was restricted only to anti-HIV-1 but not to non-HIV-1 mAbs. The VH1 family genes were dominantly used, followed by VH3, VH4, and VH5 among anti-HIV-1 mAbs, while non-HIV-1 specific mAbs preferentially used VH3 family genes, followed by VH4, VH1 and VH5 families in a pattern identical to Abs derived from healthy individuals. This observation suggests that the biased usage of Ig genes by anti-HIV-1 mAbs is driven by structural requirements of the virus antigens rather than by compensation to any depletion of VH3 B cells due to autoreactive mechanisms, according to the gp120 superantigen hypothesis.

  10. 25 years of time series forecasting

    NARCIS (Netherlands)

    de Gooijer, J.G.; Hyndman, R.J.

    2006-01-01

    We review the past 25 years of research into time series forecasting. In this silver jubilee issue, we naturally highlight results published in journals managed by the International Institute of Forecasters (Journal of Forecasting 1982-1985 and International Journal of Forecasting 1985-2005). During

  11. Forecasting Covariance Matrices: A Mixed Frequency Approach

    DEFF Research Database (Denmark)

    Halbleib, Roxana; Voev, Valeri

    This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows for flexi......This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows...... matrix dynamics. Our empirical results show that the new mixing approach provides superior forecasts compared to multivariate volatility specifications using single sources of information....

  12. Earthquake number forecasts testing

    Science.gov (United States)

    Kagan, Yan Y.

    2017-10-01

    We study the distributions of earthquake numbers in two global earthquake catalogues: Global Centroid-Moment Tensor and Preliminary Determinations of Epicenters. The properties of these distributions are especially required to develop the number test for our forecasts of future seismic activity rate, tested by the Collaboratory for Study of Earthquake Predictability (CSEP). A common assumption, as used in the CSEP tests, is that the numbers are described by the Poisson distribution. It is clear, however, that the Poisson assumption for the earthquake number distribution is incorrect, especially for the catalogues with a lower magnitude threshold. In contrast to the one-parameter Poisson distribution so widely used to describe earthquake occurrences, the negative-binomial distribution (NBD) has two parameters. The second parameter can be used to characterize the clustering or overdispersion of a process. We also introduce and study a more complex three-parameter beta negative-binomial distribution. We investigate the dependence of parameters for both Poisson and NBD distributions on the catalogue magnitude threshold and on temporal subdivision of catalogue duration. First, we study whether the Poisson law can be statistically rejected for various catalogue subdivisions. We find that for most cases of interest, the Poisson distribution can be shown to be rejected statistically at a high significance level in favour of the NBD. Thereafter, we investigate whether these distributions fit the observed distributions of seismicity. For this purpose, we study upper statistical moments of earthquake numbers (skewness and kurtosis) and compare them to the theoretical values for both distributions. Empirical values for the skewness and the kurtosis increase for the smaller magnitude threshold and increase with even greater intensity for small temporal subdivision of catalogues. The Poisson distribution for large rate values approaches the Gaussian law, therefore its skewness

  13. Oregon Washington Coastal Ocean Forecast System: Real-time Modeling and Data Assimilation

    Science.gov (United States)

    Erofeeva, S.; Kurapov, A. L.; Pasmans, I.

    2016-02-01

    Three-day forecasts of ocean currents, temperature and salinity along the Oregon and Washington coasts are produced daily by a numerical ROMS-based ocean circulation model. NAM is used to derive atmospheric forcing for the model. Fresh water discharge from Columbia River, Fraser River, and small rivers in Puget Sound are included. The forecast is constrained by open boundary conditions derived from the global Navy HYCOM model and once in 3 days assimilation of recent data, including HF radar surface currents, sea surface temperature from the GOES satellite, and SSH from several satellite altimetry missions. 4-dimensional variational data assimilation is implemented in 3-day time windows using the tangent linear and adjoint codes developed at OSU. The system is semi-autonomous - all the data, including NAM and HYCOM fields are automatically updated, and daily operational forecast is automatically initiated. The pre-assimilation data quality control and post-assimilation forecast quality control require the operator's involvement. The daily forecast and 60 days of hindcast fields are available for public on opendap. As part of the system model validation plots to various satellites and SEAGLIDER are also automatically updated and available on the web (http://ingria.coas.oregonstate.edu/rtdavow/). Lessons learned in this pilot real-time coastal ocean forecasting project help develop and test metrics for forecast skill assessment for the West Coast Operational Forecast System (WCOFS), currently at testing and development phase at the National Oceanic and Atmospheric Administration (NOAA).

  14. [A model of individually forecasting the penile length gained after penis lengthening].

    Science.gov (United States)

    Wang, Hong-Yi; Tao, Ling; Chen, Liang; Cao, Chuan; Li, Shi-Rong

    2011-11-01

    To establish a model of individually forecasting the penile length gained after penis lengthening. A total of 322 patients were diagnosed congenital penile shortness and received partial suspensory ligament release in our department from Oct. 1988 to Apr. 2011. The patients were divide into two groups as Modeling Group (n = 200) and Checking Group (n = 122). Then a two-dimensional model of the suspensory-ligament-release penis lengthening is established. In the Modeling Group, a statistical analysis of the penile length in flaccid and erectile state before and after penis lengthening was carried out, and a forecasting predictive function of increased penile length was derived. Then the predictive accurate rate was tested in the Checking Group. There was a significant linear correlation between the increased length in flaccid and erectile state (correlation coefficient = 0.921, P forecasting models were established. A predictive function of increased flaccid length was derived from the two regression forecasting models. The effectively forecasting rates were 84.5% (169/200, the Modeling Group) and 87.7% (107/122, the Checking Group) when the absolute value of forecasting error was less than 1.5 cm. The discovered significant correlation and the established forecasting function provide us a model of roughly and individually forecasting the penile length gained after penis lengthening.

  15. Valuing information from mesoscale forecasts

    NARCIS (Netherlands)

    Kok, K.; Wichers Schreur, B.G.J.; Vogelenzang, D.

    2008-01-01

    The development of meso-gamma scale numerical weather prediction (NWP) models requires a substantial investment in research, development and computational resources. Traditional objective verification of deterministic model output fails to demonstrate the added value of high-resolution forecasts

  16. Ensemble hydromoeteorological forecasting in Denmark

    DEFF Research Database (Denmark)

    Lucatero Villasenor, Diana

    of the main sources of uncertainty in hydrological forecasts. This is the reason why substantiated efforts to include information from Numerical Weather Predictors (NWP) or General Circulation Models (GCM) have been made over the last couple of decades. The present thesis expects to advance the field......teorological extremes such as flood and droughts cause economical and live losses that could be, if not prevented, at least dampened if sufficient time is given to respond to potential threats. This is the ultimate purpose of forecasting which then translates into making reliable predictions...... of ensemble hydrometeorological forecasting by evaluating the added value of NWP and GCM ensemble prediction systems (EPS) for hydrological purposes. The use of NWP EPS that differ in both spatial and temporal resolution to feed a hydrological model for discharge forecasts at specific points, revealed two...

  17. Load forecasting of supermarket refrigeration

    DEFF Research Database (Denmark)

    Rasmussen, Lisa Buth; Bacher, Peder; Madsen, Henrik

    2016-01-01

    This paper presents a novel study of models for forecasting the electrical load for supermarket refrigeration. The data used for building the models consists of load measurements, local climate measurements and weather forecasts. The load measurements are from a supermarket located in a village...... in Denmark. Every hour the hourly electrical load for refrigeration is forecasted for the following 42 h. The forecast models are adaptive linear time series models. The model has two regimes; one for opening hours and one for closing hours, this is modeled by a regime switching model and two different...... methods for predicting the regimes are tested. The dynamic relation between the weather and the load is modeled by simple transfer functions and the non-linearities are described using spline functions. The results are thoroughly evaluated and it is shown that the spline functions are suitable...

  18. Recurrent networks for wave forecasting

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    , merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper presents an application of the Artificial Neural Network, namely Backpropagation Recurrent Neural Network (BRNN) with rprop update algorithm for wave forecasting...

  19. Flash floods: forecasting and warning

    National Research Council Canada - National Science Library

    Sene, Kevin

    2013-01-01

    ... and levees.The volume discusses the increasing use of meteorological observation and forecasting techniques to extend the lead time available for warning, combined with hydrological models for the river response...

  20. Forecasting and management of technology

    National Research Council Canada - National Science Library

    Roper, A. T

    2011-01-01

    .... The scope of this edition has broadened to include management of technology content that is relevant to now to executives in organizations while updating and strengthening the technology forecasting...

  1. Electricity forecasting on the individual household level enhanced based on activity patterns.

    Science.gov (United States)

    Gajowniczek, Krzysztof; Ząbkowski, Tomasz

    2017-01-01

    Leveraging smart metering solutions to support energy efficiency on the individual household level poses novel research challenges in monitoring usage and providing accurate load forecasting. Forecasting electricity usage is an especially important component that can provide intelligence to smart meters. In this paper, we propose an enhanced approach for load forecasting at the household level. The impacts of residents' daily activities and appliance usages on the power consumption of the entire household are incorporated to improve the accuracy of the forecasting model. The contributions of this paper are threefold: (1) we addressed short-term electricity load forecasting for 24 hours ahead, not on the aggregate but on the individual household level, which fits into the Residential Power Load Forecasting (RPLF) methods; (2) for the forecasting, we utilized a household specific dataset of behaviors that influence power consumption, which was derived using segmentation and sequence mining algorithms; and (3) an extensive load forecasting study using different forecasting algorithms enhanced by the household activity patterns was undertaken.

  2. A complex autoregressive model and application to monthly temperature forecasts

    Directory of Open Access Journals (Sweden)

    X. Gu

    2005-11-01

    Full Text Available A complex autoregressive model was established based on the mathematic derivation of the least squares for the complex number domain which is referred to as the complex least squares. The model is different from the conventional way that the real number and the imaginary number are separately calculated. An application of this new model shows a better forecast than forecasts from other conventional statistical models, in predicting monthly temperature anomalies in July at 160 meteorological stations in mainland China. The conventional statistical models include an autoregressive model, where the real number and the imaginary number are separately disposed, an autoregressive model in the real number domain, and a persistence-forecast model.

  3. Fuzzy forecasting based on fuzzy-trend logical relationship groups.

    Science.gov (United States)

    Chen, Shyi-Ming; Wang, Nai-Yi

    2010-10-01

    In this paper, we present a new method to predict the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy-trend logical relationship groups (FTLRGs). The proposed method divides fuzzy logical relationships into FTLRGs based on the trend of adjacent fuzzy sets appearing in the antecedents of fuzzy logical relationships. First, we apply an automatic clustering algorithm to cluster the historical data into intervals of different lengths. Then, we define fuzzy sets based on these intervals of different lengths. Then, the historical data are fuzzified into fuzzy sets to derive fuzzy logical relationships. Then, we divide the fuzzy logical relationships into FTLRGs for forecasting the TAIEX. Moreover, we also apply the proposed method to forecast the enrollments and the inventory demand, respectively. The experimental results show that the proposed method gets higher average forecasting accuracy rates than the existing methods.

  4. Preparing for an Uncertain Forecast

    Science.gov (United States)

    Karolak, Eric

    2011-01-01

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

  5. Analyst Forecasts and Herding Behavior.

    OpenAIRE

    Trueman, Brett

    1994-01-01

    The use of analyst forecasts as proxies for investors' earnings expectations is commonplace in empirical research. An implicit assumption behind their use is that they reflect analysts' private information in an unbiased manner. As demonstrated here, this assumption is not necessarily valid. There is shown to be a tendency for analysts to release forecasts closer to prior earnings expectations than is appropriate, given their information. Further, analysts exhibit herding behavior, whereby th...

  6. Forecasting with Dynamic Regression Models

    CERN Document Server

    Pankratz, Alan

    2012-01-01

    One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.

  7. High-resolution hydrological seasonal forecasting for water resources management over Europe

    Science.gov (United States)

    Pan, Ming; Wanders, Niko; Wood, Eric; Sheffield, Justin; Samaniego, Luis; Thober, Stephan; Kumar, Rohini; Prudhomme, Christel; Houghton-Carr, Helen

    2017-04-01

    To support the decision-making process at the seasonal time scale, hydrological forecasts with a high temporal and spatial resolution are required to provide the level of information needed by water managers. So far high-resolution seasonal forecasts have been unavailable due to 1) lack of availability in meteorological seasonal forecasts, 2) the coarse temporal resolution of meteorological seasonal forecasts, requiring temporal downscaling, and 3) lack of consistency between observations and seasonal forecasts, requiring bias-correction. As part of the EDgE (End-to-end Demonstrator for improved decision making in the water sector in Europe) project, we have created a unique dataset of hydrological seasonal forecasts derived from four atmospheric circulation models (CanCM4, FLOR-B01, ECMF, LFPW) in combination with four global hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP). The forecasts provide daily values at 5-km spatial resolution and are bias corrected against E-OBS meteorological observations. Consistency in the LSM parameterization ensures synergy in the hydrological forecasts, resulting in 208 forecasts at any given day over Europe. The forecast results are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs) that have been co-designed in collaboration with end-users and stakeholders inside the EDgE project. An example of an SCII is the percentage of ensemble realizations above the 10th percentile of monthly river flow or below the 90th percentile, including the persistency in the forecast with increasing lead times. Results show that skillful discharge forecasts can be made throughout Europe 3 months in advance, with predictability up to 6 months for Northern Europe due to the impact of snow. The predictability of soil moisture is limited to the first three months, due to the significant impact of precipitation and the short memory in the initial conditions (only for the first month). The groundwater recharge predictability

  8. Central bank forecasting: an international comparison

    OpenAIRE

    John C. Robertson

    2000-01-01

    Forecasts, whether explicit or implicit, are at the heart of policy making. In considering forecasting for monetary policy, this article contrasts the forecasting processes at three central banks-the Reserve Bank of New Zealand, the Bank of England, and the U.S. Federal Reserve. ; In the United States policymakers consider confidential staff forecasts in policy discussions, but these do not necessarily represent the consensus forecasts of the policy committee. At the Bank of England, official...

  9. Electricity derivatives

    CERN Document Server

    Aïd, René

    2015-01-01

    Offering a concise but complete survey of the common features of the microstructure of electricity markets, this book describes the state of the art in the different proposed electricity price models for pricing derivatives and in the numerical methods used to price and hedge the most prominent derivatives in electricity markets, namely power plants and swings. The mathematical content of the book has intentionally been made light in order to concentrate on the main subject matter, avoiding fastidious computations. Wherever possible, the models are illustrated by diagrams. The book should allow prospective researchers in the field of electricity derivatives to focus on the actual difficulties associated with the subject. It should also offer a brief but exhaustive overview of the latest techniques used by financial engineers in energy utilities and energy trading desks.

  10. Container Throughput Forecasting Using Dynamic Factor Analysis and ARIMAX Model

    Directory of Open Access Journals (Sweden)

    Marko Intihar

    2017-11-01

    Full Text Available The paper examines the impact of integration of macroeconomic indicators on the accuracy of container throughput time series forecasting model. For this purpose, a Dynamic factor analysis and AutoRegressive Integrated Moving-Average model with eXogenous inputs (ARIMAX are used. Both methodologies are integrated into a novel four-stage heuristic procedure. Firstly, dynamic factors are extracted from external macroeconomic indicators influencing the observed throughput. Secondly, the family of ARIMAX models of different orders is generated based on the derived factors. In the third stage, the diagnostic and goodness-of-fit testing is applied, which includes statistical criteria such as fit performance, information criteria, and parsimony. Finally, the best model is heuristically selected and tested on the real data of the Port of Koper. The results show that by applying macroeconomic indicators into the forecasting model, more accurate future throughput forecasts can be achieved. The model is also used to produce future forecasts for the next four years indicating a more oscillatory behaviour in (2018-2020. Hence, care must be taken concerning any bigger investment decisions initiated from the management side. It is believed that the proposed model might be a useful reinforcement of the existing forecasting module in the observed port.

  11. Functional dynamic factor models with application to yield curve forecasting

    KAUST Repository

    Hays, Spencer

    2012-09-01

    Accurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM with functional factor loading curves. This results in a model capable of forecasting functional time series. Further, in the yield curve context we show that the model retains economic interpretation. Model estimation is achieved through an expectation- maximization algorithm, where the time series parameters and factor loading curves are simultaneously estimated in a single step. Efficient computing is implemented and a data-driven smoothing parameter is nicely incorporated. We show that our model performs very well on forecasting actual yield data compared with existing approaches, especially in regard to profit-based assessment for an innovative trading exercise. We further illustrate the viability of our model to applications outside of yield forecasting.

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

    Science.gov (United States)

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

    2013-11-01

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

  13. Seasonal Forecasting of Reservoir Inflow for the Segura River Basin, Spain

    Science.gov (United States)

    de Tomas, Alberto; Hunink, Johannes

    2017-04-01

    A major threat to the agricultural sector in Europe is an increasing occurrence of low water availability for irrigation, affecting the local and regional food security and economies. Especially in the Mediterranean region, such as in the Segura river basin (Spain), drought epidodes are relatively frequent. Part of the irrigation water demand in this basin is met by a water transfer from the Tagus basin (central Spain), but also in this basin an increasing pressure on the water resources has reduced the water available to be transferred. Currently, Drought Management Plans in these Spanish basins are in place and mitigate the impact of drought periods to some extent. Drought indicators that are derived from the available water in the storage reservoirs impose a set of drought mitigation measures. Decisions on water transfers are dependent on a regression-based time series forecast from the reservoir inflows of the preceding months. This user-forecast has its limitations and can potentially be improved using more advanced techniques. Nowadays, seasonal climate forecasts have shown to have increasing skill for certain areas and for certain applications. So far, such forecasts have not been evaluated in a seasonal hydrologic forecasting system in the Spanish context. The objective of this work is to develop a prototype of a Seasonal Hydrologic Forecasting System and compare this with a reference forecast. The reference forecast in this case is the locally used regression-based forecast. Additionally, hydrological simulations derived from climatological reanalysis (ERA-Interim) are taken as a reference forecast. The Spatial Processes in Hydrology model (SPHY - http://www.sphy.nl/) forced with the ECMWF- SFS4 (15 ensembles) Seasonal Forecast Systems is used to predict reservoir inflows of the upper basins of the Segura and Tagus rivers. The system is evaluated for 4 seasons with a forecasting lead time of 3 months. First results show that only for certain initialization

  14. A Robust Multimodel Framework for Ensemble Seasonal Hydroclimatic Forecasts

    Science.gov (United States)

    Mendoza, P. A.; Rajagopalan, B.; Clark, M. P.; Cortés, G.; McPhee, J. P.

