WorldWideScience

Sample records for condition indicators forecasting

  1. Conditional Probabilistic Population Forecasting

    OpenAIRE

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

    2003-01-01

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

  2. Conditional probabilistic population forecasting

    OpenAIRE

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

    2003-01-01

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

  3. Conditional Probabilistic Population Forecasting

    OpenAIRE

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

    2004-01-01

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

  4. 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…

  5. Operational forecasting of human-biometeorological conditions

    Science.gov (United States)

    Giannaros, T. M.; Lagouvardos, K.; Kotroni, V.; Matzarakis, A.

    2018-03-01

    This paper presents the development of an operational forecasting service focusing on human-biometeorological conditions. The service is based on the coupling of numerical weather prediction models with an advanced human-biometeorological model. Human thermal perception and stress forecasts are issued on a daily basis for Greece, in both point and gridded format. A user-friendly presentation approach is adopted for communicating the forecasts to the public via the worldwide web. The development of the presented service highlights the feasibility of replacing standard meteorological parameters and/or indices used in operational weather forecasting activities for assessing the thermal environment. This is of particular significance for providing effective, human-biometeorology-oriented, warnings for both heat waves and cold outbreaks.

  6. 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

  7. Forecasting annual gross electricity demand by artificial neural networks using predicted values of socio-economic indicators and climatic conditions: Case of Turkey

    International Nuclear Information System (INIS)

    Günay, M. Erdem

    2016-01-01

    In this work, the annual gross electricity demand of Turkey was modeled by multiple linear regression and artificial neural networks as a function population, gross domestic product per capita, inflation percentage, unemployment percentage, average summer temperature and average winter temperature. Among these, the unemployment percentage and the average winter temperature were found to be insignificant to determine the demand for the years between 1975 and 2013. Next, the future values of the statistically significant variables were predicted by time series ANN models, and these were simulated in a multilayer perceptron ANN model to forecast the future annual electricity demand. The results were validated with a very high accuracy for the years that the electricity demand was known (2007–2013), and they were also superior to the official predictions (done by Ministry of Energy and Natural Resources of Turkey). The model was then used to forecast the annual gross electricity demand for the future years, and it was found that, the demand will be doubled reaching about 460 TW h in the year 2028. Finally, it was concluded that the approach applied in this work can easily be implemented for other countries to make accurate predictions for the future. - Highlights: • Electricity demand of Turkey increased from 15.6 to 246.4 TW h in 1975–2013 period. • Population, GDP per capita, inflation and average summer temperature influence demand. • Future values of descriptor variables can be predicted by time series ANN models. • ANN model simulated by the predicted values of descriptors can forecast the demand. • Demand is forecasted to be doubled reaching about 460 TW h in the year 2028.

  8. Forecasting Investment Risks in Conditions of Uncertainty

    Directory of Open Access Journals (Sweden)

    Andrenko Elena A.

    2017-04-01

    Full Text Available The article is aimed at studying the topical problem of evaluation and forecasting risks of investment activity of enterprises in conditions of uncertainty. Generalizing the researches on qualitative and quantitative methods for evaluating investment risks has helped to reveal certain shortcomings of the proposed approaches, to note in most of the publications there are no results as to any practical application, and to allocate promising directions. On the basis of the theory of fuzzy sets, a model of forecasting the expected risk has been proposed, making use of the Gauss membership function, which has certain advantages over the multi-angular membership functions. Dependences of investment risk from the parameters characterizing the investment project have been obtained. Using the formulas obtained, the total risk of investing in innovation project depending on the boundary conditions has been defined. As the researched target, index of profitability has been selected. The model provides the potential investors and developers with forecasting possible scenarios of investment process to make informed managerial decisions about the appropriateness of introduction and implementation of a project.

  9. Condition Indicators for Gearbox Condition Monitoring Systems

    Directory of Open Access Journals (Sweden)

    P. Večeř

    2005-01-01

    Full Text Available Condition monitoring systems for manual transmissions based on vibration diagnostics are widely applied in industry. The systems deal with various condition indicators, most of which are focused on a specific type of gearbox fault. Frequently used condition indicators (CIs are described in this paper. The ability of a selected condition indicator to describe the degree of gearing wear was tested using vibration signals acquired during durability testing of manual transmission with helical gears. 

  10. Forecasting Irish Inflation: A Composite Leading Indicator

    OpenAIRE

    Quinn, Terry; Mawdsley, Andrew

    1996-01-01

    This paper presents the results of research into the construction of a composite leading indicator of the Irish rate of inflation, as measured by the annual percentage change in the Consumer Price Index (CPI). It follows the work of Fagan and Fell (1994) who applied the business cycle leading indicator methodology, initially established by Mitchell and Burns (1938,1946), to construct a composite leading indicator of the Irish business cycle.