    2014-12-01

    We provide a framework for careful analysis of the different methodological choices we make when constructing multimodel ensemble seasonal forecasts of hydroclimatic variables. Specifically, we focus on three common modeling decisions: (i) number of models, (ii) multimodel combination approach, and (iii) lead time for prediction. The analysis scheme includes a multimodel ensemble forecasting algorithm based on nonparametric regression, a set of alternatives for the options previously pointed, and a selection of probabilistic verification methods for ensemble forecast evaluation. The usefulness of this framework is tested through an example application aimed to generate spring/summer streamflow forecasts at multiple locations in Central Chile. Results demonstrate the high impact that subjectivity in decision-making may have on the quality of ensemble seasonal hydroclimatic forecasts. In particular, we note that the probabilistic verification criteria may lead to different choices regarding the number of models or the multimodel combination method. We also illustrate how this objective analysis scheme may lead to results that are extremely relevant for the case study presented here, such as skillful seasonal streamflow predictions for very dry conditions.

  15. State-space adjustment of radar rainfall and stochastic flow forecasting for use in real-time control of urban drainage systems

    DEFF Research Database (Denmark)

    Löwe, Roland; Mikkelsen, Peter Steen; Rasmussen, Michael R.

    2013-01-01

    improves runoff forecasts compared to using the original radar data and that rain gauge measurements as forecast input are also outperformed. Combining the data merging approach with short term rainfall forecasting algorithms may result in further improved runoff forecasts that can be used in real time......Merging of radar rainfall data with rain gauge measurements is a common approach to overcome problems in deriving rain intensities from radar measurements. We extend an existing approach for adjustment of C-band radar data using state-space models and use the resulting rainfall intensities as input...... for forecasting outflow from two catchments in the Copenhagen area. Stochastic greybox models are applied to create the runoff forecasts, providing us with not only a point forecast but also a quantification of the forecast uncertainty. Evaluating the results, we can show that using the adjusted radar data...

  16. State-space adjustment of radar rainfall and stochastic flow forecasting for use in real-time control of urban drainage systems

    DEFF Research Database (Denmark)

    Löwe, Roland; Mikkelsen, Peter Steen; Rasmussen, Michael R.

    2012-01-01

    improves runoff forecasts compared to using the original radar data and that rain gauge measurements as forecast input are also outperformed. Combining the data merging approach with short term rainfall forecasting algorithms may result in further improved runoff forecasts that can be used in real time......Merging of radar rainfall data with rain gauge measurements is a common approach to overcome problems in deriving rain intensities from radar measurements. We extend an existing approach for adjustment of C-band radar data using state-space models and use the resulting rainfall intensities as input...... for forecasting outflow from two catchments in the Copenhagen area. Stochastic greybox models are applied to create the runoff forecasts, providing us with not only a point forecast but also a quantification of the forecast uncertainty. Evaluating the results, we can show that using the adjusted radar data...

  17. 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.

  18. Adjoint-Based Forecast Error Sensitivity Diagnostics in Data Assimilation

    Science.gov (United States)

    Langland, R.; Daescu, D.

    2016-12-01

    We present an up-to-date review of the adjoint-data assimilation system (DAS) approach to evaluate the forecast sensitivity to error covariance parameters and provide guidance to flow-dependent adaptive covariance tuning (ACT) procedures. New applications of the forecast sensitivity to observation error covariance (FSR) are investigated including the sensitivity to observation error correlations and a priori first-order assessment to the error correlation impact on the forecasts. Issues related to ambiguities in the a posteriori estimation to the observation error covariance (R) and background error covariance (B) are discussed. A synergistic framework to adaptive covariance tuning is considered that combines R-estimates derived from a posteriori covariance diagnosis and FSR derivative information. The evaluation of the forecast sensitivity to the innovation-weight coefficients is introduced as a computationally-feasible approach to account for the characteristics of both R- and B-parameters and perform direct tuning of the DAS gain operator (K). Theoretical aspects are discussed and recent results are provided with the adjoint versions of the Naval Research Laboratory Atmospheric Variational Data Assimilation System-Accelerated Representer (NAVDAS-AR).

  19. Bayesian flood forecasting methods: A review

    Science.gov (United States)

    Han, Shasha; Coulibaly, Paulin

    2017-08-01

    Over the past few decades, floods have been seen as one of the most common and largely distributed natural disasters in the world. If floods could be accurately forecasted in advance, then their negative impacts could be greatly minimized. It is widely recognized that quantification and reduction of uncertainty associated with the hydrologic forecast is of great importance for flood estimation and rational decision making. Bayesian forecasting system (BFS) offers an ideal theoretic framework for uncertainty quantification that can be developed for probabilistic flood forecasting via any deterministic hydrologic model. It provides suitable theoretical structure, empirically validated models and reasonable analytic-numerical computation method, and can be developed into various Bayesian forecasting approaches. This paper presents a comprehensive review on Bayesian forecasting approaches applied in flood forecasting from 1999 till now. The review starts with an overview of fundamentals of BFS and recent advances in BFS, followed with BFS application in river stage forecasting and real-time flood forecasting, then move to a critical analysis by evaluating advantages and limitations of Bayesian forecasting methods and other predictive uncertainty assessment approaches in flood forecasting, and finally discusses the future research direction in Bayesian flood forecasting. Results show that the Bayesian flood forecasting approach is an effective and advanced way for flood estimation, it considers all sources of uncertainties and produces a predictive distribution of the river stage, river discharge or runoff, thus gives more accurate and reliable flood forecasts. Some emerging Bayesian forecasting methods (e.g. ensemble Bayesian forecasting system, Bayesian multi-model combination) were shown to overcome limitations of single model or fixed model weight and effectively reduce predictive uncertainty. In recent years, various Bayesian flood forecasting approaches have been

  20. Derived Subjects In Kinyarwanda Locative Constructions*

    African Journals Online (AJOL)

    Information Technology

    To the best of my knowledge, contrasts such as the one between (3b) and (4) have not been systematically discussed in the existing literature on Kinyarwanda. In this paper, I therefore examine the syntax of transitive locative constructions such as (3b) and (4) within the framework of the Minimalist Program (Chomsky 1995, ...

  1. Derived Subjects In Kinyarwanda Locative Constructions*

    African Journals Online (AJOL)

    Information Technology

    Inyaanya z-eer-a-mo tomatoes ...... pronunciation is irrelevant for my analysis. 2. ... functional heads like T and ν, and I also pass over the function of case features and the .... MA-thesis, University of KwaZulu-Natal, Durban, South Africa.

  2. 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

  3. Improved Weather Forecasting for the Dynamic Scheduling System of the Green Bank Telescope

    Science.gov (United States)

    Henry, Kari; Maddalena, Ronald

    2018-01-01

    The Robert C Byrd Green Bank Telescope (GBT) uses a software system that dynamically schedules observations based on models of vertical weather forecasts produced by the National Weather Service (NWS). The NWS provides hourly forecasted values for ~60 layers that extend into the stratosphere over the observatory. We use models, recommended by the Radiocommunication Sector of the International Telecommunications Union, to derive the absorption coefficient in each layer for each hour in the NWS forecasts and for all frequencies over which the GBT has receivers, 0.1 to 115 GHz. We apply radiative transfer models to derive the opacity and the atmospheric contributions to the system temperature, thereby deriving forecasts applicable to scheduling radio observations for up to 10 days into the future. Additionally, the algorithms embedded in the data processing pipeline use historical values of the forecasted opacity to calibrate observations. Until recently, we have concentrated on predictions for high frequency (> 15 GHz) observing, as these need to be scheduled carefully around bad weather. We have been using simple models for the contribution of rain and clouds since we only schedule low-frequency observations under these conditions. In this project, we wanted to improve the scheduling of the GBT and data calibration at low frequencies by deriving better algorithms for clouds and rain. To address the limitation at low frequency, the observatory acquired a Radiometrics Corporation MP-1500A radiometer, which operates in 27 channels between 22 and 30 GHz. By comparing 16 months of measurements from the radiometer against forecasted system temperatures, we have confirmed that forecasted system temperatures are indistinguishable from those measured under good weather conditions. Small miss-calibrations of the radiometer data dominate the comparison. By using recalibrated radiometer measurements, we looked at bad weather days to derive better models for forecasting the

  4. A força de preensão manual é boa preditora do desempenho funcional de idosos frágeis: um estudo correlacional múltiplo The hand-grip forecasts the functional performance of fragile elder subjects: a multiple-correlation study

    Directory of Open Access Journals (Sweden)

    Amandio A.R. Geraldes

    2008-02-01

    institutionalized elderly subjects, having a good potential as an epidemiologic exposition variable to forecast functional performance.

  5. Expanding subjectivities

    DEFF Research Database (Denmark)

    Lundgaard Andersen, Linda; Soldz, Stephen

    2012-01-01

    A major theme in recent psychoanalytic thinking concerns the use of therapist subjectivity, especially “countertransference,” in understanding patients. This thinking converges with and expands developments in qualitative research regarding the use of researcher subjectivity as a tool to understa...

  6. Strength of baseline inter-trial correlations forecasts adaptive capacity in the vestibulo-ocular reflex.

    Directory of Open Access Journals (Sweden)

    Kara H Beaton

    Full Text Available Individual differences in sensorimotor adaptability may permit customized training protocols for optimum learning. Here, we sought to forecast individual adaptive capabilities in the vestibulo-ocular reflex (VOR. Subjects performed 400 head-rotation steps (400 trials during a baseline test, followed by 20 min of VOR gain adaptation. All subjects exhibited mean baseline VOR gain of approximately 1.0, variable from trial to trial, and showed desired reductions in gain following adaptation with variation in extent across individuals. The extent to which a given subject adapted was inversely proportional to a measure of the strength and duration of baseline inter-trial correlations (β. β is derived from the decay of the autocorrelation of the sequence of VOR gains, and describes how strongly correlated are past gain values; it thus indicates how much the VOR gain on any given trial is informed by performance on previous trials. To maximize the time that images are stabilized on the retina, the VOR should maintain a gain close to 1.0 that is adjusted predominantly according to the most recent error; hence, it is not surprising that individuals who exhibit smaller β (weaker inter-trial correlations also exhibited the best adaptation. Our finding suggests that the temporal structure of baseline behavioral data contains important information that may aid in forecasting adaptive capacities. This has significant implications for the development of personalized physical therapy protocols for patients, and for other cases when it is necessary to adjust motor programs to maintain movement accuracy in response to pathological and environmental changes.

  7. Advances in Solar Power Forecasting

    Science.gov (United States)

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

    2014-12-01

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

  8. Trend Monitoring and Forecasting

    Science.gov (United States)

    2015-03-11

    including breaking news, meme , and commemorative day, on the context patterns. Table 2 shows the example pattern of classifying context pattern feature...used the following rule to find the ‘ meme ’. If the trending topic contains ‘#’ AND ‘subject+verb’, then trending topic is ‘ Meme ’. Table 2 Context

  9. Revenue Forecast Errors in the European Union

    OpenAIRE

    Afonso, António; Carvalho, Rui

    2014-01-01

    In this paper we assess the determinants of revenue forecast errors for the EU-15 between 1999 and 2012, based on the forecasts published bi-annually by the European Commission. Our results show that personal income rate changes increase the revenue forecast errors: for forecasts made in t for t, increases in the corporate tax rate implies a decrease in the revenue forecast errors, in t+1 and t+2. Moreover, an increase in GDP forecast errors decreases revenue errors, whereas an increase in th...

  10. Two approaches to forecast Ebola synthetic epidemics.

    Science.gov (United States)

    Champredon, David; Li, Michael; Bolker, Benjamin M; Dushoff, Jonathan

    2017-02-24

    We use two modelling approaches to forecast synthetic Ebola epidemics in the context of the RAPIDD Ebola Forecasting Challenge. The first approach is a standard stochastic compartmental model that aims to forecast incidence, hospitalization and deaths among both the general population and health care workers. The second is a model based on the renewal equation with latent variables that forecasts incidence in the whole population only. We describe fitting and forecasting procedures for each model and discuss their advantages and drawbacks. We did not find that one model was consistently better in forecasting than the other. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

  11. A New Reference for Wind Power Forecasting

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov; Joensen, Alfred K.; Madsen, Henrik

    1998-01-01

    In recent years some research towards developing forecasting models for wind power or energy has been carried out. In order to evaluate the prediction ability of these models, the forecasts are usually compared with those of the persistence forecast model. As shown in this article, however......, it is not reasonable to use the persistence model when the forecast length is more than a few hours. Instead, a new statistical reference for predicting wind power, which basically is a weighting between the persistence and the mean of the power, is proposed. This reference forecast model is adequate for all forecast...

  12. Nonlinear solar cycle forecasting: theory and perspectives

    Directory of Open Access Journals (Sweden)

    A. L. Baranovski

    2008-02-01

    Full Text Available In this paper we develop a modern approach to solar cycle forecasting, based on the mathematical theory of nonlinear dynamics. We start from the design of a static curve fitting model for the experimental yearly sunspot number series, over a time scale of 306 years, starting from year 1700 and we establish a least-squares optimal pulse shape of a solar cycle. The cycle-to-cycle evolution of the parameters of the cycle shape displays different patterns, such as a Gleissberg cycle and a strong anomaly in the cycle evolution during the Dalton minimum. In a second step, we extract a chaotic mapping for the successive values of one of the key model parameters – the rate of the exponential growth-decrease of the solar activity during the n-th cycle. We examine piece-wise linear techniques for the approximation of the derived mapping and we provide its probabilistic analysis: calculation of the invariant distribution and autocorrelation function. We find analytical relationships for the sunspot maxima and minima, as well as their occurrence times, as functions of chaotic values of the above parameter. Based on a Lyapunov spectrum analysis of the embedded mapping, we finally establish a horizon of predictability for the method, which allows us to give the most probable forecasting of the upcoming solar cycle 24, with an expected peak height of 93±21 occurring in 2011/2012.

  13. Score Matrix for HWBI Forecast Model

    Science.gov (United States)

    2000-2010 Annual State-Scale Service and Domain scores used to support the approach for forecasting EPA's Human Well-Being Index. A modeling approach was developed based relationship function equations derived from select economic, social and ecosystem final goods and service scores and calculated human well-being index and related domain scores. These data are being used in a secondary capacity. The foundational data and scoring techniques were originally described in: a) U.S. EPA. 2012. Indicators and Methods for Constructing a U.S. Human Well-being Index (HWBI) for Ecosystem Services Research. Report. EPA/600/R-12/023. pp. 121; and b) U.S. EPA. 2014. Indicators and Methods for Evaluating Economic, Ecosystem and Social Services Provisioning. Report. EPA/600/R-14/184. pp. 174. Mode Smith, L. M., Harwell, L. C., Summers, J. K., Smith, H. M., Wade, C. M., Straub, K. R. and J.L. Case (2014).This dataset is associated with the following publication:Summers , K., L. Harwell , and L. Smith. A Model For Change: An Approach for Forecasting Well-Being From Service-Based Decisions. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 69: 295-309, (2016).

  14. Nonlinear solar cycle forecasting: theory and perspectives

    Directory of Open Access Journals (Sweden)

    A. L. Baranovski

    2008-02-01

    Full Text Available In this paper we develop a modern approach to solar cycle forecasting, based on the mathematical theory of nonlinear dynamics. We start from the design of a static curve fitting model for the experimental yearly sunspot number series, over a time scale of 306 years, starting from year 1700 and we establish a least-squares optimal pulse shape of a solar cycle. The cycle-to-cycle evolution of the parameters of the cycle shape displays different patterns, such as a Gleissberg cycle and a strong anomaly in the cycle evolution during the Dalton minimum. In a second step, we extract a chaotic mapping for the successive values of one of the key model parameters – the rate of the exponential growth-decrease of the solar activity during the n-th cycle. We examine piece-wise linear techniques for the approximation of the derived mapping and we provide its probabilistic analysis: calculation of the invariant distribution and autocorrelation function. We find analytical relationships for the sunspot maxima and minima, as well as their occurrence times, as functions of chaotic values of the above parameter. Based on a Lyapunov spectrum analysis of the embedded mapping, we finally establish a horizon of predictability for the method, which allows us to give the most probable forecasting of the upcoming solar cycle 24, with an expected peak height of 93±21 occurring in 2011/2012.

  15. Forecast Value Added (FVA Analysis as a Means to Improve the Efficiency of a Forecasting Process

    Directory of Open Access Journals (Sweden)

    Filip Chybalski

    2017-01-01

    Full Text Available A praxeological approach has been proposed in order to improve a forecasting process through the employment of the forecast value added (FVA analysis. This may be interpreted as a manifestation of lean management in forecasting. The author discusses the concepts of the effectiveness and efficiency of forecasting. The former, defined in the praxeology as the degree to which goals are achieved, refers to the accuracy of forecasts. The latter reflects the relation between the benefits accruing from the results of forecasting and the costs incurred in this process. Since measuring the benefits accruing from a forecasting is very difficult, a simplification according to which this benefit is a function of the forecast accuracy is proposed. This enables evaluating the efficiency of the forecasting process. Since improving this process may consist of either reducing forecast error or decreasing costs, FVA analysis, which expresses the concept of lean management, may be applied to reduce the waste accompanying forecasting. (original abstract

  16. State-space adjustment of radar rainfall and skill score evaluation of stochastic volume forecasts in urban drainage systems

    DEFF Research Database (Denmark)

    Löwe, Roland; Mikkelsen, Peter Steen; Rasmussen, Michael Robdrup

    2013-01-01

    Merging of radar rainfall data with rain gauge measurements is a common approach to overcome problems in deriving rain intensities from radar measurements. We extend an existing approach for adjustment of C-band radar data using state-space models and use the resulting rainfall intensities as input...... improves runoff forecasts compared with using the original radar data and that rain gauge measurements as forecast input are also outperformed. Combining the data merging approach with short-term rainfall forecasting algorithms may result in further improved runoff forecasts that can be used in real time...

  17. U.S. Regional Demand Forecasts Using NEMS and GIS

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

    2005-07-01

    The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of

  18. Forecasting extreme temperature health hazards in Europe

    Science.gov (United States)

    Di Napoli, Claudia; Pappenberger, Florian; Cloke, Hannah L.

    2017-04-01

    Extreme hot temperatures, such as those experienced during a heat wave, represent a dangerous meteorological hazard to human health. Heat disorders such as sunstroke are harmful to people of all ages and responsible for excess mortality in the affected areas. In 2003 more than 50,000 people died in western and southern Europe because of a severe and sustained episode of summer heat [1]. Furthermore, according to the Intergovernmental Panel on Climate Change heat waves are expected to get more frequent in the future thus posing an increasing threat to human lives. Developing appropriate tools for extreme hot temperatures prediction is therefore mandatory to increase public preparedness and mitigate heat-induced impacts. A recent study has shown that forecasts of the Universal Thermal Climate Index (UTCI) provide a valid overview of extreme temperature health hazards on a global scale [2]. UTCI is a parameter related to the temperature of the human body and its regulatory responses to the surrounding atmospheric environment. UTCI is calculated using an advanced thermo-physiological model that includes the human heat budget, physiology and clothing. To forecast UTCI the model uses meteorological inputs, such as 2m air temperature, 2m water vapour pressure and wind velocity at body height derived from 10m wind speed, from NWP models. Here we examine the potential of UTCI as an extreme hot temperature prediction tool for the European area. UTCI forecasts calculated using above-mentioned parameters from ECMWF models are presented. The skill in predicting UTCI for medium lead times is also analysed and discussed for implementation to international health-hazard warning systems. This research is supported by the ANYWHERE project (EnhANcing emergencY management and response to extreme WeatHER and climate Events) which is funded by the European Commission's HORIZON2020 programme. [1] Koppe C. et al., Heat waves: risks and responses. World Health Organization. Health and

  19. 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

  20. Aggregate vehicle travel forecasting model

    Energy Technology Data Exchange (ETDEWEB)

    Greene, D.L.; Chin, Shih-Miao; Gibson, R. [Tennessee Univ., Knoxville, TN (United States)

    1995-05-01

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

  1. Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts

    Directory of Open Access Journals (Sweden)

    M. P. Mittermaier

    2008-05-01

    Full Text Available A simple measure of the uncertainty associated with using radar-derived rainfall estimates as "truth" has been introduced to the Numerical Weather Prediction (NWP verification process to assess the effect on forecast skill and errors. Deterministic precipitation forecasts from the mesoscale version of the UK Met Office Unified Model for a two-day high-impact event and for a month were verified at the daily and six-hourly time scale using a spatially-based intensity-scale method and various traditional skill scores such as the Equitable Threat Score (ETS and log-odds ratio. Radar-rainfall accumulations from the UK Nimrod radar-composite were used.

    The results show that the inclusion of uncertainty has some effect, shifting the forecast errors and skill. The study also allowed for the comparison of results from the intensity-scale method and traditional skill scores. It showed that the two methods complement each other, one detailing the scale and rainfall accumulation thresholds where the errors occur, the other showing how skillful the forecast is. It was also found that for the six-hourly forecasts the error distributions remain similar with forecast lead time but skill decreases. This highlights the difference between forecast error and forecast skill, and that they are not necessarily the same.

  2. Evaluation of bias-correction methods for ensemble streamflow volume forecasts

    Directory of Open Access Journals (Sweden)

    T. Hashino

    2007-01-01

    Full Text Available Ensemble prediction systems are used operationally to make probabilistic streamflow forecasts for seasonal time scales. However, hydrological models used for ensemble streamflow prediction often have simulation biases that degrade forecast quality and limit the operational usefulness of the forecasts. This study evaluates three bias-correction methods for ensemble streamflow volume forecasts. All three adjust the ensemble traces using a transformation derived with simulated and observed flows from a historical simulation. The quality of probabilistic forecasts issued when using the three bias-correction methods is evaluated using a distributions-oriented verification approach. Comparisons are made of retrospective forecasts of monthly flow volumes for a north-central United States basin (Des Moines River, Iowa, issued sequentially for each month over a 48-year record. The results show that all three bias-correction methods significantly improve forecast quality by eliminating unconditional biases and enhancing the potential skill. Still, subtle differences in the attributes of the bias-corrected forecasts have important implications for their use in operational decision-making. Diagnostic verification distinguishes these attributes in a context meaningful for decision-making, providing criteria to choose among bias-correction methods with comparable skill.

  3. Uncertainty calculation in transport models and forecasts

    DEFF Research Database (Denmark)

    Manzo, Stefano; Prato, Carlo Giacomo

    Transport projects and policy evaluations are often based on transport model output, i.e. traffic flows and derived effects. However, literature has shown that there is often a considerable difference between forecasted and observed traffic flows. This difference causes misallocation of (public......, infrastructure, and regulation) and demand. Uncertainty pertains to everything the modeller does not know to a full extent about the system object of the modelling process due to a limited knowledge or stochasticity of some model components. Thus, ultimately uncertainty reflects the inability of the modeller...... the uncertainty propagation pattern over time specific for key model outputs becomes strategically important. 1 Manzo, S., Nielsen, O. A. & Prato, C. G. (2014). The Effects of uncertainty in speed-flow curve parameters on a large-scale model. Transportation Research Record, 1, 30-37. 2 Manzo, S., Nielsen, O. A...

  4. Two-Step Forecast of Geomagnetic Storm Using Coronal Mass Ejection and Solar Wind Condition

    Science.gov (United States)

    Kim, R.-S.; Moon, Y.-J.; Gopalswamy, N.; Park, Y.-D.; Kim, Y.-H.

    2014-01-01

    To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study (Bz = -5 nT or Ey = 3 mV/m for t = 2 h for moderate storms with minimum Dst less than -50 nT) (i.e. Magnetic Field Magnitude, B (sub z) less than or equal to -5 nanoTeslas or duskward Electrical Field, E (sub y) greater than or equal to 3 millivolts per meter for time greater than or equal to 2 hours for moderate storms with Minimum Disturbance Storm Time, Dst less than -50 nanoTeslas) and a Dst model developed by Temerin and Li (2002, 2006) (TL [i.e. Temerin Li] model). Using 55 CME-Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90 percent) than the forecasts based on the TL model (87 percent). However, the latter produces better forecasts for 24 nonstorm events (88 percent), while the former correctly forecasts only 71 percent of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80 percent) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (n, i.e. cap operator - the intersection set that is comprised of all the elements that are common to both), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81 percent) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (?, i.e. cup operator - the union set that is comprised of all the elements of either or both

  5. Testing efficacy of monthly forecast application in agrometeorology: Winter wheat phenology dynamic

    Science.gov (United States)

    Lalic, B.; Jankovic, D.; Dekic, Lj; Eitzinger, J.; Firanj Sremac, A.

    2017-02-01

    Use of monthly weather forecast as input meteorological data for agrometeorological forecasting, crop modelling and plant protection can foster promising applications in agricultural production. Operational use of monthly or seasonal weather forecast can help farmers to optimize field operations (fertilizing, irrigation) and protection measures against plant diseases and pests by taking full advantage of monthly forecast information in predicting plant development, pest and disease risks and yield potentials few weeks in advance. It can help producers to obtain stable or higher yield with the same inputs and to minimise losses caused by weather. In Central and South-Eastern Europe ongoing climate change lead to shifts of crops phenology dynamics (i.e. in Serbia 4-8 weeks earlier in 2016 than in previous years) and brings this subject in the front of agronomy science and practice. Objective of this study is to test efficacy of monthly forecast in predicting phenology dynamics of different winter wheat varieties, using phenological model developed by Forecasting and Warning Service of Serbia in plant protection. For that purpose, historical monthly forecast for four months (March 1, 2005 - June 30, 2005) was assimilated from ECMWF MARS archive for 50 ensemble members and control run. Impact of different agroecological conditions is tested by using observed and forecasted data for two locations - Rimski Sancevi (Serbia) and Groß-Enzersdorf (Austria).

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

    Science.gov (United States)

    Harris, Andrew J. L.

    2015-04-01

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

  7. Global Forecast System (GFS) [1 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Forecast System (GFS) is a weather forecast model produced by the National Centers for Environmental Prediction (NCEP). Dozens of atmospheric and...

  8. WPC's Short Range Forecast Coded Bulletin

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Short Range Forecast Coded Bulletin. The Short Range Forecast Coded Bulletin describes the expected locations of high and low pressure centers, surface frontal...

  9. Road weather forecast quality analysis : project summary

    Science.gov (United States)

    2006-03-01

    The purpose of this research is to enhance the use of KDOTs Roadway Weather : Information System by improving the weather forecasts themselves and raising the level of : confidence in these forecasts.

  10. Introducing Government Contracts to Technology Forecasting

    National Research Council Canada - National Science Library

    Nikita Sergeyevich Nikitinsky; Dmitry Alexeyevich Ustalov; Sergey Alexandrovich Shashev

    2015-01-01

      Nowadays, technology forecasting has become a multidisciplinary field employing various methods for detecting patterns in data sources in order to forecast trends and future state of different technologies...

  11. Accuracy of forecasts in strategic intelligence.

    Science.gov (United States)

    Mandel, David R; Barnes, Alan

    2014-07-29

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

  12. Forecasting Global Point Rainfall using ECMWF's Ensemble Forecasting System

    Science.gov (United States)

    Pillosu, Fatima; Hewson, Timothy; Zsoter, Ervin; Baugh, Calum

    2017-04-01

    ECMWF (the European Centre for Medium range Weather Forecasts), in collaboration with the EFAS (European Flood Awareness System) and GLOFAS (GLObal Flood Awareness System) teams, has developed a new operational system that post-processes grid box rainfall forecasts from its ensemble forecasting system to provide global probabilistic point-rainfall predictions. The project attains a higher forecasting skill by applying an understanding of how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals. In turn this approach facilitates identification of cases in which very localized extreme totals are much more likely. This approach aims also to improve the rainfall input required in different hydro-meteorological applications. Flash flood forecasting, in particular in urban areas, is a good example. In flash flood scenarios precipitation is typically characterised by high spatial variability and response times are short. In this case, to move beyond radar based now casting, the classical approach has been to use very high resolution hydro-meteorological models. Of course these models are valuable but they can represent only very limited areas, may not be spatially accurate and may give reasonable results only for limited lead times. On the other hand, our method aims to use a very cost-effective approach to downscale global rainfall forecasts to a point scale. It needs only rainfall totals from standard global reporting stations and forecasts over a relatively short period to train it, and it can give good results even up to day 5. For these reasons we believe that this approach better satisfies user needs around the world. This presentation aims to describe two phases of the project: The first phase, already completed, is the implementation of this new system to provide 6 and 12 hourly point-rainfall accumulation probabilities. To do this we use a limited number of physically relevant global model parameters (i

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

    Energy Technology Data Exchange (ETDEWEB)

    Martin Wilde, Principal Investigator

    2012-12-31

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

  14. Microwave observations for forecasting energetic particles from the Sun

    Science.gov (United States)

    Zucca, Pietro; Nuñez, Marlon; Klein, Karl-Ludwig; Malandraki, Olga; Pavlos, Evgenios; Miteva, Rositsa

    2017-04-01

    Solar energetic particles (SEPs), especially protons and heavy ions, are a major space weather hazard when they impact spacecraft and the terrestrial atmosphere. Forecasting schemes have been developed, which use earlier signatures of particle acceleration to predict the arrival of solar protons and ions in the space environment of the Earth. In this study, we investigate the advantages of microwave observations for forecasting the SEP occurrence and SEP energy spectrum. The UMASEP scheme forecasts the occurrence and the importance of a SEP event based on combined observations of soft X-rays, their time derivative, and protons above 10 MeV at geosynchronous orbit. We explore the possibility to replace the derivative of the soft X-ray time history by the microwave time history in the UMASEP scheme. For the forecast of the SEP energy spectrum, we investigate if the hardness or softness of the proton spectrum in interplanetary space can be predicted from the shape of the microwave spectrum. The technique developed by Chertok et al (2009) is to use the ratio of peak microwave flux densities near 9 and 15 GHz as a predictor. Here, we tested this scheme over solar cycle 23 and 24. A detailed analysis of the results including limitations the methods are presented. We conclude that microwave patrol observations improve SEP forecasting schemes that employ soft X-rays. High-quality microwave data available in real time appear as a significant addition to our ability to predict SEP occurrence and their energy spectrum. Acknowledgements: This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 637324

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

    Science.gov (United States)

    Klopfenstein, Bruce C.

    1989-01-01

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

  16. Introducing Government Contracts to Technology Forecasting

    OpenAIRE

    Nikitinsky, Nikita Sergeyevich; Ustalov, Dmitry Alexeyevich; Shashev, Sergey Alexandrovich

    2015-01-01

    Nowadays, technology forecasting has become a multidisciplinary field employing various methods for detecting patterns in data sources in order to forecast trends and future state of different technologies. Technology forecasting is widely used by decision-makers for evaluating grant and contract proposals. Although there are some production-grade systems for technology forecasting for English, Russian patent databases and citation indexes are isolated from the global ones. This makes technol...

  17. A Delphi forecast of technology in education

    Science.gov (United States)

    Robinson, B. E.

    1973-01-01

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

  18. Dynamical forecast vs Ensemble Streamflow Prediction (ESP): how sensitive are monthly and seasonal hydrological forecasts to the quality of rainfall drivers?

    Science.gov (United States)

    Tanguy, Maliko; Prudhomme, Christel; Harrigan, Shaun; Smith, Katie

    2017-04-01

    Seasonal forecasting of hydrological extremes is challenging for the hydro-meteorological modelling community, and the performance of hydrological forecasts at lead times over 1 month is still poor especially for catchments with limited hydrological memory. A considerable amount of effort is being invested within the meteorological community to improve dynamic meteorological forecasting which can then be used to drive hydrological models to produce physically-driven hydrological forecasts. However, currently for the UK, these meteorological forecasts are being produced at 1 month or seasonal time-step, whereas hydrological models often require daily or sub-daily time-steps. A simpler way to get seasonal forecasts is to use historical climate data to drive hydrological models using Ensemble Streamflow Prediction (ESP). This gives a range of possible future hydrological status given known initial conditions, but it does not contain any information on the future dynamic of the atmosphere. The error is highly dependent on the type of catchment, but ESP is an improvement compared to simply using climatology of river flows, especially in groundwater dominated catchments. The objective of this study is to find out how accurate the seasonal rainfall forecast has to be (in terms of total rainfall and temporal distribution) for the dynamical seasonal forecast to beat ESP. To this aim, we have looked at the sensitivity of hydrological models to the quality of driving rainfall input, proxy of 'best possible' forecasts. Study catchments representative of the range of UK's hydro-climatic conditions were selected. For these catchments, synthetic rainfall time series derived from observed data were created by increasingly degrading the data. The number of rainy days, their intensity and their sequencing were artificially modified to analyse which of these characteristics is most important to get a better hydrological forecast using a simple lumped hydrological model (GR4J), and

  19. Industrial enterprises bankruptcy forecasting

    Directory of Open Access Journals (Sweden)

    Dvořáček, J.

    2008-01-01

    Full Text Available This paper addresses problems of bankruptcy prediction. It has been oriented by past and recent situations in the Czech Republic. A brief overview of authors from abroad, who have been involved in investigations of this subject, is given. The circulation of capital is described inclusive intrusive factors that disturb capital’s circulation hampering economic functioning of corporate businesses, which may lead to their final demise. A set of indicators has been specified that reflect the circulation of capital, and which provide for employing a statistical process – discriminate analysis – that links the probability of a corporate business default to these indicators.

  20. Forecasting corn production in Serbia using ARIMA model

    Directory of Open Access Journals (Sweden)

    Ilić Ivana

    2016-01-01

    Full Text Available Agricultural crop production is closely related to climate, as a decisive success factor. Temperature fluctuations and changes in the volume of precipitation are the main factors affecting the growth and development of crops, and, ultimately, the quantity produced. Corn is the most common crop necessary to provide for domestic needs, and a strategic product for export. Production of corn in the period from 1947 to 2014 in Serbia had an oscillatory trend, with significant jumps and falls in production. The subject of this paper is the forecasting of future trends in corn production in Serbia. Building on the subject, the purpose of this paper is to create the model for forecasting future corn production and establishing its trends.

  1. Validating quantitative precipitation forecast for the Flood ...

    Indian Academy of Sciences (India)

    In tropical regions like India, weather forecasting by using statistical and numerical methods is quite useful for operational purpose. In view of this, quantitative precipitation forecast (QPF) might be done by adopting conventional synoptic analysis method since it can serve as a potential tool for operational flood forecasting ...

  2. Urban runoff forecasting with ensemble weather predictions

    DEFF Research Database (Denmark)

    Pedersen, Jonas Wied; Courdent, Vianney Augustin Thomas; Vezzaro, Luca

    This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice....

  3. Location specific forecasting of maximum and minimum ...

    Indian Academy of Sciences (India)

    But, accurate forecasting of surface param- eters, particularly maximum and minimum tem- peratures over India, is a difficult task due to. Keywords. Statistical bias correction; location specific forecast; DMO; Numerical Weather Prediction; maximum and minimum temperature forecast. J. Earth Syst. Sci. 123, No. 5, July 2014 ...