  11. Bayesian Sampling using Condition Indicators

    DEFF Research Database (Denmark)

    Faber, Michael H.; Sørensen, John Dalsgaard

    2002-01-01

    of condition indicators introduced by Benjamin and Cornell (1970) a Bayesian approach to quality control is formulated. The formulation is then extended to the case where the quality control is based on sampling of indirect information about the condition of the components, i.e. condition indicators...

  12. The use of ambient humidity conditions to improve influenza forecast.

    Directory of Open Access Journals (Sweden)

    Jeffrey Shaman

    2017-11-01

    Full Text Available Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1-4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively. These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast.

  13. The use of ambient humidity conditions to improve influenza forecast.

    Science.gov (United States)

    Shaman, Jeffrey; Kandula, Sasikiran; Yang, Wan; Karspeck, Alicia

    2017-11-01

    Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1-4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing) and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively). These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast.

  14. Two quantitative forecasting methods for macroeconomic indicators in Czech Republic

    Directory of Open Access Journals (Sweden)

    Mihaela BRATU (SIMIONESCU

    2012-03-01

    Full Text Available Econometric modelling and exponential smoothing techniques are two quantitative forecasting methods with good results in practice, but the objective of the research was to find out which of the two techniques are better for short run predictions. Therefore, for inflation, unemployment and interest rate in Czech Republic some accuracy indicators were calculated for the predictions based on these methods. Short run forecasts on a horizon of 3 months were made for December 2011-February 2012, the econometric models being updated. For Czech Republic, the exponential smoothing techniques provided more accurate forecasts than the econometric models (VAR(2 models, ARMA procedure and models with lagged variables. One explication for the better performance of smoothing techniques would be that in the chosen countries the short run predictions more influenced by the recent evolution of the indicators.

  15. Forecasting in Intelligence: Indications and Warning Methodology in Modern Practice

    Directory of Open Access Journals (Sweden)

    Marina Gennadievna Vlasova

    2015-12-01

    Full Text Available Today the national security system effectiveness seriously depends on the professional analysis of information and timely forecasts. Thus the efficient methods of forecasting in the sphere of international relations are of current importance for the modern intelligence services. The Indications and Warning Technique that was a key element of forecasting methodology in intelligence until the end of Cold War is estimated in the present article. Is this method still relevant in the contemporary world with its new international order, new security challenges and technological revolution in the data collection and processing? The main conclusion based on the overview of current researches and known intelligence practice is that indicators technique is still relevant for the early warning of national security threats but requires some adaptation to today’s issues. The most important trends in adaptation are supposed to be a creation of broadest possible spectrum of threatens scenarios as well as research of current strategic threatens and corresponding indicators. Also the appropriate software that automates the use of indications technique by the security services is very important. The author believes that the cooperation between intelligence services and academic community can increase the efficiency of the Indications Methodology and of the strategic forecasting as well.

  16. The Use of Ambient Humidity Conditions to Improve Influenza Forecast

    Science.gov (United States)

    Shaman, J. L.; Kandula, S.; Yang, W.; Karspeck, A. R.

    2017-12-01

    Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing. These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast and provide further evidence that humidity modulates rates of influenza transmission.

  17. Global Wildfire Forecasts Using Large Scale Climate Indices

    Science.gov (United States)

    Shen, Huizhong; Tao, Shu

    2016-04-01

    Using weather readings, fire early warning can provided forecast 4-6 hour in advance to minimize fire loss. The benefit would be dramatically enhanced if relatively accurate long-term projection can be also provided. Here we present a novel method for predicting global fire season severity (FSS) at least three months in advance using multiple large-scale climate indices (CIs). The predictive ability is proven effective for various geographic locations and resolution. Globally, as well as in most continents, the El Niño Southern Oscillation (ENSO) is the dominant driving force controlling interannual FSS variability, whereas other CIs also play indispensable roles. We found that a moderate El Niño event is responsible for 465 (272-658 as interquartile range) Tg carbon release and an annual increase of 29,500 (24,500-34,800) deaths from inhalation exposure to air pollutants. Southeast Asia accounts for half of the deaths. Both intercorrelation and interaction of WPs and CIs are revealed, suggesting possible climate-induced modification of fire responses to weather conditions. Our models can benefit fire management in response to climate change.

  18. Can confidence indicators forecast the probability of expansion in Croatia?

    Directory of Open Access Journals (Sweden)

    Mirjana Čižmešija

    2016-04-01

    Full Text Available The aim of this paper is to investigate how reliable are confidence indicators in forecasting the probability of expansion. We consider three Croatian Business Survey indicators: the Industrial Confidence Indicator (ICI, the Construction Confidence Indicator (BCI and the Retail Trade Confidence Indicator (RTCI. The quarterly data, used in the research, covered the periods from 1999/Q1 to 2014/Q1. Empirical analysis consists of two parts. The non-parametric Bry-Boschan algorithm is used for distinguishing periods of expansion from the period of recession in the Croatian economy. Then, various nonlinear probit models were estimated. The models differ with respect to the regressors (confidence indicators and the time lags. The positive signs of estimated parameters suggest that the probability of expansion increases with an increase in Confidence Indicators. Based on the obtained results, the conclusion is that ICI is the most powerful predictor of the probability of expansion in Croatia.