  4. New interval forecast for stationary autoregressive models ...

    African Journals Online (AJOL)

    In this paper, we proposed a new forecasting interval for stationary Autoregressive, AR(p) models using the Akaike information criterion (AIC) function. Ordinarily, the AIC function is used to determine the order of an AR(p) process. In this study however, AIC forecast interval compared favorably with the theoretical forecast ...

  5. Can Business Students Forecast Their Own Grade?

    Science.gov (United States)

    Hossain, Belayet; Tsigaris, Panagiotis

    2013-01-01

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

  6. Interval Forecast for Smooth Transition Autoregressive Model ...

    African Journals Online (AJOL)

    In this paper, we propose a simple method for constructing interval forecast for smooth transition autoregressive (STAR) model. This interval forecast is based on bootstrapping the residual error of the estimated STAR model for each forecast horizon and computing various Akaike information criterion (AIC) function. This new ...

  7. Seasonal Streamflow Forecasts for African Basins

    Science.gov (United States)

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

    2015-12-01

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

  8. Intermittent demand : Linking forecasting to inventory obsolescence

    NARCIS (Netherlands)

    Teunter, Ruud H.; Syntetos, Aris A.; Babai, M. Zied

    2011-01-01

    The standard method to forecast intermittent demand is that by Croston. This method is available in ERP-type solutions such as SAP and specialised forecasting software packages (e.g. Forecast Pro), and often applied in practice. It uses exponential smoothing to separately update the estimated demand

  9. Forecasting Market Shares from Models for Sales

    NARCIS (Netherlands)

    D. Fok (Dennis); Ph.H.B.F. Franses (Philip Hans)

    2000-01-01

    textabstractDividing forecasts of brand sales by a forecast of category sales, when they are generated from brand specific sales-response models, renders biased forecasts of the brands' market shares. In this paper we therefore propose an easy-to-apply simulation-based method which results in

  10. Location specific forecasting of maximum and minimum ...

    Indian Academy of Sciences (India)

    Statistical bias correction; location specific forecast; DMO; Numerical Weather Prediction; maximum and minimum temperature forecast. Abstract. The output from Global Forecasting System (GFS) T574L64 operational at India Meteorological Department (IMD), New Delhi is used for obtaining location specific quantitative ...

  11. Forecasting Interest Rates and Inflation

    DEFF Research Database (Denmark)

    Chun, Albert Lee

    the best overall for short horizon forecasts of short to medium term yields and inflation. Econometric models with shrinkage perform the best over longer horizons and maturities. Aggregating over a larger set of analysts improves inflation surveys while generally degrading interest rates surveys. We...

  12. In Brief: Forecasting meningitis threats

    Science.gov (United States)

    Showstack, Randy

    2008-12-01

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

  13. Forecasting the space weather impact

    DEFF Research Database (Denmark)

    Crosby, N. B.; Veronig, A.; Robbrecht, E.

    2012-01-01

    The FP7 COronal Mass Ejections and Solar Energetic Particles (COMESEP) project is developing tools for forecasting geomagnetic storms and solar energetic particle (SEP) radiation storms. By analysis of historical data, complemented by the extensive data coverage of solar cycle 23, the key ingredi...

  14. Understanding and Forecasting Ethnolinguistic Vitality

    Science.gov (United States)

    Karan, Mark E.

    2011-01-01

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

  15. Using forecast and observed weather data to assess performance of forecast products in identifying heat waves and estimating heat wave effects on mortality.

    Science.gov (United States)

    Zhang, Kai; Chen, Yeh-Hsin; Schwartz, Joel D; Rood, Richard B; O'Neill, Marie S

    2014-09-01

    Heat wave and health warning systems are activated based on forecasts of health-threatening hot weather. We estimated heat-mortality associations based on forecast and observed weather data in Detroit, Michigan, and compared the accuracy of forecast products for predicting heat waves. We derived and compared apparent temperature (AT) and heat wave days (with heat waves defined as ≥ 2 days of daily mean AT ≥ 95th percentile of warm-season average) from weather observations and six different forecast products. We used Poisson regression with and without adjustment for ozone and/or PM10 (particulate matter with aerodynamic diameter ≤ 10 μm) to estimate and compare associations of daily all-cause mortality with observed and predicted AT and heat wave days. The 1-day-ahead forecast of a local operational product, Revised Digital Forecast, had about half the number of false positives compared with all other forecasts. On average, controlling for heat waves, days with observed AT = 25.3°C were associated with 3.5% higher mortality (95% CI: -1.6, 8.8%) than days with AT = 8.5°C. Observed heat wave days were associated with 6.2% higher mortality (95% CI: -0.4, 13.2%) than non-heat wave days. The accuracy of predictions varied, but associations between mortality and forecast heat generally tended to overestimate heat effects, whereas associations with forecast heat waves tended to underestimate heat wave effects, relative to associations based on observed weather metrics. Our findings suggest that incorporating knowledge of local conditions may improve the accuracy of predictions used to activate heat wave and health warning systems.

  16. SUBJECT INDEX

    Indian Academy of Sciences (India)

    M. Senthilkumar (Newgen Imaging) 1461 1996 Oct 15 13:05:22

    Ocean-atmosphere interaction and synoptic weather conditions in association with the two contrasting phases of monsoon during BOBMEX-1999. 283. Baseline lengths. Pre-seismic, co-seismic and post-seismic displace- ments associated with the Bhuj 2001 earthquake derived from recent and historic geodetic data 331.

  17. Adaptive correction of ensemble forecasts

    Science.gov (United States)

    Pelosi, Anna; Battista Chirico, Giovanni; Van den Bergh, Joris; Vannitsem, Stephane

    2017-04-01

    Forecasts from numerical weather prediction (NWP) models often suffer from both systematic and non-systematic errors. These are present in both deterministic and ensemble forecasts, and originate from various sources such as model error and subgrid variability. Statistical post-processing techniques can partly remove such errors, which is particularly important when NWP outputs concerning surface weather variables are employed for site specific applications. Many different post-processing techniques have been developed. For deterministic forecasts, adaptive methods such as the Kalman filter are often used, which sequentially post-process the forecasts by continuously updating the correction parameters as new ground observations become available. These methods are especially valuable when long training data sets do not exist. For ensemble forecasts, well-known techniques are ensemble model output statistics (EMOS), and so-called "member-by-member" approaches (MBM). Here, we introduce a new adaptive post-processing technique for ensemble predictions. The proposed method is a sequential Kalman filtering technique that fully exploits the information content of the ensemble. One correction equation is retrieved and applied to all members, however the parameters of the regression equations are retrieved by exploiting the second order statistics of the forecast ensemble. We compare our new method with two other techniques: a simple method that makes use of a running bias correction of the ensemble mean, and an MBM post-processing approach that rescales the ensemble mean and spread, based on minimization of the Continuous Ranked Probability Score (CRPS). We perform a verification study for the region of Campania in southern Italy. We use two years (2014-2015) of daily meteorological observations of 2-meter temperature and 10-meter wind speed from 18 ground-based automatic weather stations distributed across the region, comparing them with the corresponding COSMO

  18. SUBJECT INDEX

    Indian Academy of Sciences (India)

    Subject Index. Variation of surface electric field during geomagnetic disturbed period at Maitri, Antarctica. 1721. Geomorphology. A simple depression-filling method for raster and irregular elevation datasets. 1653. Decision Support System integrated with Geographic. Information System to target restoration actions in water-.

  19. Comparison of statistical post-processing methods for probabilistic wind speed forecasting

    Science.gov (United States)

    Han, Keunhee; Choi, JunTae; Kim, Chansoo

    2017-12-01

    In this study, the statistical post-processing methods that include bias-corrected and probabilistic forecasts of wind speed measured in PyeongChang, which is scheduled to host the 2018 Winter Olympics, are compared and analyzed to provide more accurate weather information. The six post-processing methods used in this study are as follows: mean bias-corrected forecast, mean and variance bias-corrected forecast, decaying averaging forecast, mean absolute bias-corrected forecast, and the alternative implementations of ensemble model output statistics (EMOS) and Bayesian model averaging (BMA) models, which are EMOS and BMA exchangeable models by assuming exchangeable ensemble members and simplified version of EMOS and BMA models. Observations for wind speed were obtained from the 26 stations in PyeongChang and 51 ensemble member forecasts derived from the European Centre for Medium-Range Weather Forecasts (ECMWF Directorate, 2012) that were obtained between 1 May 2013 and 18 March 2016. Prior to applying the post-processing methods, reliability analysis was conducted by using rank histograms to identify the statistical consistency of ensemble forecast and corresponding observations. Based on the results of our study, we found that the prediction skills of probabilistic forecasts of EMOS and BMA models were superior to the biascorrected forecasts in terms of deterministic prediction, whereas in probabilistic prediction, BMA models showed better prediction skill than EMOS. Even though the simplified version of BMA model exhibited best prediction skill among the mentioned six methods, the results showed that the differences of prediction skills between the versions of EMOS and BMA were negligible.

  20. The non-alcoholic fraction of beer increases stromal cell derived factor 1 and the number of circulating endothelial progenitor cells in high cardiovascular risk subjects: a randomized clinical trial.

    Science.gov (United States)

    Chiva-Blanch, Gemma; Condines, Ximena; Magraner, Emma; Roth, Irene; Valderas-Martínez, Palmira; Arranz, Sara; Casas, Rosa; Martínez-Huélamo, Miriam; Vallverdú-Queralt, Anna; Quifer-Rada, Paola; Lamuela-Raventos, Rosa M; Estruch, Ramon

    2014-04-01

    Moderate alcohol consumption is associated with a decrease in cardiovascular risk, but fermented beverages seem to confer greater cardiovascular protection due to their polyphenolic content. Circulating endothelial progenitor cells (EPC) are bone-marrow-derived stem cells with the ability to repair and maintain endothelial integrity and function and are considered as a surrogate marker of vascular function and cumulative cardiovascular risk. Nevertheless, no study has been carried out on the effects of moderate beer consumption on the number of circulating EPC in high cardiovascular risk patients. To compare the effects of moderate consumption of beer, non-alcoholic beer and gin on the number of circulating EPC and EPC-mobilizing factors. In this crossover trial, 33 men at high cardiovascular risk were randomized to receive beer (30 g alcohol/d), the equivalent amount of polyphenols in the form of non-alcoholic beer, or gin (30 g alcohol/d) for 4 weeks. Diet and physical exercise were carefully monitored. The number of circulating EPC and EPC-mobilizing factors were determined at baseline and after each intervention. After the beer and non-alcoholic beer interventions, the number of circulating EPC significantly increased by 8 and 5 units, respectively, while no significant differences were observed after the gin period. In correlation, stromal cell derived factor 1 increased significantly after the non-alcoholic and the beer interventions. The non-alcoholic fraction of beer increases the number of circulating EPC in peripheral blood from high cardiovascular risk subjects. http://www.controlled-trials.com/ISRCTN95345245 ISRCTN95345245. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  1. Online load forecasting for supermarket refrigeration

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

    2013-01-01

    This paper presents a study of models for forecasting the load for supermarket refrigeration. The data used for building the forecasting models consists of load measurements, local climate measurements and weather forecasts. The load measurements are from a supermarket located in a village...... in Denmark. Every hour the hourly load for refrigeration for the following 42 hours is forecasted. The forecast models are time adaptive linear time-series models. The dynamic relations between the inputs and the load is modeled by simple transfer functions. The system operates in two regimes: one...

  2. Forecasting Interest Rates Using Geostatistical Techniques

    Directory of Open Access Journals (Sweden)

    Giuseppe Arbia

    2015-11-01

    Full Text Available Geostatistical spatial models are widely used in many applied fields to forecast data observed on continuous three-dimensional surfaces. We propose to extend their use to finance and, in particular, to forecasting yield curves. We present the results of an empirical application where we apply the proposed method to forecast Euro Zero Rates (2003–2014 using the Ordinary Kriging method based on the anisotropic variogram. Furthermore, a comparison with other recent methods for forecasting yield curves is proposed. The results show that the model is characterized by good levels of predictions’ accuracy and it is competitive with the other forecasting models considered.

  3. Data Assimilation of AIRS Water Vapor Profiles: Impact on Precipitation Forecasts for Atmospheric River Cases Affecting the Western of the United States

    Science.gov (United States)

    Blankenship, Clay; Zavodsky, Bradley; Jedlovec, Gary; Wick, Gary; Neiman, Paul

    2013-01-01

    Atmospheric rivers are transient, narrow regions in the atmosphere responsible for the transport of large amounts of water vapor. These phenomena can have a large impact on precipitation. In particular, they can be responsible for intense rain events on the western coast of North America during the winter season. This paper focuses on attempts to improve forecasts of heavy precipitation events in the Western US due to atmospheric rivers. Profiles of water vapor derived from from Atmospheric Infrared Sounder (AIRS) observations are combined with GFS forecasts by a three-dimensional variational data assimilation in the Gridpoint Statistical Interpolation (GSI). Weather Research and Forecasting (WRF) forecasts initialized from the combined field are compared to forecasts initialized from the GFS forecast only for 3 test cases in the winter of 2011. Results will be presented showing the impact of the AIRS profile data on water vapor and temperature fields, and on the resultant precipitation forecasts.

  4. Quantile forecast discrimination ability and value

    DEFF Research Database (Denmark)

    Ben Bouallègue, Zied; Pinson, Pierre; Friederichs, Petra

    2015-01-01

    While probabilistic forecast verification for categorical forecasts is well established, some of the existing concepts and methods have not found their equivalent for the case of continuous variables. New tools dedicated to the assessment of forecast discrimination ability and forecast value are ...... is illustrated based on synthetic datasets, as well as for the case of global radiation forecasts from the high resolution ensemble COSMO-DE-EPS of the German Weather Service.......While probabilistic forecast verification for categorical forecasts is well established, some of the existing concepts and methods have not found their equivalent for the case of continuous variables. New tools dedicated to the assessment of forecast discrimination ability and forecast value...... are introduced here, based on quantile forecasts being the base product for the continuous case. The relative user characteristic (RUC) curve and the quantile value plot allow analysing the performance of a forecast for a specific user in a decision-making framework. The RUC curve is designed as a user...

  5. How to Improve the SPF Forecasts?

    Directory of Open Access Journals (Sweden)

    Bratu (Simionescu Mihaela

    2013-04-01

    Full Text Available The reduction of forecasts uncertainty is one of the major goal to be achieved in forecasting process. This implies the improvement of predictions accuracy. In this study, many types of forecasts of the annual rate of change for the HICP for EU were developed, their accuracy was evaluated and compared with the accuracy of SPF predictions. All the proposed predictions for January 2010-May 2012 (those based on a random walk developed for 1997-2009, combined forecasts, the median and the mean of forecasts, predictions based on different econometric models that take into account the previous SPF forecasts were not more accurate than the naïve forecasts or SPF ones. A considerably improvement of the accuracy was gotten for predictions based on mean error of SPF expectations for 1997-2009 and the previous registered value. This empirical strategy of building more accurate forecasts was better than the classical theoretical approaches from literature, but it is still less accurate than the naïve forecasts that could be made for UE inflation rate. So, the forecasts based on a simple econometric model as the random walk from the naïve approach are the most accurate, conclusion that is in accordance with the latest researches in literature and with one of the essential condition in forecasting theory.

  6. Polynomial Chaos Based Acoustic Uncertainty Predictions from Ocean Forecast Ensembles

    Science.gov (United States)

    Dennis, S.

    2016-02-01

    Most significant ocean acoustic propagation occurs at tens of kilometers, at scales small compared basin and to most fine scale ocean modeling. To address the increased emphasis on uncertainty quantification, for example transmission loss (TL) probability density functions (PDF) within some radius, a polynomial chaos (PC) based method is utilized. In order to capture uncertainty in ocean modeling, Navy Coastal Ocean Model (NCOM) now includes ensembles distributed to reflect the ocean analysis statistics. Since the ensembles are included in the data assimilation for the new forecast ensembles, the acoustic modeling uses the ensemble predictions in a similar fashion for creating sound speed distribution over an acoustically relevant domain. Within an acoustic domain, singular value decomposition over the combined time-space structure of the sound speeds can be used to create Karhunen-Loève expansions of sound speed, subject to multivariate normality testing. These sound speed expansions serve as a basis for Hermite polynomial chaos expansions of derived quantities, in particular TL. The PC expansion coefficients result from so-called non-intrusive methods, involving evaluation of TL at multi-dimensional Gauss-Hermite quadrature collocation points. Traditional TL calculation from standard acoustic propagation modeling could be prohibitively time consuming at all multi-dimensional collocation points. This method employs Smolyak order and gridding methods to allow adaptive sub-sampling of the collocation points to determine only the most significant PC expansion coefficients to within a preset tolerance. Practically, the Smolyak order and grid sizes grow only polynomially in the number of Karhunen-Loève terms, alleviating the curse of dimensionality. The resulting TL PC coefficients allow the determination of TL PDF normality and its mean and standard deviation. In the non-normal case, PC Monte Carlo methods are used to rapidly establish the PDF. This work was

  7. Effective Feature Preprocessing for Time Series Forecasting

    DEFF Research Database (Denmark)

    Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

    2006-01-01

    Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting......, there is so far no systematic research to study and compare their performance. How to select effective techniques of feature preprocessing in a forecasting model remains a problem. In this paper, the authors conduct a comprehensive study of existing feature preprocessing techniques to evaluate their empirical...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...

  8. Measuring inaccuracy in travel demand forecasting

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent

    2005-01-01

    Project promoters, forecasters, and managers sometimes object to two things in measuring inaccuracy in travel demand forecasting: (1)using the forecast made at the time of making the decision to build as the basis for measuring inaccuracy and (2)using traffic during the first year of operations...... as the basis for measurement. This paper presents the case against both objections. First, if one is interested in learning whether decisions about building transport infrastructure are based on reliable information, then it is exactly the traffic forecasted at the time of making the decision to build...... in travel demand forecasts are likely to be conservatively biased, i.e., accuracy in travel demand forecasts estimated from such samples would likely be higher than accuracy in travel demand forecasts in the project population. This bias must be taken into account when interpreting the results from...

  9. Regional air-quality forecasting for the Pacific Northwest using MOPITT/TERRA assimilated carbon monoxide MOZART-4 forecasts as a near real-time boundary condition

    Directory of Open Access Journals (Sweden)

    F. L. Herron-Thorpe

    2012-06-01

    Full Text Available Results from a regional air quality forecast model, AIRPACT-3, were compared to AIRS carbon monoxide column densities for the spring of 2010 over the Pacific Northwest. AIRPACT-3 column densities showed high correlation (R > 0.9 but were significantly biased (~25% with consistent under-predictions for spring months when there is significant transport from Asia. The AIRPACT-3 CO bias relative to AIRS was eliminated by incorporating dynamic boundary conditions derived from NCAR's MOZART forecasts with assimilated MOPITT carbon monoxide. Changes in ozone-related boundary conditions derived from MOZART forecasts are also discussed and found to affect background levels by ± 10 ppb but not found to significantly affect peak ozone surface concentrations.

  10. Validation of FOAM near-surface ocean current forecasts using Lagrangian drifting buoys

    Science.gov (United States)

    Blockley, E. W.; Martin, M. J.; Hyder, P.

    2012-07-01

    In this study, the quality of near-surface current forecasts from the FOAM ocean forecasting system is assessed using the trajectories of Lagrangian drifting buoys. A method is presented for deriving pseudo-Eulerian estimates of ocean currents from the positions of Surface Velocity Program drifters and the resulting data are compared to velocities observed by the global tropical moored buoy array. A quantitative analysis of the global FOAM velocities is performed for the period 2007 and 2008 using currents derived from over 3000 unique drifters (providing an average of 650 velocity observations per day). A potential bias is identified in the Southern Ocean which appears to be caused by wind-slip in the drifter dataset as a result of drogue loss. The drifter-derived currents are also used to show how the data assimilation scheme and a recent system upgrade impact upon the quality of FOAM current forecasts.

  11. Validation of FOAM near-surface ocean current forecasts using Lagrangian drifting buoys

    Directory of Open Access Journals (Sweden)

    E. W. Blockley

    2012-07-01

    Full Text Available In this study, the quality of near-surface current forecasts from the FOAM ocean forecasting system is assessed using the trajectories of Lagrangian drifting buoys. A method is presented for deriving pseudo-Eulerian estimates of ocean currents from the positions of Surface Velocity Program drifters and the resulting data are compared to velocities observed by the global tropical moored buoy array. A quantitative analysis of the global FOAM velocities is performed for the period 2007 and 2008 using currents derived from over 3000 unique drifters (providing an average of 650 velocity observations per day. A potential bias is identified in the Southern Ocean which appears to be caused by wind-slip in the drifter dataset as a result of drogue loss. The drifter-derived currents are also used to show how the data assimilation scheme and a recent system upgrade impact upon the quality of FOAM current forecasts.

  12. Fine-Scale Road Stretch Forecasting along Main Danish Roads

    Science.gov (United States)

    Mahura, A.; Petersen, C.; Sattler, K.; Sass, B.

    2009-09-01

    and fine height accuracy. The main aim of this study is to research, analyze, develop, and improve the quality of the road condition forecasts by refining, detalization, setting up, and running the fine-scale resolution numerical weather prediction (NWP) model with integration (from high resolution databases) of characteristics and derived parameters of surrounding roads the land-use, terrain, positioning and road properties at road stations/ stretches. The objectives include, at first, research and development of the existing road model based on input from a fine-scale NWP modelling. At second, it is analysis and integration of detailed data and derived parameters at road stations/stretches into the RCM based on available detailed Danish datasets on terrain, GPS positioning, land-use, and road properties. And at third, it is elaboration, testing, evaluation, and implementation of the methods and approaches suitable for forecasting and verification of the RCM performance for fine-scales. The results of this study are applicable for improvement of quality of detailed forecasts at road stretches. This will facilitate the use of data from the road stretch forecasting to automatic adjustment of control of the dosage spread by salting spreaders (i.e. for optimization of the salt amount spreaded in order to prevent the icing/freezing and better timing of salting schedule). It will lead to improvement of the overall safety of the winter road traffic. It will contribute to further development and improvement of the visualization tools for the road stretches forecasting. And it may reduce the environmental impact in the road surroundings due to an optimized spreading of the salt.

  13. On forecasting ionospheric total electron content responses to high-speed solar wind streams

    Directory of Open Access Journals (Sweden)

    Meng Xing

    2016-01-01

    Full Text Available Conditions in the ionosphere have become increasingly important to forecast, since more and more spaceborne and ground-based technological systems rely on ionospheric weather. Here we explore the feasibility of ionospheric forecasts with the current generation of physics-based models. In particular, we focus on total electron content (TEC predictions using the Global Ionosphere-Thermosphere Model (GITM. Simulations are configured in a forecast mode and performed for four typical high-speed-stream events during 2007–2012. The simulated TECs are quantified through a metric, which divides the globe into a number of local regions and robustly differentiates between quiet and disturbed periods. Proposed forecast products are hourly global maps color-coded by the TEC disturbance level of each local region. To assess the forecasts, we compare the simulated TEC disturbances with global TEC maps derived from Global Positioning System (GPS satellite observations. The forecast performance is found to be merely acceptable, with a large number of regions where the observed variations are not captured by the simulations. Examples of model-data agreements and disagreements are investigated in detail, aiming to understand the model behavior and improve future forecasts. For one event, we identify two adjacent regions with similar TEC observations but significant differences in how local chemistry versus plasma transport contribute to electron density changes in the simulation. Suggestions for further analysis are described.

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

    Science.gov (United States)

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

    2017-04-01

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

  15. Forecasting spot prices in bulk shipping using multivariate and univariate models

    Directory of Open Access Journals (Sweden)

    N.D. Geomelos

    2014-12-01

    Full Text Available This paper employs an applied econometric study concerning forecasting spot prices in bulk shipping in both markets of tankers and bulk carriers in a disaggregated level. This research is essential, as spot market is one of the most volatile markets and there is a great uncertainty about the future development of spot prices. This uncertainty could be reduced by using estimates of ex-post and ex-ante forecasts. Econometric analysis focuses in the comparison of different econometric models from two important categories of econometrics: (1 multivariate models (VAR and VECM and (2 univariate time series models (ARIMA, GARCH and E-GARCH in order to derive the best predicting model for each ship type. Also, forecasts can be modified to yield an improved performance of forecasting accuracy via the theory of combining methods. Ex-post and ex-ante forecasts are estimated on the basis of best predicting model’s performance. Results show that the combining methodology can reduce even more the forecasting errors. The results of empirical analysis could also be useful from the specialization, identification, estimation, and evaluation of previous econometric models’ point of view. Also, ex-ante forecasts, which are taking into consideration the present economic crisis, can be used for the formation of efficient economic policy from decision-makers of shipping industry reducing even more spot markets’ risk.

  16. Visualization of uncertainties and forecast skill in user-tailored seasonal climate predictions for agriculture

    Science.gov (United States)

    Sedlmeier, Katrin; Gubler, Stefanie; Spierig, Christoph; Flubacher, Moritz; Maurer, Felix; Quevedo, Karim; Escajadillo, Yury; Avalos, Griña; Liniger, Mark A.; Schwierz, Cornelia

    2017-04-01

    Seasonal climate forecast products potentially have a high value for users of different sectors. During the first phase (2012-2015) of the project CLIMANDES (a pilot project of the Global Framework for Climate Services led by WMO [http://www.wmo.int/gfcs/climandes]), a demand study conducted with Peruvian farmers indicated a large interest in seasonal climate information for agriculture. The study further showed that the required information should by precise, timely, and understandable. In addition to the actual forecast, two complex measures are essential to understand seasonal climate predictions and their limitations correctly: forecast uncertainty and forecast skill. The former can be sampled by using an ensemble of climate simulations, the latter derived by comparing forecasts of past time periods to observations. Including uncertainty and skill information in an understandable way for end-users (who are often not technically educated) poses a great challenge. However, neglecting this information would lead to a false sense of determinism which could prove fatal to the credibility of climate information. Within the second phase (2016-2018) of the project CLIMANDES, one goal is to develop a prototype of a user-tailored seasonal forecast for the agricultural sector in Peru. In this local context, the basic education level of the rural farming community presents a major challenge for the communication of seasonal climate predictions. This contribution proposes different graphical presentations of climate forecasts along with possible approaches to visualize and communicate the associated skill and uncertainties, considering end users with varying levels of technical knowledge.

  17. The New Era in Operational Forecasting

    Science.gov (United States)

    Tobiska, W.; Schunk, R. W.; Sojka, J. J.; Carlson, H. C.; Gardner, L. C.; Scherliess, L.; Zhu, L.; Eccles, J. V.; Rice, D. D.; Bouwer, D.; Bailey, J. J.; Knipp, D. J.; Blake, J. B.; Rex, J.; Fuschino, R.; Mertens, C. J.; Gersey, B.; Wilkins, R.; Atwell, W.

    2012-12-01

    also provides the space weather smartphone app called SpaceWx for iPhone, iPad, iPod, and Android for professional users and public space weather education. SpaceWx displays the real-time solar, heliosphere, magnetosphere, thermosphere, and ionosphere drivers to changes in the total electron content, for example, as well as global NVIS maps. We describe recent forecasting advances for moving space weather information through automated systems into operational, derivative products for communications, aviation, and satellite operations uses.

  18. The use of HBV model for flash flood forecasting

    Directory of Open Access Journals (Sweden)

    M. Kobold

    2006-01-01

    Full Text Available The standard conceptual HBV model was originally developed with daily data and is normally operated on daily time step. But many floods in Slovenia are usually flash floods as result of intense frontal precipitation combined with orographic enhancement. Peak discharges are maintained only for hours or even minutes. To use the HBV model for flash flood forecasting, the version of HBV-96 has been applied on the catchment with complex topography with the time step of one hour. The recording raingauges giving hourly values of precipitation have been taken in calibration of the model. The uncertainty of simulated runoff is mainly the result of precipitation uncertainty associated with the mean areal precipitation and is higher for mountainous catchments. Therefore the influence of number of raingauges used to derive the areal precipitation by the method of Thiessen polygons was investigated. The quantification of hydrological uncertainty has been performed by analysis of sensitivity of the HBV model to error in precipitation input. The results show that an error of 10% in the amount of precipitation causes an error of 17% in the peak of flood wave. The polynomial equations showing the relationship between the errors in rainfall amounts and peak discharges were derived for two water stations on the Savinja catchment. Simulated discharges of half-yearly runs demonstrate the applicability of the HBV model for flash flood forecasting using the mesoscale meteorological forecasts of ALADIN/SI model as input precipitation data.

  19. Modelling and forecasting monthly swordfish catches in the Eastern Mediterranean

    Directory of Open Access Journals (Sweden)

    Konstantinos I. Stergiou

    2003-04-01

    Full Text Available In this study, we used the X-11 census technique for modelling and forecasting the monthly swordfish (Xiphias gladius catches in the Greek Seas during 1982-1996 and 1997 respectively, using catches reported by the National Statistical Service of Greece (NSSG. Forecasts built with X-11 were also compared with those derived from ARIMA andWinter’s exponential smoothing (WES models. The X-11 method captured the features of the study series and outperformed the other two methods, in terms of both fitting and forecasting performance, for all the accuracy measures used. Thus, with the exception of October, November and December 1997, when the corresponding absolute percentage error(APE values were very high (as high as 178.6% because of the low level of the catches, monthly catches during the remaining months of 1997 were predicted accurately, with a mean APE of 12.5%. In contrast, the mean APE values of the other two methods for the same months were higher (ARIMA: 14.6%; WES: 16.6%. The overall good performance of X-11 andthe fact that it provides an insight into the various components (i.e. the seasonal, trend-cycle and irregular components of the time series of interest justify its use in fisheries research. The basic features of the swordfish catches revealed by the application of the X-11 method, the effect of the length of the forecasting horizon on forecasting accuracy and the accuracy of the catches reported by NSSG are also discussed.

  20. Characteristics of the Polarity Inversion Line and Solar Flare Forecasts

    Science.gov (United States)

    Sadykov, Viacheslav M.; Kosovichev, Alexander G.

    2017-08-01

    Studying connection between solar flares and properties of magnetic field in active regions is very important for understanding the flare physics and developing space weather forecasts. In this work, we analyze relationship between the flare X-ray peak flux from the GOES satellite, and characteristics of the line-of-sight (LOS) magnetograms obtained by the SDO/HMI instrument during the period of April, 2010 - June, 2016. We try to answer two questions: 1) What characteristics of the LOS magnetic field are most important for the flare initiation and magnitude? 2) Is it possible to construct a reliable forecast of ≥ M1.0 and ≥ X1.0 class flares based only on the LOS magnetic field characteristics? To answer these questions, we apply a Polarity Inversion Line (PIL) detection algorithm, and derive various properties of the PIL and the corresponding Active Regions (AR). The importance of these properties for flare forecasting is determined by their ability to separate flaring cases from non-flaring, and their Fisher ranking score. It is found that the PIL characteristics are of special importance for the forecasts of both ≥ M1.0 and ≥ X1.0 flares, while the global AR characteristics become comparably discriminative only for ≥ X1.0 flares. We use the Support Vector Machine (SVM) classifier and train it on the six characteristics of the most importance for each case. The obtained True Skill Statistics (TSS) values of 0.70 for ≥ M1.0 flares and 0.64 for ≥ X1.0 flares are better than the currently-known expert-based predictions. Therefore, the results confirm the importance of the LOS magnetic field data and, in particular, the PIL region characteristics for flare forecasts.

  1. Judgmental Forecasting of Operational Capabilities

    OpenAIRE

    Hallin, Carina Antonia; Tveterås, Sigbjørn; Andersen, Torben Juul

    2012-01-01

    This paper explores a new judgmental forecasting indicator, the Employee Sensed Operational Capabilities (ESOC). The purpose of the ESOC is to establish a practical prediction tool that can provide early signals about changes in financial performance by gauging frontline employees’ sensing of changes in the firm’s operational capabilities. We present the first stage of the development of ESOC by applying a formative measurement approach to test the index in relation to financia...

  2. Confessions of an International Forecaster

    OpenAIRE

    Thomas M. Fullerton Jr

    2004-01-01

    Impacts of the availability of low cost computing power on macroeconometric forecasting and research in Latin America are widespread. One of the most immediate effects of the adoption of microcomputing hardware was more rapid adoption of new econometric estimation techniques. Easier development and maintenace of large-scale modeling systems for individual economies also became feasible. Greater flexibility in analyzing major policy innovations such as the Brady initiative for international de...

  3. Communicating uncertainty in hydrological forecasts: mission impossible?

    Science.gov (United States)

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

    2010-05-01

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

  4. Type- and Subtype-Specific Influenza Forecast.

    Science.gov (United States)

    Kandula, Sasikiran; Yang, Wan; Shaman, Jeffrey

    2017-03-01

    Prediction of the growth and decline of infectious disease incidence has advanced considerably in recent years. As these forecasts improve, their public health utility should increase, particularly as interventions are developed that make explicit use of forecast information. It is the task of the research community to increase the content and improve the accuracy of these infectious disease predictions. Presently, operational real-time forecasts of total influenza incidence are produced at the municipal and state level in the United States. These forecasts are generated using ensemble simulations depicting local influenza transmission dynamics, which have been optimized prior to forecast with observations of influenza incidence and data assimilation methods. Here, we explore whether forecasts targeted to predict influenza by type and subtype during 2003-2015 in the United States were more or less accurate than forecasts targeted to predict total influenza incidence. We found that forecasts separated by type/subtype generally produced more accurate predictions and, when summed, produced more accurate predictions of total influenza incidence. These findings indicate that monitoring influenza by type and subtype not only provides more detailed observational content but supports more accurate forecasting. More accurate forecasting can help officials better respond to and plan for current and future influenza activity. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  5. Ensemble approach to wheat yield forecasting in Ukraine

    Science.gov (United States)

    Kussul, Nataliia; Kolotii, Andrii; Skakun, Sergii; Shelestov, Andrii; Kussul, Olga; Kravchenko, Oleksii

    2014-05-01

    Crop yield forecasting is an extremely important component of the agriculture monitoring domain. In our previous study [1], we assessed relative efficiency and feasibility of using an NDVI-based empirical model for winter wheat yield forecasting at oblast level in Ukraine. Though the NDVI-based model provides minimum data requirements, it has some limitations since NDVI is indirectly related just to biomass but not meteorological conditions. Therefore, it is necessary to assess satellite-derived parameters that incorporate meteorology while maintaining the requirement of minimum data inputs. The objective of the proposed paper is several-fold: (i) to assess efficiency of using biophysical satellite-derived parameters for crop yield forecasting for Ukraine and select the optimal ones based on rigorous feature selection procedure; (ii) to assimilate predictions made by models built on various satellite-derived parameters. Two new parameters are considered in the paper: (i) vegetation health index (VHI) at 4 km spatial resolution derived from a series of NOAA satellites; (ii) Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) derived from SPOT-VEGETATION at 1 km spatial resolution. VHI data are provided as weekly composites and FAPAR data are provided as decadal composites. The particular advantage of using VHI is that it incorporates moisture and thermal conditions of vegetation canopy, while FAPAR is directly related to the primary productivity of photosynthesis It is required to find a day of the year for which a parameter is taken and used in the empirical model. For this purpose, a Random Forest feature selection procedure is applied. It is found that VHI and FAPAR values taken in April-May provided the minimum error value when comparing to the official statistics, thus enabling forecasts 2-3 months prior to harvest, and this corresponds to results derived from LOOCV procedure. The best timing for making reliable yield forecasts is nearly the same

  6. Forecasting the brittle failure of heterogeneous, porous geomaterials

    Science.gov (United States)

    Vasseur, Jérémie; Wadsworth, Fabian; Heap, Michael; Main, Ian; Lavallée, Yan; Dingwell, Donald

    2017-04-01

    Heterogeneity develops in magmas during ascent and is dominated by the development of crystal and importantly, bubble populations or pore-network clusters which grow, interact, localize, coalesce, outgas and resorb. Pore-scale heterogeneity is also ubiquitous in sedimentary basin fill during diagenesis. As a first step, we construct numerical simulations in 3D in which randomly generated heterogeneous and polydisperse spheres are placed in volumes and which are permitted to overlap with one another, designed to represent the random growth and interaction of bubbles in a liquid volume. We use these simulated geometries to show that statistical predictions of the inter-bubble lengthscales and evolving bubble surface area or cluster densities can be made based on fundamental percolation theory. As a second step, we take a range of well constrained random heterogeneous rock samples including sandstones, andesites, synthetic partially sintered glass bead samples, and intact glass samples and subject them to a variety of stress loading conditions at a range of temperatures until failure. We record in real time the evolution of the number of acoustic events that precede failure and show that in all scenarios, the acoustic event rate accelerates toward failure, consistent with previous findings. Applying tools designed to forecast the failure time based on these precursory signals, we constrain the absolute error on the forecast time. We find that for all sample types, the error associated with an accurate forecast of failure scales non-linearly with the lengthscale between the pore clusters in the material. Moreover, using a simple micromechanical model for the deformation of porous elastic bodies, we show that the ratio between the equilibrium sub-critical crack length emanating from the pore clusters relative to the inter-pore lengthscale, provides a scaling for the error on forecast accuracy. Thus for the first time we provide a potential quantitative correction for

  7. The Use of Operational Short and Long Lead-time Hydrologic Forecasts by Water Resources Decision Makers in the Ohio River Valley

    Science.gov (United States)

    Adams, T. E.