  19. Model Forecast Skill and Sensitivity to Initial Conditions in the Seasonal Sea Ice Outlook

    Science.gov (United States)

    Blanchard-Wrigglesworth, E.; Cullather, R. I.; Wang, W.; Zhang, J.; Bitz, C. M.

    2015-01-01

    We explore the skill of predictions of September Arctic sea ice extent from dynamical models participating in the Sea Ice Outlook (SIO). Forecasts submitted in August, at roughly 2 month lead times, are skillful. However, skill is lower in forecasts submitted to SIO, which began in 2008, than in hindcasts (retrospective forecasts) of the last few decades. The multimodel mean SIO predictions offer slightly higher skill than the single-model SIO predictions, but neither beats a damped persistence forecast at longer than 2 month lead times. The models are largely unsuccessful at predicting each other, indicating a large difference in model physics and/or initial conditions. Motivated by this, we perform an initial condition sensitivity experiment with four SIO models, applying a fixed -1 m perturbation to the initial sea ice thickness. The significant range of the response among the models suggests that different model physics make a significant contribution to forecast uncertainty.

  20. Aircraft route forecasting under adverse weather conditions

    Directory of Open Access Journals (Sweden)

    Thomas Hauf

    2017-04-01

    Full Text Available In this paper storm nowcasts in the terminal manoeuvring area (TMA of Hong Kong International Airport are used to forecast deviation routes through a field of storms for arriving and departing aircraft. Storms were observed and nowcast by the nowcast system SWIRLS from the Hong Kong Observatory. Storms were considered as no-go zones for aircraft and deviation routes were determined with the DIVSIM software package. Two days (21 and 22 May 2011 with 22 actual flown routes were investigated. Flights were simulated with a nowcast issued at the time an aircraft entered the TMA or departed from the airport. These flights were compared with a posteriori simulations, in which all storm fields were known and circumnavigated. Both types of simulated routes were then compared with the actual flown routes. The qualitative comparison of the various routes revealed generally good agreement. Larger differences were found in more complex situations with many active storms in the TMA. Route differences resulted primarily from air traffic control measures imposed such as holdings, slow-downs and shortcuts, causing the largest differences between the estimated and actual landing time. Route differences could be enhanced as aircraft might be forced to circumnavigate a storm ahead in a different sense. The use of route forecasts to assist controllers coordinating flights in a complex moving storm field is discussed. The study emphasises the important application of storm nowcasts in aviation meteorology.

  1. Improved forecasting with leading indicators: the principal covariate index

    NARCIS (Netherlands)

    C. Heij (Christiaan)

    2007-01-01

    textabstractWe propose a new method of leading index construction that combines the need for data compression with the objective of forecasting. This so-called principal covariate index is constructed to forecast growth rates of the Composite Coincident Index. The forecast performance is compared

  2. Seasonal streamflow forecast with machine learning and teleconnection indices in the context non-stationary climate

    Science.gov (United States)

    Haguma, D.; Leconte, R.

    2017-12-01

    Spatial and temporal water resources variability are associated with large-scale pressure and circulation anomalies known as teleconnections that influence the pattern of the atmospheric circulation. Teleconnection indices have been used successfully to forecast streamflow in short term. However, in some watersheds, classical methods cannot establish relationships between seasonal streamflow and teleconnection indices because of weak correlation. In this study, machine learning algorithms have been applied for seasonal streamflow forecast using teleconnection indices. Machine learning offers an alternative to classical methods to address the non-linear relationship between streamflow and teleconnection indices the context non-stationary climate. Two machine learning algorithms, random forest (RF) and support vector machine (SVM), with teleconnection indices associated with North American climatology, have been used to forecast inflows for one and two leading seasons for the Romaine River and Manicouagan River watersheds, located in Quebec, Canada. The indices are Pacific-North America (PNA), North Atlantic Oscillation (NAO), El Niño-Southern Oscillation (ENSO), Arctic Oscillation (AO) and Pacific Decadal Oscillation (PDO). The results showed that the machine learning algorithms have an important predictive power for seasonal streamflow for one and two leading seasons. The RF performed better for training and SVM generally have better results with high predictive capability for testing. The RF which is an ensemble method, allowed to assess the uncertainty of the forecast. The integration of teleconnection indices responds to the seasonal forecast of streamflow in the conditions of the non-stationarity the climate, although the teleconnection indices have a weak correlation with streamflow.