    2012-12-01

    The need for hydroclimatic forecasts for water resources systems operations is significant and is clearly growing. Hydroclimatic forecasts consist of two components: first, forecasts of hydrometeorological forcings used to drive hydrologic models and, second, the resulting streamflow and stage forecasts or derivative quantities, such as reservoir inflow volumes or time above (or below) some threshold value. These forecast range from hourly to annual lead-times and include both deterministic and probabilistic formats. In the Ohio River Valley, forecasts are made available by the NOAA/NWS Ohio River Forecast Center to decision makers. These include the general public, local and state emergency managers and other officials, federal agencies, utilities, the navigation industry, and agricultural sector, and others. Hydrologic forecasts are utilized by end-users for widely varying purposes including flood warning and mitigation, reservoir management, and decision making for construction projects, to name a few. This paper will illustrate the range of NWS hydrologic streamflow and stage products that are made publicly available and how some of the forecasts are used during drought or low-flow periods and during episodes of flooding. The methodologies used to generate hydroclimatic forecasts and the complexities found in large-scale operational systems and their impact on forecast robustness will also be discussed.

  8. An Analytical Framework for Flood Water Conservation Considering Forecast Uncertainty and Acceptable Risk

    Science.gov (United States)

    Ding, W.; Zhang, C.

    2015-12-01

    Reservoir water levels are usually not allowed to exceed the flood limited water level (FLWL) during flood season, which neglects the meteorological and real-time forecast information and leads to the great waste of water resources. With the development of weather forecasting, hydrologic modeling, and hydro-climatic teleconnection, the streamflow forecast precision have improved a lot, which provides the technical support for the flood water utilization. This paper addresses how much flood water can be conserved for use after the flood season through the operation of reservoir based on uncertain forecast information by taking into account the residual flood control capacity (the difference between flood conveyance capacity and the expected inflow in a lead time). A two-stage model for dynamic control of the flood limited water level (the maximum allowed water level during the flood season, DC-FLWL) is established considering forecast uncertainty and acceptable flood risk. It is found that DC-FLWL is applicable when the reservoir inflow ranges from small to medium levels of the historical records, while both forecast uncertainty and acceptable risk in the downstream affect the feasible space of DC-FLWL. As forecast uncertainty increases (under a given risk level) or as acceptable risk level decreases (under a given forecast uncertainty level), the minimum required safety margin for flood control increases, and the chance for DC-FLWL decreases. The derived hedging rules from the modeling framework illustrate either the dominant role of water conservation or flood control or the tradeoff between the two objectives under different levels of forecast uncertainty and acceptable risk. These rules may provide useful guidelines for conserving water from flood, especially in the area with heavy water stress.

  9. Daily value-at-risk modeling and forecast evaluation: The realized volatility approach

    Directory of Open Access Journals (Sweden)

    Zhen Yao Wong

    2016-09-01

    Full Text Available One of the main applications of conditional volatility modeling and forecasting of financial assets is the value-at-risk (VaR estimation that is used by financial institutions for reporting the daily capital in risk. It remains a question on whether realized volatility (RV models that incorporate the use of intraday data produce better VaR forecasts compared to methodologies that are based solely on daily returns. This study provides extensive comparison of out-of-sample volatility and VaR forecast performance on three equity market indices: S&P500, FTSE100, and DAX30 using 13 risk models that consist of 5 GARCH specifications, 4 ARFIMAX specifications and 4 HARX specifications. The out-of-sample volatility forecasts are evaluated by various loss functions and simple scoring procedures in order to identity the model that produces the overall best volatility forecasts. For VaR forecasts, the models are evaluated using a two-stage backtesting procedure where the models undergo unconditional and conditional coverage tests to eliminate underperforming models and the qualified models are then evaluated using the quadratic probability score (QPS function that is computed based on various VaR loss functions. The results showed that RV models outperform GARCH models for volatility forecasts, but a simple EGARCH model outperforms the rest models for most of the VaR forecasts. The results also indicated that capturing the asymmetric behavior of volatility dynamics is essential for accurate volatility and VaR forecasts. The findings of this study provide useful information for market risk regulation, financial risk management and further investigations such as extension to derivative markets and options pricing.

  10. Modeling and forecasting of wind power generation - Regime-switching approaches

    DEFF Research Database (Denmark)

    Trombe, Pierre-Julien

    of more renewable energy into power systems since these systems are subjected to maintain a strict balance between electricity consumption and production, at any time. For this purpose, wind power forecasts offer an essential support to power system operators. In particular, there is a growing demand...... for improved forecasts over very short lead times, from a few minutes up to a few hours, because these forecasts, when generated with traditional approaches, are characterized by large uncertainty. In this thesis, this issue is considered from a statistical perspective, with time series models. The primary...... of high and low variability. They also yield substantial gains in probabilistic forecast accuracy for lead times of a few minutes. However, these models only integrate historical and local measurements of wind power and thus have a limited ability for notifying regime changes for larger lead times...

  11. Titanic Weather Forecasting

    Science.gov (United States)

    2004-04-01

    . ESO PR Photo 08c/04 ESO PR Photo 08c/04 Titan Surface Projections [Preview - JPEG: 601 x 400 pix - 64k] [Normal - JPEG: 1201 x 800 pix - 544k] Caption: ESO PR Photo 08c/04 : Titan images obtained with NACO on November 26th, 2002. Left: Titan's surface projection on the trailing hemisphere as observed at 1.3 μm, revealing a complex brightness structure thanks to the high image contrast of about 40%. Right: a new, possibly meteorological, phenomenon observed at 2.12 μm in Titan's atmosphere, in the form of a bright feature revolving around the South Pole. A team of French astronomers [2] have recently used the NACO state-of-the-art adaptive optics system on the fourth 8.2-m VLT unit telescope, Yepun, to map the surface of Titan by means of near-infrared images and to search for changes in the dense atmosphere. These extraordinary images have a nominal resolution of 1/30th arcsec and show details of the order of 200 km on the surface of Titan. To provide the best possible views, the raw data from the instrument were subjected to deconvolution (image sharpening). Images of Titan were obtained through 9 narrow-band filters, sampling near-infrared wavelengths with large variations in methane opacity. This permits sounding of different altitudes ranging from the stratosphere to the surface. Titan harbours at 1.24 and 2.12 μm a "southern smile", that is a north-south asymmetry, while the opposite situation is observed with filters probing higher altitudes, such as 1.64, 1.75 and 2.17 μm. A high-contrast bright feature is observed at the South Pole and is apparently caused by a phenomenon in the atmosphere, at an altitude below 140 km or so. This feature was found to change its location on the images from one side of the south polar axis to the other during the week of observations. Outlook An additional series of NACO observations of Titan is foreseen later this month (April 2004). These will be a great asset in helping optimize the return of the Cassini/Huygens mission

  12. A methodology for Electric Power Load Forecasting

    Directory of Open Access Journals (Sweden)

    Eisa Almeshaiei

    2011-06-01

    Full Text Available Electricity demand forecasting is a central and integral process for planning periodical operations and facility expansion in the electricity sector. Demand pattern is almost very complex due to the deregulation of energy markets. Therefore, finding an appropriate forecasting model for a specific electricity network is not an easy task. Although many forecasting methods were developed, none can be generalized for all demand patterns. Therefore, this paper presents a pragmatic methodology that can be used as a guide to construct Electric Power Load Forecasting models. This methodology is mainly based on decomposition and segmentation of the load time series. Several statistical analyses are involved to study the load features and forecasting precision such as moving average and probability plots of load noise. Real daily load data from Kuwaiti electric network are used as a case study. Some results are reported to guide forecasting future needs of this network.

  13. 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.

  14. Remote-sensing based approach to forecast habitat quality under climate change scenarios.

    Directory of Open Access Journals (Sweden)

    Juan M Requena-Mullor

    Full Text Available As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the

  15. Remote-sensing based approach to forecast habitat quality under climate change scenarios.

    Science.gov (United States)

    Requena-Mullor, Juan M; López, Enrique; Castro, Antonio J; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

    2017-01-01

    As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological

  16. Climate Prediction Center (CPC) NCEP-Global Forecast System (GFS) Precipitation Forecast Product

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Forecast System (GFS) forecast precipitation data at 37.5km resolution is created at the NOAA Climate Prediction Center for the purpose of near real-time...

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

    Science.gov (United States)

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

    2016-12-01

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

  18. 24-Hour Forecast of Air Temperatures from the National Weather Service's National Digital Forecast Database (NDFD)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Digital Forecast Database (NDFD) contains a seamless mosaic of the National Weather Service's (NWS) digital forecasts of air temperature. In...

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

    Science.gov (United States)

    Canestrelli, A.; Di Donato, M.

    2016-02-01

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

  20. Novel methodology for pharmaceutical expenditure forecast

    OpenAIRE

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

    2014-01-01

    Background and objective: The value appreciation of new drugs across countries today features a disruption that is making the historical data that are used for forecasting pharmaceutical expenditure poorly reliable. Forecasting methods rarely addressed uncertainty. The objective of this project was to propose a methodology to perform pharmaceutical expenditure forecasting that integrates expected policy changes and uncertainty (developed for the European Commission as the ‘EU Pharmaceutical e...

  1. Optimal forecasting model selection and data characteristics

    OpenAIRE

    Fildes, Robert; Madden, Gary; Tan, Joachim

    2007-01-01

    Selection protocols such as Box–Jenkins, variance analysis, method switching and rules-based forecasting measure data characteristics and incorporate them in models to generate best forecasts. These protocol selection methods are judgemental in application and often select a single (aggregate) model to forecast a collection of series. An alternative is to apply individually selected models for to series. A multinomial logit (MNL) approach is developed and tested on Information and communicati...

  2. Forecasting with Excel: Suggestions for Managers

    Directory of Open Access Journals (Sweden)

    Scott Nadler

    2007-05-01

    Full Text Available This article provides readers and more especially business managers with an overview of moving average, exponential smoothing, trend analysis, and linear regression approaches to forecasting. The authors then provide specific examples for each approach and the Excel formulas necessary to develop effective forecasts. This is an important contribution to the literature because it demonstrates that businesses with limited resources can develop reliable and accurate forecasts in a timely and cost effective manner using readily available software.

  3. Wheat Yield Forecasting for Punjab Province from Vegetation Index Time Series and Historic Crop Statistics

    Directory of Open Access Journals (Sweden)

    Jan Dempewolf

    2014-10-01

    Full Text Available Policy makers, government planners and agricultural market participants in Pakistan require accurate and timely information about wheat yield and production. Punjab Province is by far the most important wheat producing region in the country. The manual collection of field data and data processing for crop forecasting by the provincial government requires significant amounts of time before official reports can be released. Several studies have shown that wheat yield can be effectively forecast using satellite remote sensing data. In this study, we developed a methodology for estimating wheat yield and area for Punjab Province from freely available Landsat and MODIS satellite imagery approximately six weeks before harvest. Wheat yield was derived by regressing reported yield values against time series of four different peak-season MODIS-derived vegetation indices. We also tested deriving wheat area from the same MODIS time series using a regression-tree approach. Among the four evaluated indices, WDRVI provided more consistent and accurate yield forecasts compared to NDVI, EVI2 and saturation-adjusted normalized difference vegetation index (SANDVI. The lowest RMSE values at the district level for forecast versus reported yield were found when using six or more years of training data. Forecast yield for the 2007/2008 to 2012/2013 growing seasons were within 0.2% and 11.5% of final reported values. Absolute deviations of wheat area and production forecasts from reported values were slightly greater compared to using the previous year's or the three- or six-year moving average values, implying that 250-m MODIS data does not provide sufficient spatial resolution for providing improved wheat area and production forecasts.

  4. Online short-term solar power forecasting

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

    2009-01-01

    . Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to two hours......This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 hours. The data used is fifteen...

  5. Forecasting effects of global warming on biodiversity

    DEFF Research Database (Denmark)

    Botkin, D.B.; Saxe, H.; Araújo, M.B.

    2007-01-01

    The demand for accurate forecasting of the effects of global warming on biodiversity is growing, but current methods for forecasting have limitations. In this article, we compare and discuss the different uses of four forecasting methods: (1) models that consider species individually, (2) niche...... and theoretical ecological results suggest that many species could be at risk from global warming, during the recent ice ages surprisingly few species became extinct. The potential resolution of this conundrum gives insights into the requirements for more accurate and reliable forecasting. Our eight suggestions...

  6. FORECASTING TOURIST ARRIVALS TO LANGKAWI ISLAND MALAYSIA

    National Research Council Canada - National Science Library

    Kamarul Ariffin MANSOR; Wan Irham ISHAK

    2015-01-01

    .... Therefore, forecasting tourist arrivals with high accuracy becomes important since it may ensure the development and the readiness of all tourism related industries such as hotels, transportation...

  7. Online Short-term Solar Power Forecasting

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

    This poster presents two approaches to online forecasting of power production from PV systems. The methods are suited for online forecasting in many applications and here they are used to predict hourly values of solar power for horizons up to 32 hours.......This poster presents two approaches to online forecasting of power production from PV systems. The methods are suited for online forecasting in many applications and here they are used to predict hourly values of solar power for horizons up to 32 hours....

  8. 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....

  9. Solar Forecasting in a Challenging Insular Context

    Directory of Open Access Journals (Sweden)

    Philippe Lauret

    2016-01-01

    Full Text Available This paper aims at assessing the accuracy of different solar forecasting methods in the case of an insular context. Two sites of La Réunion Island, Le Tampon and Saint-Pierre, are chosen to do the benchmarking exercise. Réunion Island is a tropical island with a complex orography where cloud processes are mainly governed by local dynamics. As a consequence, Réunion Island exhibits numerous micro-climates. The two aforementioned sites are quite representative of the challenging character of solar forecasting in the case of a tropical island with complex orography. Hence, although distant from only 10 km, these two sites exhibit very different sky conditions. This work focuses on day-ahead and intra-day solar forecasting. Day-ahead solar forecasts are provided by the European Center for Medium-Range Weather Forecast (ECMWF. This organization maintains and runs the Numerical Weather Prediction (NWP model named Integrated Forecast System (IFS. In this work, post-processing techniques are applied to refine the output of the IFS model for day-ahead forecasting. Statistical models like a recursive linear model or a nonlinear model such as an artificial neural network are used to produce the intra-day solar forecasts. It is shown that a combination of the IFS model and the neural network model further improves the accuracy of the forecasts.

  10. Visualization of ocean forecast in BYTHOS

    Science.gov (United States)

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

    2016-08-01

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

  11. Broadband Traffic Forecasting in the Transport Network

    Directory of Open Access Journals (Sweden)

    Valentina Radojičić

    2012-07-01

    Full Text Available This paper proposes a modification of traffic forecast model generated by residential and small business (SOHO, Small Office Home Office users. The model includes forecasted values of different relevant factors and competition on broadband market. It allows forecasting the number of users for various broadband technologies and interaction impact of long-standing technologies as well as the impact of the new technology entrant on the market. All the necessary parameters are evaluated for the Serbian broadband market. The long-term forecasted results of broadband traffic are given. The analyses and evaluations performed are important inputs for the transport network resources planning.

  12. Judgmental Forecasting of Operational Capabilities

    DEFF Research Database (Denmark)

    Hallin, Carina Antonia; Tveterås, Sigbjørn; Andersen, Torben Juul

    This paper explores a new judgmental forecasting indicator, the Employee Sensed Operational Capabilities (ESOC). The purpose of the ESOC is to establish a practical prediction tool that can provide early signals about changes in financial performance by gauging frontline employees’ sensing...... of changes in the firm’s operational capabilities. We present the first stage of the development of ESOC by applying a formative measurement approach to test the index in relation to financial performance and against an organizational commitment scale. We use distributed lag models to test whether the ESOC...