  3. The use of various interplanetary scintillation indices within geomagnetic forecasts

    Directory of Open Access Journals (Sweden)

    E. A. Lucek

    Full Text Available Interplanetary scintillation (IPS, the twinkling of small angular diameter radio sources, is caused by the interaction of the signal with small-scale plasma irregularities in the solar wind. The technique may be used to sense remotely the near-Earth heliosphere and observations of a sufficiently large number of sources may be used to track large-scale disturbances as they propagate from close to the Sun to the Earth. Therefore, such observations have potential for use within geomagnetic forecasts. We use daily data from the Mullard Radio Astronomy Observatory, made available through the World Data Centre, to test the success of geomagnetic forecasts based on IPS observations. The approach discussed here was based on the reduction of the information in a map to a single number or series of numbers. The advantages of an index of this nature are that it may be produced routinely and that it could ideally forecast both the occurrence and intensity of geomagnetic activity. We start from an index that has already been described in the literature, INDEX35. On the basis of visual examination of the data in a full skymap format modifications were made to the way in which the index was calculated. It was hoped that these would lead to an improvement in its forecasting ability. Here we assess the forecasting potential of the index using the value of the correlation coefficient between daily Ap and the IPS index, with IPS leading by 1 day. We also compare the forecast based on the IPS index with forecasts of Ap currently released by the Space Environment Services Center (SESC. Although we find that the maximum improvement achieved is small, and does not represent a significant advance in forecasting ability, the IPS forecasts at this phase of the solar cycle are of a similar quality to those made by SESC.

  4. Conditional Monthly Weather Resampling Procedure for Operational Seasonal Water Resources Forecasting

    Science.gov (United States)

    Beckers, J.; Weerts, A.; Tijdeman, E.; Welles, E.; McManamon, A.

    2013-12-01

    To provide reliable and accurate seasonal streamflow forecasts for water resources management several operational hydrologic agencies and hydropower companies around the world use the Extended Streamflow Prediction (ESP) procedure. The ESP in its original implementation does not accommodate for any additional information that the forecaster may have about expected deviations from climatology in the near future. Several attempts have been conducted to improve the skill of the ESP forecast, especially for areas which are affected by teleconnetions (e,g. ENSO, PDO) via selection (Hamlet and Lettenmaier, 1999) or weighting schemes (Werner et al., 2004; Wood and Lettenmaier, 2006; Najafi et al., 2012). A disadvantage of such schemes is that they lead to a reduction of the signal to noise ratio of the probabilistic forecast. To overcome this, we propose a resampling method conditional on climate indices to generate meteorological time series to be used in the ESP. The method can be used to generate a large number of meteorological ensemble members in order to improve the statistical properties of the ensemble. The effectiveness of the method was demonstrated in a real-time operational hydrologic seasonal forecasts system for the Columbia River basin operated by the Bonneville Power Administration. The forecast skill of the k-nn resampler was tested against the original ESP for three basins at the long-range seasonal time scale. The BSS and CRPSS were used to compare the results to those of the original ESP method. Positive forecast skill scores were found for the resampler method conditioned on different indices for the prediction of spring peak flows in the Dworshak and Hungry Horse basin. For the Libby Dam basin however, no improvement of skill was found. The proposed resampling method is a promising practical approach that can add skill to ESP forecasts at the seasonal time scale. Further improvement is possible by fine tuning the method and selecting the most

  5. Forecasting conditional climate-change using a hybrid approach

    Science.gov (United States)

    Esfahani, Akbar Akbari; Friedel, Michael J.

    2014-01-01

    A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.

  6. A Machine LearningFramework to Forecast Wave Conditions

    Science.gov (United States)

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

    2017-12-01

    Recently, significant effort has been undertaken to quantify and extract wave energy because it is renewable, environmental friendly, abundant, and often close to population centers. However, a major challenge is the ability to accurately and quickly predict energy production, especially across a 48-hour cycle. Accurate forecasting of wave conditions is a challenging undertaking that typically involves solving the spectral action-balance equation on a discretized grid with high spatial resolution. The nature of the computations typically demands high-performance computing infrastructure. Using a case-study site at Monterey Bay, California, a machine learning framework was trained to replicate numerically simulated wave conditions at a fraction of the typical computational cost. Specifically, the physics-based Simulating WAves Nearshore (SWAN) model, driven by measured wave conditions, nowcast ocean currents, and wind data, was used to generate training data for machine learning algorithms. The model was run between April 1st, 2013 and May 31st, 2017 generating forecasts at three-hour intervals yielding 11,078 distinct model outputs. SWAN-generated fields of 3,104 wave heights and a characteristic period could be replicated through simple matrix multiplications using the mapping matrices from machine learning algorithms. In fact, wave-height RMSEs from the machine learning algorithms (9 cm) were less than those for the SWAN model-verification exercise where those simulations were compared to buoy wave data within the model domain (>40 cm). The validated machine learning approach, which acts as an accurate surrogate for the SWAN model, can now be used to perform real-time forecasts of wave conditions for the next 48 hours using available forecasted boundary wave conditions, ocean currents, and winds. This solution has obvious applications to wave-energy generation as accurate wave conditions can be forecasted with over a three-order-of-magnitude reduction in

  7. Drought Forecasting with Vegetation Temperature Condition Index Using ARIMA Models in the Guanzhong Plain

    Directory of Open Access Journals (Sweden)

    Miao Tian

    2016-08-01

    Full Text Available This paper works on the agricultural drought forecasting in the Guanzhong Plain of China using Autoregressive Integrated Moving Average (ARIMA models based on the time series of drought monitoring results of Vegetation Temperature Condition Index (VTCI. About 90 VTCI images derived from Advanced Very High Resolution Radiometer (AVHRR data were selected to develop the ARIMA models from the erecting stage to the maturity stage of winter wheat (early March to late May in each year at a ten-day interval of the years from 2000 to 2009. We take the study area overlying on the administration map around the study area, and divide the study area into 17 parts where at least one weather station is located in each part. The pixels where the 17 weather stations are located are firstly chosen and studied for their fitting models, and then the best models for all pixels of the whole area are determined. According to the procedures for the models’ development, the selected best models for the 17 pixels are identified and the forecast is done with three steps. The forecasting results of the ARIMA models were compared with the monitoring ones. The results show that with reference to the categorized VTCI drought monitoring results, the categorized forecasting results of the ARIMA models are in good agreement with the monitoring ones. The categorized drought forecasting results of the ARIMA models are more severity in the northeast of the Plain in April 2009, which are in good agreements with the monitoring ones. The absolute errors of the AR(1 models are lower than the SARIMA models, both in the frequency distributions and in the statistic results. However, the ability of SARIMA models to detect the changes of the drought situation is better than the AR(1 models. These results indicate that the ARIMA models can better forecast the category and extent of droughts and can be applied to forecast droughts in the Plain.

  8. Selecting Social Indicators to Forecast Child Welfare Caseload

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    Raghubar D. Sharma

    2008-12-01

    identified social indicators that were statistically associated with the risk factors. After measuring the statistical association between social indictors with child welfare caseload, this study develops regression models to select and narrow down a list of social indicators with the highest predictability.

  9. Key Performance Indicators and Analysts' Earnings Forecast Accuracy: An Application of Content Analysis

    OpenAIRE

    Alireza Dorestani; Zabihollah Rezaee

    2011-01-01

    We examine the association between the extent of change in key performance indicator (KPI) disclosures and the accuracy of forecasts made by analysts. KPIs are regarded as improving both the transparency and relevancy of public financial information. The results of using linear regression models show that contrary to our prediction and the hypothesis of this paper, there is no significant association between the change in non- financial KPI disclosures and the accuracy of analysts' forecasts....

  10. Forecasting of rainfall using ocean-atmospheric indices with a fuzzy neural technique

    Science.gov (United States)

    Srivastava, Gaurav; Panda, Sudhindra N.; Mondal, Pratap; Liu, Junguo

    2010-12-01

    SummaryForecasting of rainfall is imperative for rainfed agriculture of arid and semi-arid regions of the world where agriculture consumes nearly 80% of the total water demand. Fuzzy-Ranking Algorithm (FRA) is used to identify the significant input variables for rainfall forecast. A case study is carried out to forecast monthly rainfall in India with several ocean-atmospheric predictor variables. Three different scenarios of ocean-atmospheric predictor variables are used as a set of possible input variables for rainfall forecasting model: (1) two climate indices, i.e. Southern Oscillation Index (SOI) and Pacific Decadal Oscillation Index (PDOI); (2) Sea Surface Temperature anomalies (SSTa) in the 5° × 5° grid points in Indian Ocean; and (3) both the climate indices and SSTa. To generate a set of possible input variables for these scenarios, we use climatic indices and the SSTa data with different lags between 1 and 12 months. Nonlinear relationship between identified inputs and rainfall is captured with an Artificial Neural Network (ANN) technique. A new approach based on fuzzy c-mean clustering is proposed for dividing data into representative subsets for training, testing, and validation. The results show that this proposed approach overcomes the difficulty in determining optimal numbers of clusters associated with the data division technique of self-organized map. The ANN model developed with both the climate indices and SSTa shows the best performance for the forecast of the monthly August rainfall in India. Similar approach can be applied to forecast rainfall of any period at selected climatic regions of the world where significant relationship exists between the rainfall and climate indices.

  11. A dynamic system to forecast ionospheric storm disturbances based on solar wind conditions

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    L. R. Cander

    2005-06-01

    Full Text Available For the reliable performance of technologically advanced radio communications systems under geomagnetically disturbed conditions, the forecast and modelling of the ionospheric response during storms is a high priority. The ionospheric storm forecasting models that are currently in operation have shown a high degree of reliability during quiet conditions, but they have proved inadequate during storm events. To improve their prediction accuracy, we have to take advantage of the deeper understanding in ionospheric storm dynamics that is currently available, indicating a correlation between the Interplanetary Magnetic Field (IMF disturbances and the qualitative signature of ionospheric storm disturbances at middle latitude stations. In this paper we analyse observations of the foF2 critical frequency parameter from one mid-latitude European ionospheric station (Chilton in conjunction with observations of IMF parameters (total magnitude, Bt and Bz-IMF component from the ACE spacecraft mission for eight storm events. The determination of the time delay in the ionospheric response to the interplanetary medium disturbances leads to significant results concerning the forecast of the ionospheric storms onset and their development during the first 24 h. In this way the real-time ACE observations of the solar wind parameters may be used in the development of a real-time dynamic ionospheric storm model with adequate accuracy.