  13. Automated Aircraft Icing Forecast Technique.

    Science.gov (United States)

    1984-05-31

    an Air Weather Service detachment forecaster. Many thanks are due to Lt Col Robert G. Feddes who alerted me to this opportunity to automate and test...Safety Board, Washington, DC, Report No. NTSB-SR-81-1, 16 pp. Feddes, Robert G., 1974: A Synoptic-Scale Model for Simulating Condensed Atmospheric...AFOSR/TR-80/1279, 9pp. Hobbs, P. V., T. J. Matejka, P. H. Herzegh, J. D. Locatelli, and R. A. Houze , Jr., 1980b: The Mesoscale and Microscale

  14. Entity’s Irregular Demand Scheduling of the Wholesale Electricity Market based on the Forecast of Hourly Price Ratios

    Directory of Open Access Journals (Sweden)

    O. V. Russkov

    2015-01-01

    Full Text Available The article considers a hot issue to forecast electric power demand amounts and prices for the entities of wholesale electricity market (WEM, which are in capacity of a large user with production technology requirements prevailing over hourly energy planning ones. An electric power demand of such entities is on irregular schedule. The article analyses mathematical models, currently applied to forecast demand amounts and prices. It describes limits of time-series models and fundamental ones in case of hourly forecasting an irregular demand schedule of the electricity market entity. The features of electricity trading at WEM are carefully analysed. Factors that influence on irregularity of demand schedule of the metallurgical plant are shown. The article proposes method for the qualitative forecast of market price ratios as a tool to reduce a dependence on the accuracy of forecasting an irregular schedule of demand. It describes the differences between the offered method and the similar ones considered in research studies and scholarly works. The correlation between price ratios and relaxation in the requirements for the forecast accuracy of the electric power consumption is analysed. The efficiency function of forecast method is derived. The article puts an increased focus on description of the mathematical model based on the method of qualitative forecast. It shows main model parameters and restrictions the electricity market imposes on them. The model prototype is described as a programme module. Methods to assess an effectiveness of the proposed forecast model are examined. The positive test results of the model using JSC «Volzhsky Pipe Plant» data are given. A conclusion is drawn concerning the possibility to decrease dependence on the forecast accuracy of irregular schedule of entity’s demand at WEM. The effective trading tool has been found for the entities of irregular demand schedule at WEM. The tool application allows minimizing cost

  15. Improving Precipitation Forecast for Canadian Catchments

    Science.gov (United States)

    Jha, S. K.; Shrestha, D. L.; Walford, C.; Leong, D. N. S.; Friesenhan, E.; Campbell, D.; Rasmussen, P. F.

    2016-12-01

    In Canada, floods occur frequently along large river systems, causing devastation to lives and infrastructure. Flooding in Canada is often caused by heavy rainfall during the snowmelt period. The flood forecast centres are responsible for providing advanced flood warnings and rely heavily on forecasted precipitation from numerical weather prediction (NWP) model outputs produced by Environment Canada and the National Oceanic and Atmospheric Administration. The uncertainties in NWP model output are enhanced by physiography and orographic effects over diverse landscapes, particularly in the western catchments of Canada. Therefore, post-processing of NWP model output is necessary to obtain better forecasts of rainfall amount, location, timing, and intensity; and to reliably quantify forecast uncertainty. The Rainfall Post Processing (RPP) approach (Robertson et al., 2013) has been successfully applied recently to remove rainfall forecast bias and quantify forecast uncertainty from NWP models in Australian catchments (Shrestha et al., 2015). In principle, the RPP method can be applied to other regions (e.g. cold regions) but has not been tested yet. In this study we will evaluate the performance of the RPP for improving the precipitation forecast in southern catchments in Alberta and British Columbia. The RPP relates raw quantitative precipitation forecasts and observed precipitation using a Bayesian joint probability (BJP) modeling approach, followed by the Schaake shuffle. Precipitation forecasts were analysed from two NWP models, Global Ensemble Forecasting System and Global Deterministic Prediction System. Observed data was collected from the provincial river forecast centres. The study period from Jan 2012 to Dec 2015 covered major flood events in Calgary, Alberta, and floods in coastal watersheds in British Columbia. Rain-gauge observations and forecast grid points were interpolated to obtain an aerial average precipitation in subareas to force the hydrological

  16. Improved low visibility forecasts at Amsterdam Airport

    Science.gov (United States)

    Wijngaard, J.; Vogelezang, D.; Maat, N.; van Bruggen, H.

    2009-09-01

    Accurate, reliable and unambiguous information concerning the actual and expected (low) visibility conditions at Amsterdam Airport Schiphol is very important for the available operational flow capacity. Therefore visibility forecast errors can have a negative impact on safety and operational expenses. KNMI has performed an update of the visibility forecast system in close collaboration with the main users of the forecasts (Air Traffic Control, the airport authorities and KLM airlines). This automatic forecasting system consists of a Numerical Weather Prediction Model (Hirlam) with a statistical post processing module on top of it. Output of both components is supplied to a human forecaster who issues a special probabilistic forecast bulletin. This bulletin is tailored to the specific requirements of the airport community. The improvements made to the forecast system are twofold: 1) In addition to the Meteorological Optical Range (MOR) values, RVR (Runway Visual Range) is forecasted. Since RVR depends on both MOR and the local Background Luminance, a (deterministic) statistical forecast for the latter has been developed. 2) Another improvement was achieved by calculating joint probabilities for specific combinations of visibility and cloud base height for thresholds which have direct impact on the flow capacity at the airport. The development of this new visibility forecast will be presented briefly. Also a few verification results will be shown to demonstrate the improvements made. Finally, the importance of explaining the user the use of the forecast information, in relation to their decision making process, will be discussed. For that reason, a simple guideline model to make a cost-optimal choice will be introduced.

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

    Science.gov (United States)

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

    2015-12-01

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

  18. Does a more skilful meteorological input lead to a more skilful flood forecast at seasonal timescales?

    Science.gov (United States)

    Neumann, Jessica; Arnal, Louise; Magnusson, Linus; Cloke, Hannah

    2017-04-01

    Seasonal river flow forecasts are important for many aspects of the water sector including flood forecasting, water supply, hydropower generation and navigation. In addition to short term predictions, seasonal forecasts have the potential to realise higher benefits through more optimal and consistent decisions. Their operational use however, remains a challenge due to uncertainties posed by the initial hydrologic conditions (e.g. soil moisture, groundwater levels) and seasonal climate forcings (mainly forecasts of precipitation and temperature), leading to a decrease in skill with increasing lead times. Here we present a stakeholder-led case study for the Thames catchment (UK), currently being undertaken as part of the H2020 IMPREX project. The winter of 2013-14 was the wettest on record in the UK; driven by 12 major Atlantic depressions, the Thames catchment was subject to compound (concurrent) flooding from fluvial and groundwater sources. Focusing on the 2013-14 floods, this study aims to see whether increased skill in meteorological input translates through to more accurate forecasting of compound flood events at seasonal timescales in the Thames catchment. An earlier analysis of the ECMWF System 4 (S4) seasonal meteorological forecasts revealed that it did not skilfully forecast the extreme event of winter 2013-14. This motivated the implementation of an atmospheric experiment by the ECMWF to force the S4 to more accurately represent the low-pressure weather conditions prevailing in winter 2013-14 [1]. Here, we used both the standard and the "improved" S4 seasonal meteorological forecasts to force the EFAS (European Flood Awareness System) LISFLOOD hydrological model. Both hydrological forecasts were started on the 1st of November 2013 and run for 4 months of lead time to capture the peak of the 2013-14 flood event. Comparing the seasonal hydrological forecasts produced with both meteorological forcing data will enable us to assess how the improved meteorology

  19. Evaluation of official tropical cyclone track forecast over north Indian ...

    Indian Academy of Sciences (India)

    itoring forecast improvements resulting from new algorithms, techniques and observing systems;. • Evaluation of ... available forecast techniques, perhaps including stratification into different synoptic, latitudinal, or seasonal ... mentioned track forecast error measures represents an important factor in the overall decision pro-.

  20. Forecasting Hurricane Tracks Using a Complex Adaptive System

    National Research Council Canada - National Science Library

    Lear, Matthew R

    2005-01-01

    Forecast hurricane tracks using a multi-model ensemble that consists of linearly combining the individual model forecasts have greatly reduced the average forecast errors when compared to individual...

  1. A Complex Adaptive System Approach to Forecasting Hurricane Tracks

    National Research Council Canada - National Science Library

    Lear, Matthew R

    2005-01-01

    Forecast hurricane tracks using a multi-model ensemble that consists of linearly combining the individual model forecasts have greatly reduced the average forecast errors when compared to individual...

  2. Crop Insurance Inaccurate FCIC Price Forecasts Increase Program Costs

    National Research Council Canada - National Science Library

    1991-01-01

    ...) how FCIC can improve its forecast accuracy. We found that FCIC's corn, wheat, and soybeans price forecasts exhibit large bias errors that exceed those of other available alternative forecasts and that FCIC would have spent...

  3. Global Ensemble Forecast System (GEFS) [2.5 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  4. On the skill of seasonal sea surface temperature forecasts in the California Current System and its connection to ENSO variability

    Science.gov (United States)

    Jacox, Michael G.; Alexander, Michael A.; Stock, Charles A.; Hervieux, Gaëlle

    2017-03-01

    The California Current System (CCS) is a biologically productive Eastern Boundary Upwelling System that experiences considerable environmental variability on seasonal and interannual timescales. Given that this variability drives changes in ecologically and economically important living marine resources, predictive skill for regional oceanographic conditions is highly desirable. Here, we assess the skill of seasonal sea surface temperature (SST) forecasts in the CCS using output from Global Climate Forecast Systems in the North American Multi-Model Ensemble (NMME), and describe mechanisms that underlie SST predictability. A simple persistence forecast provides considerable skill for lead times up to 4 months, while skill above persistence is mostly confined to forecasts of late winter/spring and derives primarily from predictable evolution of ENSO-related variability. Specifically, anomalously weak (strong) equatorward winds are skillfully forecast during El Niño (La Niña) events, and drive negative (positive) upwelling anomalies and consequently warm (cold) temperature anomalies. This mechanism prevails during moderate to strong ENSO events, while years of ENSO-neutral conditions are not associated with significant forecast skill in the wind or significant skill above persistence in SST. We find also a strong latitudinal gradient in predictability within the CCS; SST forecast skill is highest off the Washington/Oregon coast and lowest off southern California, consistent with variable wind forcing being the dominant driver of SST predictability. These findings have direct implications for regional downscaling of seasonal forecasts and for short-term management of living marine resources.

  5. Approximate *-derivations and approximate quadratic *-derivations on C*-algebras

    Directory of Open Access Journals (Sweden)

    Park Choonkil

    2011-01-01

    Full Text Available Abstract In this paper, we prove the stability of *-derivations and of quadratic *-derivations on Banach *-algebras. We moreover prove the superstability of *-derivations and of quadratic *-derivations on C*-algebras. 2000 Mathematics Subject Classification: 39B52; 47B47; 46L05; 39B72.

  6. New Methodology of ENSO Forecast

    Science.gov (United States)

    Feigin, A. M.; Gavrilov, A.; Mukhin, D.; Loskutov, E.; Seleznev, A.

    2016-12-01

    We describe methodology of ENSO forecast based on data-driven construction of evolution operator of underlying climate sub-system. The methodology is composed of two key algorithms: (i) space-distributed data preparation aiming to reduce data dimensionality with minimal loss of information about system's dynamics, and (ii) construction of operator that reproduces evolution of the system in reduced data space. The first algorithm combines several known data preprocessing techniques: decomposition via empirical orthogonal function basis, its spatiotemporal generalization as well as singular value decomposition techniques. The second algorithm supposes construction of evolution operator in the form of random dynamical system realized as nonlinear random mapping; the last is parameterized by artificial neural networks. General Bayesian approach is applied for mutual searching optimal parameters of both algorithms: optimal dimensionality of reduced data space and optimal complexity of the evolution operator. Abilities of suggested methodology will be demonstrated via reproduction and forecast of different ENSO related indexes including comparison of prediction skill of new methodology with power of other existing techniques. This research was supported by the Government of the Russian Federation (Agreement No.14.Z50.31.0033 with the Institute of Applied Physics RAS).

  7. MSSM Forecast for the LHC

    CERN Document Server

    Cabrera, Maria Eugenia; de Austri, Roberto Ruiz

    2009-01-01

    We perform a forecast of the MSSM with universal soft terms (CMSSM) for the LHC, based on an improved Bayesian analysis. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises from the Bayesian analysis itself when the experimental value of $M_Z$ is considered. This allows to scan the whole parameter space, allowing arbitrarily large soft terms. Still the low-energy region is statistically favoured (even before including dark matter or g-2 constraints). Contrary to other studies, the results are almost unaffected by changing the upper limits taken for the soft terms. The results are also remarkable stable when using flat or logarithmic priors, a fact that arises from the larger statistical weight of the low-energy region in both cases. Then we incorporate all the important experimental constrains to the analysis, obtaining a map of the probability density of the MSSM parameter space, i.e. the forecast of the MSSM. Since not all the experimental i...

  8. Phantosmia as a meteorological forecaster

    Science.gov (United States)

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

    2013-09-01

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

  9. The in vitro effects of Xancor, a synthetic astaxanthine derivative, on hemostatic biomarkers in aspirin-naïve and aspirin-treated subjects with multiple risk factors for vascular disease.

    Science.gov (United States)

    Serebruany, Victor; Malinin, Alex; Goodin, Thomas; Pashkow, Fredric

    2010-01-01

    Astaxanthine is a polar carotenoid metabolite derived from a proprietary prodrug, Xancor, which aligns parallel with the membrane phospholipids exhibiting potent antioxidant, anti-inflammatory, and cell protective properties, although the precise mechanism of action is unknown. This prodrug is currently under development for hepatic, neurologic, and vascular disease indications. Considering established links between heart disease and stroke with platelets, coagulation cascade, and fibrinolysis, the aim of the study was to assess the effect of asthaxantine on human biomarkers of hemostasis. The rationale was to test a hypothesis that the drug may diminish activation of hemostasis, making it a potentially attractive addition to treat patients with vascular disease. In vitro effects of whole blood preincubation with escalating concentrations of asthaxantine (0.3 microM, 1 microM, 3 microM, 10 microM, 30 microM, and 100 microM) were assessed from 12 aspirin-naïve and eight aspirin-treated volunteers with multiple risk factors for vascular disease. A total of 25 biomarkers were measured, of which 12 were related to platelet function, 10 to coagulation, and three to fibrinolysis. Platelet aggregation induced by ADP, collagen, and arachidonic acid and expression of CD31, CD41, GP IIb/IIIa, CD51/61, P-selectin, CD63, CD107a, CD151+CD14, and CD154 were not affected. Coagulation indices such as aPTT, prothrombin time, thrombin time, fibrinogen, antithrombin III (antigen and activity), Protein C, Protein S (free and activity), and von Willebrand factor remained unchanged after incubation with astaxanthine. Fibrinolytic activity biomarkers such as plasminogen, D-dimer, and FDP were also not affected after in vitro pretreatment of blood samples with astaxanthine. In the projected subclinical (less than 1 microM), therapeutic (3 microM to 30 microM), and supratherapeutic concentration (100 microM), astaxanthine in vitro does not affect platelet, coagulation, or fibrinolytic

  10. Tourist Arrivals to Sabah by Using Fuzzy Forecasting

    Directory of Open Access Journals (Sweden)

    Tarmudi Zamali

    2014-01-01

    Full Text Available The aim of this paper is to investigate the existing tourist trend arrival in Sabah based on fuzzy approach. It focuses on the latest 12 years (2002 – 2013 visitors arrival based on their nationality for forecasting purposes. Based on Sabah Tourism Board’s data, the tourist arrival continue to grow annually but with an inconsistent number of arrival. This can be seen from the trend of tourist arrival from 2011 to 2012. There is an increase in the number of arrival but only at 1.1 % compared to the other years which are in the rank of 10 – 18% increase in number of arrival per year. Therefore, the purpose of this study is to predict the number of tourist arrival to Sabah. The study employs the modification of Fuzzy Delphi Method (FDM and utilizes the flexibility of triangular fuzzy numbers (TFNs as well as fuzzy averaging to deal with the yearly inconsistency numbers of visitor’s arrival. Then, the trio levels of alpha (α-cut was used via linguistic variables to assess the confidence of decision made and to overcome the uncertainty of the input data sets. The analysis was carried out using fully data sets obtained from the official website of Sabah tourism board. Results show that our proposed forecasting approach offers a new dimension technique as compared to the traditional statistical method. It also derived more confident decision and precision forecast for Sabah tourism authority planning purposes.

  11. Multifractality and value-at-risk forecasting of exchange rates

    Science.gov (United States)

    Batten, Jonathan A.; Kinateder, Harald; Wagner, Niklas

    2014-05-01

    This paper addresses market risk prediction for high frequency foreign exchange rates under nonlinear risk scaling behaviour. We use a modified version of the multifractal model of asset returns (MMAR) where trading time is represented by the series of volume ticks. Our dataset consists of 138,418 5-min round-the-clock observations of EUR/USD spot quotes and trading ticks during the period January 5, 2006 to December 31, 2007. Considering fat-tails, long-range dependence as well as scale inconsistency with the MMAR, we derive out-of-sample value-at-risk (VaR) forecasts and compare our approach to historical simulation as well as a benchmark GARCH(1,1) location-scale VaR model. Our findings underline that the multifractal properties in EUR/USD returns in fact have notable risk management implications. The MMAR approach is a parsimonious model which produces admissible VaR forecasts at the 12-h forecast horizon. For the daily horizon, the MMAR outperforms both alternatives based on conditional as well as unconditional coverage statistics.

  12. Solar Energetic Particle Forecasting Algorithms and Associated False Alarms

    Science.gov (United States)

    Swalwell, B.; Dalla, S.; Walsh, R. W.