  12. Performance of technical indicators in forecasting high-frequency foreign exchange rates

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    Václav Mastný

    2004-01-01

    Full Text Available This paper deals with technical analysis and its forecasting ability in the intradaily foreign exchange market. The objective of this study is to investigate whether technical indicators are able to provide prediction superior to „buy and hold“ strategy. Each indicator is tested with series of parameters in time series of different frequency (5, 15, 30, 60 min. The profitability of each indicator is examined in simple trading modell.

  13. Quantifying uncertainty in Gulf of Mexico forecasts stemming from uncertain initial conditions

    KAUST Repository

    Iskandarani, Mohamed; Le Hé naff, Matthieu; Srinivasan, Ashwanth; Knio, Omar

    2016-01-01

    Polynomial Chaos (PC) methods are used to quantify the impacts of initial conditions uncertainties on oceanic forecasts of the Gulf of Mexico circulation. Empirical Orthogonal Functions are used as initial conditions perturbations with their modal

  14. Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Petr Maca

    2016-01-01

    Full Text Available The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI and the standardized precipitation evaporation index (SPEI and were derived for the period of 1948–2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feedforward multilayer perceptron with one hidden layer of neurons.

  15. Aggregate electricity demand in South Africa: Conditional forecasts to 2030

    Energy Technology Data Exchange (ETDEWEB)

    Inglesi, Roula [Department of Economics, Faculty of Economic and Management Sciences, University of Pretoria, Main Campus, Pretoria 0002 (South Africa)

    2010-01-15

    In 2008, South Africa experienced a severe electricity crisis. Domestic and industrial electricity users had to suffer from black outs all over the country. It is argued that partially the reason was the lack of research on energy, locally. However, Eskom argues that the lack of capacity can only be solved by building new power plants. The objective of this study is to specify the variables that explain the electricity demand in South Africa and to forecast electricity demand by creating a model using the Engle-Granger methodology for co-integration and Error Correction models. By producing reliable results, this study will make a significant contribution that will improve the status quo of energy research in South Africa. The findings indicate that there is a long run relationship between electricity consumption and price as well as economic growth/income. The last few years in South Africa, price elasticity was rarely taken into account because of the low and decreasing prices in the past. The short-run dynamics of the system are affected by population growth, too After the energy crisis, Eskom, the national electricity supplier, is in search for substantial funding in order to build new power plants that will help with the envisaged lack of capacity that the company experienced. By using two scenarios for the future of growth, this study shows that the electricity demand will drop substantially due to the price policies agreed - until now - by Eskom and the National Energy Regulator South Africa (NERSA) that will affect the demand for some years. (author)

  16. Aggregate electricity demand in South Africa: Conditional forecasts to 2030

    International Nuclear Information System (INIS)

    Inglesi, Roula

    2010-01-01

    In 2008, South Africa experienced a severe electricity crisis. Domestic and industrial electricity users had to suffer from black outs all over the country. It is argued that partially the reason was the lack of research on energy, locally. However, Eskom argues that the lack of capacity can only be solved by building new power plants. The objective of this study is to specify the variables that explain the electricity demand in South Africa and to forecast electricity demand by creating a model using the Engle-Granger methodology for co-integration and Error Correction models. By producing reliable results, this study will make a significant contribution that will improve the status quo of energy research in South Africa. The findings indicate that there is a long run relationship between electricity consumption and price as well as economic growth/income. The last few years in South Africa, price elasticity was rarely taken into account because of the low and decreasing prices in the past. The short-run dynamics of the system are affected by population growth, too After the energy crisis, Eskom, the national electricity supplier, is in search for substantial funding in order to build new power plants that will help with the envisaged lack of capacity that the company experienced. By using two scenarios for the future of growth, this study shows that the electricity demand will drop substantially due to the price policies agreed - until now - by Eskom and the National Energy Regulator South Africa (NERSA) that will affect the demand for some years. (author)

  17. Skill of a global seasonal streamflow forecasting system, relative roles of initial conditions and meteorological forcing

    NARCIS (Netherlands)

    Candogan Yossef, N.; Winsemius, H.C.; Weerts, A.; Van Beek, R.; Bierkens, M.F.P.

    2013-01-01

    We investigate the relative contributions of initial conditions (ICs) and meteorological forcing (MF) to the skill of the global seasonal streamflow forecasting system FEWS-World, using the global hydrological model PCRaster Global Water Balance. Potential improvement in forecasting skill through

  18. Conditional time series forecasting with convolutional neural networks

    NARCIS (Netherlands)

    A. Borovykh (Anastasia); S.M. Bohte (Sander); C.W. Oosterlee (Cornelis)

    2017-01-01

    textabstractForecasting financial time series using past observations has been a significant topic of interest. While temporal relationships in the data exist, they are difficult to analyze and predict accurately due to the non-linear trends and noise present in the series. We propose to learn these

  19. A Condition Based Maintenance Approach to Forecasting B-1 Aircraft Parts

    Science.gov (United States)

    2017-03-23

    Air Force Institute of Technology AFIT Scholar Theses and Dissertations 3-23-2017 A Condition Based Maintenance Approach to Forecasting B-1 Aircraft...component’s life history where reliability forecasts could be stipulated based on a component’s current condition . One of the major issues their report noted...Engine Condition Monitoring System Specification. Contract Number DOT-CG-80513-A. Grand Prairie, TX. Air Force Materiel Command. (2011) Requirements For

  20. 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

  1. Forecasting energy market indices with recurrent neural networks: Case study of crude oil price fluctuations

    International Nuclear Information System (INIS)

    Wang, Jie; Wang, Jun

    2016-01-01

    In an attempt to improve the forecasting accuracy of crude oil price fluctuations, a new neural network architecture is established in this work which combines Multilayer perception and ERNN (Elman recurrent neural networks) with stochastic time effective function. ERNN is a time-varying predictive control system and is developed with the ability to keep memory of recent events in order to predict future output. The stochastic time effective function represents that the recent information has a stronger effect for the investors than the old information. With the established model the empirical research has a good performance in testing the predictive effects on four different time series indices. Compared to other models, the present model is possible to evaluate data from 1990s to today with extreme accuracy and speedy. The applied CID (complexity invariant distance) analysis and multiscale CID analysis, are provided as the new useful measures to evaluate a better predicting ability of the proposed model than other traditional models. - Highlights: • A new forecasting model is developed by a random Elman recurrent neural network. • The forecasting accuracy of crude oil price fluctuations is improved by the model. • The forecasting results of the proposed model are more accurate than compared models. • Two new distance analysis methods are applied to confirm the predicting results.

  2. Forecasting value-at-risk and expected shortfall using fractionally integrated models of conditional volatility: international evidence

    OpenAIRE

    Degiannakis, Stavros; Floros, Christos; Dent, P.

    2013-01-01

    The present study compares the performance of the long memory FIGARCH model, with that of the short memory GARCH specification, in the forecasting of multi-period Value-at-Risk (VaR) and Expected Shortfall (ES) across 20 stock indices worldwide. The dataset is comprised of daily data covering the period from 1989 to 2009. The research addresses the question of whether or not accounting for long memory in the conditional variance specification improves the accuracy of the VaR and ES forecasts ...

  3. Quantifying uncertainty in Gulf of Mexico forecasts stemming from uncertain initial conditions

    KAUST Repository

    Iskandarani, Mohamed

    2016-06-09

    Polynomial Chaos (PC) methods are used to quantify the impacts of initial conditions uncertainties on oceanic forecasts of the Gulf of Mexico circulation. Empirical Orthogonal Functions are used as initial conditions perturbations with their modal amplitudes considered as uniformly distributed uncertain random variables. These perturbations impact primarily the Loop Current system and several frontal eddies located in its vicinity. A small ensemble is used to sample the space of the modal amplitudes and to construct a surrogate for the evolution of the model predictions via a nonintrusive Galerkin projection. The analysis of the surrogate yields verification measures for the surrogate\\'s reliability and statistical information for the model output. A variance analysis indicates that the sea surface height predictability in the vicinity of the Loop Current is limited to about 20 days. © 2016. American Geophysical Union. All Rights Reserved.

  4. Influence of Met-Ocean Condition Forecasting Uncertainties on Weather Window Predictions for Offshore Operations

    DEFF Research Database (Denmark)

    Gintautas, Tomas; Sørensen, John Dalsgaard

    2017-01-01

    The article briefly presents a novel methodology of weather window estimation for offshore operations and mainly focuses on effects of met-ocean condition forecasting uncertainties on weather window predictions when using the proposed methodology. It is demonstrated that the proposed methodology...... to include stochastic variables, representing met-ocean forecasting uncertainties and the results of such modification are given in terms of predicted weather windows for a selected test case....

  5. Overtaking as Indicator of Road Traffic Conditions

    Directory of Open Access Journals (Sweden)

    Dražen Topolnik

    2012-10-01

    Full Text Available Overtaking is presemed as one of the indicators of roadtraffic flow. The possibility of overtaking depends on the existenceof an intetval in the opposing traffic flow sufficient to performovertaking. It also analyses the probability of overtakingby applying adequate equations and graphical presentations

  6. Software INCAS (Convective Clouds Indicator to Seeding Activities) to convective clouds class forecast in Mendoza (Argentina).

    Science.gov (United States)

    Pérez, R. C.