    2017-11-01

    Solar energetic particle (SEP) events are known to occur following solar flares and coronal mass ejections (CMEs). However, some high-energy solar events do not result in SEPs being detected at Earth, and it is these types of event which may be termed "false alarms". We define two simple SEP forecasting algorithms based upon the occurrence of a magnetically well-connected CME with a speed in excess of 1500 km s^{-1} (a "fast" CME) or a well-connected X-class flare and analyse them with respect to historical datasets. We compare the parameters of those solar events which produced an enhancement of {>} 40 MeV protons at Earth (an "SEP event") and the parameters of false alarms. We find that an SEP forecasting algorithm based solely upon the occurrence of a well-connected fast CME produces fewer false alarms (28.8%) than an algorithm which is based solely upon a well-connected X-class flare (50.6%). Both algorithms fail to forecast a relatively high percentage of SEP events (53.2% and 50.6%, respectively). Our analysis of the historical datasets shows that false-alarm X-class flares were either not associated with any CME, or were associated with a CME slower than 500 km s^{-1}; false-alarm fast CMEs tended to be associated with flare classes lower than M3. A better approach to forecasting would be an algorithm which takes as its base the occurrence of both CMEs and flares. We define a new forecasting algorithm which uses a combination of CME and flare parameters, and we show that the false-alarm ratio is similar to that for the algorithm based upon fast CMEs (29.6%), but the percentage of SEP events not forecast is reduced to 32.4%. Lists of the solar events which gave rise to {>} 40 MeV protons and the false alarms have been derived and are made available to aid further study.

  13. Verification of a probabilistic flood forecasting system for an Alpine Region of northern Italy

    Science.gov (United States)

    Laiolo, P.; Gabellani, S.; Rebora, N.; Rudari, R.; Ferraris, L.; Ratto, S.; Stevenin, H.

    2012-04-01

    Probabilistic hydrometeorological forecasting chains are increasingly becoming an operational tool used by civil protection centres for issuing flood alerts. One of the most important requests of decision makers is to have reliable systems, for this reason an accurate verification of their predictive performances become essential. The aim of this work is to validate a probabilistic flood forecasting system: Flood-PROOFS. The system works in real time, since 2008, in an alpine Region of northern Italy, Valle d'Aosta. It is used by the Civil Protection regional service to issue warnings and by the local water company to protect its facilities. Flood-PROOFS uses as input Quantitative Precipitation Forecast (QPF) derived from the Italian limited area model meteorological forecast (COSMO-I7) and forecasts issued by regional expert meteorologists. Furthermore the system manages and uses both real time meteorological and satellite data and real time data on the maneuvers performed by the water company on dams and river devices. The main outputs produced by the computational chain are deterministic and probabilistic discharge forecasts in different cross sections of the considered river network. The validation of the flood prediction system has been conducted on a 25 months period considering different statistical methods such as Brier score, Rank histograms and verification scores. The results highlight good performances of the system as support system for emitting warnings but there is a lack of statistics especially for huge discharge events.

  14. Vesicular stomatitis forecasting based on Google Trends

    Science.gov (United States)

    Lu, Yi; Zhou, GuangYa; Chen, Qin

    2018-01-01

    Background Vesicular stomatitis (VS) is an important viral disease of livestock. The main feature of VS is irregular blisters that occur on the lips, tongue, oral mucosa, hoof crown and nipple. Humans can also be infected with vesicular stomatitis and develop meningitis. This study analyses 2014 American VS outbreaks in order to accurately predict vesicular stomatitis outbreak trends. Methods American VS outbreaks data were collected from OIE. The data for VS keywords were obtained by inputting 24 disease-related keywords into Google Trends. After calculating the Pearson and Spearman correlation coefficients, it was found that there was a relationship between outbreaks and keywords derived from Google Trends. Finally, the predicted model was constructed based on qualitative classification and quantitative regression. Results For the regression model, the Pearson correlation coefficients between the predicted outbreaks and actual outbreaks are 0.953 and 0.948, respectively. For the qualitative classification model, we constructed five classification predictive models and chose the best classification predictive model as the result. The results showed, SN (sensitivity), SP (specificity) and ACC (prediction accuracy) values of the best classification predictive model are 78.52%,72.5% and 77.14%, respectively. Conclusion This study applied Google search data to construct a qualitative classification model and a quantitative regression model. The results show that the method is effective and that these two models obtain more accurate forecast. PMID:29385198

  15. 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)

  16. Forecasting the demand for new telecommunication services

    DEFF Research Database (Denmark)

    Skouby, Knud Erik; Veiro, Bjørn

    1991-01-01

    A forecasting method that is applicable for new services, where little historical data have been recorded, is proposed. The method uses estimators based on economical, demographic and traffic data. Compared to traditional forecasting procedures that are built upon a solid historical record of dat...

  17. Toward a Marine Ecological Forecasting System

    Science.gov (United States)

    2010-06-01

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

  18. Forecasting Workload for Defense Logistics Agency Distribution

    Science.gov (United States)

    2014-12-01

    forecast results (Syntetos, Boylan, & Disney , 2009). The inevitable errors in mathematical models can be ameliorated by decisions managers make. The...www.dtic.mil/dtic/tr/fulltext/u2/a211935.pdf. Syntetos, A. A., Boylan, J. E., & Disney , S. M. (2009). Forecasting for inventory planning: A 50-year review. The

  19. School Science Inspired by Improving Weather Forecasts

    Science.gov (United States)

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

    2014-01-01

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

  20. Quantifying forecast quality of IT business value

    NARCIS (Netherlands)

    Eveleens, J.L.; van der Pas, M.; Verhoef, C.

    2012-01-01

    This article discusses how to quantify the forecasting quality of IT business value. We address a common economic indicator often used to determine the business value of project proposals, the Net Present Value (NPV). To quantify the forecasting quality of IT business value, we develop a generalized

  1. Fuzzy time series forecasting of wheat production

    OpenAIRE

    Narendra Kumar; Sachin Ahuja; Shashank Bhardwaj; Vipin Kumar

    2010-01-01

    The present study provides a foundation for the development and application of fuzzy time series model for short term agricultural production forecasting. The present study can provide an advantageous basis to Farm administration for better post harvest management and thelocal industries in planning for their raw material requirement management. The fuzzy time series forecasting can be optimally utilized in agri-business management.

  2. A Delphi Forecast of Technology in Education.

    Science.gov (United States)

    Robinson, Burke E.

    The forecast reported here surveys expected utilization levels, organizational structures, and values concerning technology in education in 1990. The focus is upon educational technology and forecasting methodology; televised instruction, computer-assisted instruction (CAI), and information services are considered. The methodology employed…

  3. Econometric Models for Forecasting of Macroeconomic Indices

    Science.gov (United States)

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

    2016-01-01

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

  4. Application of probabilistic precipitation forecasts from a ...

    African Journals Online (AJOL)

    By comparing this probabilistic rainfall forecast with the expected Flash Flood Guidance (FFG) of each basin, an outlook of potential flash flooding is provided. The procedure is applied to a real flash flood event and the ensemble-based rainfall forecasts are verified against rainfall estimated by the SAFFG system.

  5. Some Initiatives in a Business Forecasting Course

    Science.gov (United States)

    Chu, Singfat

    2007-01-01

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

  6. On the Economic Evaluation of Volatility Forecasts

    DEFF Research Database (Denmark)

    Voev, Valeri

    We analyze the applicability of economic criteria for volatility forecast evaluation based on unconditional measures of portfolio performance. The main theoretical finding is that such unconditional measures generally fail to rank conditional forecasts correctly due to the presence of a bias term...... data is likely to be understated if unconditional criteria are used....

  7. Why preferring parametric forecasting to nonparametric methods?

    Science.gov (United States)

    Jabot, Franck

    2015-05-07

    A recent series of papers by Charles T. Perretti and collaborators have shown that nonparametric forecasting methods can outperform parametric methods in noisy nonlinear systems. Such a situation can arise because of two main reasons: the instability of parametric inference procedures in chaotic systems which can lead to biased parameter estimates, and the discrepancy between the real system dynamics and the modeled one, a problem that Perretti and collaborators call "the true model myth". Should ecologists go on using the demanding parametric machinery when trying to forecast the dynamics of complex ecosystems? Or should they rely on the elegant nonparametric approach that appears so promising? It will be here argued that ecological forecasting based on parametric models presents two key comparative advantages over nonparametric approaches. First, the likelihood of parametric forecasting failure can be diagnosed thanks to simple Bayesian model checking procedures. Second, when parametric forecasting is diagnosed to be reliable, forecasting uncertainty can be estimated on virtual data generated with the fitted to data parametric model. In contrast, nonparametric techniques provide forecasts with unknown reliability. This argumentation is illustrated with the simple theta-logistic model that was previously used by Perretti and collaborators to make their point. It should convince ecologists to stick to standard parametric approaches, until methods have been developed to assess the reliability of nonparametric forecasting. Copyright © 2015 Elsevier Ltd. All rights reserved.

  8. Comparison of Agricultural Forecasts with Actual Data

    Directory of Open Access Journals (Sweden)

    Y.A. Alseleem

    2001-01-01

    Full Text Available So far, little has been said regarding the accuracy of forecasting given by the Ministry of Agriculture and Water (MAW. Saudi Arabia. Measures of accuracy are quite useful in comparing several methods of sampling or analysis. A comparison of forecasts with actual data gives us a measure of accuracy. In fact, a current evaluation of the accuracy of crop forecasts appears useful since government agencies, agribusiness firms, and farmers make decisions involving millions of riyals annually on the basis of the forecast, and deficiencies in the forecasts may cause undesirable effects on plans and resource allocation. The present research examines the accuracy of 255 MAW crop area and production forecasts for wheat, barley, tomato, watermelons,  palm dates, grapes, chicken, sheep, and camel for the period 1400-1416 H (i.e. 1979-1995G. The study tested the difference between actual and forecast estimates. The results of this study provide useful information about decision making in crop (animal forecasting procedures to meet users requirements.

  9. Managing Product Returns: The Role of Forecasting

    NARCIS (Netherlands)

    B. Toktay; E.A. van der Laan (Erwin); M.P. de Brito (Marisa)

    2003-01-01

    textabstractIn this article, we discuss ways of actively influencing product returns and we review data-driven methods for forecasting return flows that exploit the fact that future returns are a function of past sales. In particular we assess the value of return forecasting at an operational level,

  10. Data Assimilation and Air Quality Forecasting

    NARCIS (Netherlands)

    Eskes, H.; Timmermans, R.; Curier, L.; Ruyter de Wildt, M. de; Segers, A.; Sauter, F.; Schaap, M.

    2014-01-01

    Lotos-Euros is a chemistry transportmodel developed in the Netherlands, and is used for air quality assessments and forecasts. Operational air quality forecasts for the Netherlands concerning ozone and PM10 are made available on the RIVM webpage (http://www.lml.rivm.nl/verw.html) and are used to

  11. Seasonal fire danger forecasts for the USA

    Science.gov (United States)

    J. Roads; F. Fujioka; S. Chen; R. Burgan

    2005-01-01

    The Scripps Experimental Climate Prediction Center has been making experimental, near-real-time, weekly to seasonal fire danger forecasts for the past 5 years. US fire danger forecasts and validations are based on standard indices from the National Fire Danger Rating System (DFDRS), which include the ignition component (IC), energy release component (ER), burning...

  12. Ensemble forecasts of road surface temperatures

    Science.gov (United States)

    Sokol, Zbyněk; Bližňák, Vojtěch; Sedlák, Pavel; Zacharov, Petr; Pešice, Petr; Škuthan, Miroslav

    2017-05-01

    This paper describes a new ensemble technique for road surface temperature (RST) forecasting using an energy balance and heat conduction model. Compared to currently used deterministic forecasts, the proposed technique allows the estimation of forecast uncertainty and probabilistic forecasts. The ensemble technique is applied to the METRo-CZ model and stems from error covariance analyses of the forecasted air temperature and humidity 2 m above the ground, wind speed at 10 m and total cloud cover N in octas by the numerical weather prediction (NWP) model. N is used to estimate the shortwave and longwave radiation fluxes. These variables are used to calculate the boundary conditions in the METRo-CZ model. We found that the variable N is crucial for generating the ensembles. Nevertheless, the ensemble spread is too small and underestimates the uncertainty in the RST forecast. One of the reasons is not considering errors in the rain and snow forecast by the NWP model when generating ensembles. Technical issues, such as incorrect sky view factors and the current state of road surface conditions also contribute to errors. Although the ensemble technique underestimates the uncertainty in the RST forecasts, it provides additional information to road authorities who provide winter road maintenance.

  13. Recent Advances in Energy Time Series Forecasting

    Directory of Open Access Journals (Sweden)

    Francisco Martínez-Álvarez

    2017-06-01

    Full Text Available This editorial summarizes the performance of the special issue entitled Energy Time Series Forecasting, which was published in MDPI’s Energies journal. The special issue took place in 2016 and accepted a total of 21 papers from twelve different countries. Electrical, solar, or wind energy forecasting were the most analyzed topics, introducing brand new methods with very sound results.

  14. 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.

  15. Modelling and Forecasting Multivariate Realized Volatility

    DEFF Research Database (Denmark)

    Chiriac, Roxana; Voev, Valeri

    This paper proposes a methodology for modelling time series of realized covariance matrices in order to forecast multivariate risks. The approach allows for flexible dynamic dependence patterns and guarantees positive definiteness of the resulting forecasts without imposing parameter restrictions...... that any risk-averse investor, regardless of the type of utility function, would be better-off using our model....

  16. Precipitation Ensembles from Single-Value Forecasts for Hydrological Ensemble Forecasting

    Science.gov (United States)

    Demargne, J.; Schaake, J.; Wu, L.; Welles, E.; Herr, H.; Seo, D.

    2005-05-01

    An ensemble pre-processor was developed to produce short-term precipitation ensembles using operational single-value forecasts. The methodology attempts to quantify the uncertainty in the single-value forecast and to capture the skill therein. These precipitation ensemble forecasts could be then ingested in the NOAA/National Weather Service (NWS) Ensemble Streamflow Prediction (ESP) system to produce probabilistic hydrological forecasts that reflect the uncertainty in forecast precipitation. The procedure constructs the joint distribution of forecast and observed precipitation from historical pairs of forecast and observed values. The probability distribution function of the future events that may occur given a particular single-value forecast is then the conditional distribution of observed precipitation given the forecast. To generate individual ensemble members for each lead time and each location, the historical observed values are replaced with values sampled from the conditional distribution given the single-value forecast. The replacement procedure matches the ranks of historical and rescaled values to preserve the space-time properties of observed precipitation in the ensemble traces. Currently, the ensemble pre-processor is being tested and evaluated at four NOAA/NWS River Forecast Centers (RFCs) in the U.S.A. In this contribution, we present the results thus far from the field and retrospective evaluations, and key science issues that must be addressed toward national operational implementation.

  17. Drift instabilities and chaos in forecasting and adaptive decision theory

    Science.gov (United States)

    Kusch, Melinda Golden; Ydstie, B. Erik

    1994-05-01

    Bifurcation theory shows that policy adaptation and the rational expectations hypothesis of macro-economics can be used to explain unpredictability, rapid changes in solution structure and chaos in decision problems with uncertainty. Structural errors lead to catastrophic instability and forecasts become irrelevant. Short evaluation horizon and the application of measures designed to give quick response give multiperiodicity and chaos. Finally, wrong interpretations of the context lead to global bifurcations, laminar drift (complacency) and chaotic bursting. The discrete map representing these dynamics is of interest in its own right. It is non-invertible and displays bifurcation behaviour not commonly seen in systems derived from physical considerations.

  18. Short-term residential load forecasting: Impact of calendar effects and forecast granularity

    DEFF Research Database (Denmark)

    Lusis, Peter; Khalilpour, Kaveh Rajab; Andrew, Lachlan

    2017-01-01

    Literature is rich in methodologies for “aggregated” load forecasting which has helped electricity network operators and retailers in optimal planning and scheduling. The recent increase in the uptake of distributed generation and storage systems has generated new demand for “disaggregated” load...... forecasting for a single-customer or even down at an appliance level. Access to high resolution data from smart meters has enabled the research community to assess conventional load forecasting techniques and develop new forecasting strategies suitable for demand-side disaggregated loads. This paper studies...... how calendar effects, forecasting granularity and the length of the training set affect the accuracy of a day-ahead load forecast for residential customers. Root mean square error (RMSE) and normalized RMSE were used as forecast error metrics. Regression trees, neural networks, and support vector...

  19. Forecasting Ocean Chlorophyll in the Equatorial Pacific

    Directory of Open Access Journals (Sweden)

    Cecile S. Rousseaux

    2017-07-01

    Full Text Available Using a global ocean biogeochemical model combined with a forecast of physical oceanic and atmospheric variables from the NASA Global Modeling and Assimilation Office, we assess the skill of a chlorophyll concentrations forecast in the Equatorial Pacific for the period 2012–2015 with a focus on the forecast of the onset of the 2015 El Niño event. Using a series of retrospective 9-month hindcasts, we assess the uncertainties of the forecasted chlorophyll by comparing the monthly total chlorophyll concentration from the forecast with the corresponding monthly ocean chlorophyll data from the Suomi-National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (S-NPP VIIRS satellite. The forecast was able to reproduce the phasing of the variability in chlorophyll concentration in the Equatorial Pacific, including the beginning of the 2015–2016 El Niño. The anomaly correlation coefficient (ACC was significant (p < 0.05 for forecast at 1-month (R = 0.33, 8-month (R = 0.42 and 9-month (R = 0.41 lead times. The root mean square error (RMSE increased from 0.0399 μg chl L−1 for the 1-month lead forecast to a maximum of 0.0472 μg chl L−1 for the 9-month lead forecast indicating that the forecast of the amplitude of chlorophyll concentration variability was getting worse. Forecasts with a 3-month lead time were on average the closest to the S-NPP VIIRS data (23% or 0.033 μg chl L−1 while the forecast with a 9-month lead time were the furthest (31% or 0.042 μg chl L−1. These results indicate the potential for forecasting chlorophyll concentration in this region but also highlights various deficiencies and suggestions for improvements to the current biogeochemical forecasting system. This system provides an initial basis for future applications including the effects of El Niño events on fisheries and other ocean resources given improvements identified in the analysis of these results.

  20. Do probabilistic forecasts lead to better decisions?

    Directory of Open Access Journals (Sweden)

    M. H. Ramos

    2013-06-01

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