    2009-09-01

    With the objective of to get to forecast and operative determinations tool to seeding of hailstorm in the damage mitigations job that produces its precipitation in Mendoza (Argentina), we developed to software based in on surface and 500 mb. level atmospherics variable. We had used on surface dates because in this level exist to big amount of information, practically it is possible to get its measures continuously; in addition it is the level that data of damages are registered that the hail precipitation produces. The decision to use the level of 500 mb, it must to that it is the height in which the upset one of the air circulation takes place from the Pacific to Mendoza, who produces important changes and instability in the atmosphere of Mendoza, these data were obtained from the radiosonde of Santo Domingo in Santiago (Chile) and El Plumerillo (Mendoza). In the program is integrated the different indices and models obtained in ours works from investigation on the subject of last the five years. Since the October of 2004 to April of 2009 the values have been taken from the variables mentioned every day, hourly during the fight campaigns antihail (October-April). The results have integrated in the program INCAS, whom it is due to enter the surface variables: Temperature in °C, the dew point in °C, the atmospheric pressure in mb., the index of ultraviolet solar radiation, the direction and wind speed; whereas the variables of the level of 500 are due to introduce mb: height of the level of 500 mb in meters, temperature of the level in °C, the direction and wind speed to that height. From the process of these variables the type of convective process is obtained like exit of the program , that is more probable that it appears in Mendoza for these atmospheric conditions; the thresholds that trigger to the stormy processes and their possible severity. This year software was validated in his first version, obtaining itself very good results.

  7. Predictive Uncertainty Estimation in Water Demand Forecasting Using the Model Conditional Processor

    Directory of Open Access Journals (Sweden)

    Amos O. Anele

    2018-04-01

    Full Text Available In a previous paper, a number of potential models for short-term water demand (STWD prediction have been analysed to find the ones with the best fit. The results obtained in Anele et al. (2017 showed that hybrid models may be considered as the accurate and appropriate forecasting models for STWD prediction. However, such best single valued forecast does not guarantee reliable and robust decisions, which can be properly obtained via model uncertainty processors (MUPs. MUPs provide an estimate of the full predictive densities and not only the single valued expected prediction. Amongst other MUPs, the purpose of this paper is to use the multi-variate version of the model conditional processor (MCP, proposed by Todini (2008, to demonstrate how the estimation of the predictive probability conditional to a number of relatively good predictive models may improve our knowledge, thus reducing the predictive uncertainty (PU when forecasting into the unknown future. Through the MCP approach, the probability distribution of the future water demand can be assessed depending on the forecast provided by one or more deterministic forecasting models. Based on an average weekly data of 168 h, the probability density of the future demand is built conditional on three models’ predictions, namely the autoregressive-moving average (ARMA, feed-forward back propagation neural network (FFBP-NN and hybrid model (i.e., combined forecast from ARMA and FFBP-NN. The results obtained show that MCP may be effectively used for real-time STWD prediction since it brings out the PU connected to its forecast, and such information could help water utilities estimate the risk connected to a decision.

  8. Pavement condition assessment to forecast maintenance program on JKR state roads in Petaling district

    Science.gov (United States)

    Hamsan, R.; Hafiz, H.; Azlan, A.; Keprawi, M. F.; Malik, A. K. A.; Adamuddin, A.; Abdullah, A. H.; Shafie, A. M.

    2018-02-01

    This research allows local authorities to project road maintenance in term of activities and financial expenditure through pavement condition assessment and then Highway Development and Management (HDM-4) analysis. Current form of road maintenance carried out by local authority is on reactive manner where corrective actions were taken based on reports recorded. Some went unrecorded hence causing prolonged damages. This causes the local authority unable to project the required cost to maintain the roads. This affects the socio-economy of the surrounding routes. Hence, it is seen, as preventive maintenance of the roads will provide more feasible option in term of work force and finance to the local authority. To overcome this issue, a preventive model was introduced. This was done through pavement condition assessment (PCA) where analysis was done through HDM-4. Nondestructive test and destructive test were conducted in order to provide an indicator to the road's health. This were then analyzed in HDM-4 where the result was benchmarked with maintenance standard. The scope of this research is set to PCA where DT and NDT were performed on the routes of Petaling and the output is analyzed in HDM-4. The result of this research provides a 10 years forecast maintenance budget in maintaining the roads in Petaling. This allows the local authority to perform good practice in term of maintaining the roads while at the same time helps them in forecasting their budget for the upcoming years. This research will have a strong impact on the local socio-economy as well as local road user confidence towards the authority over good practices. This research can be further expanded to other type of roads as well as highway bridges.

  9. Assimilation and High Resolution Forecasts of Surface and Near Surface Conditions for the 2010 Vancouver Winter Olympic and Paralympic Games

    Science.gov (United States)

    Bernier, Natacha B.; Bélair, Stéphane; Bilodeau, Bernard; Tong, Linying

    2014-01-01

    A dynamical model was experimentally implemented to provide high resolution forecasts at points of interests in the 2010 Vancouver Olympics and Paralympics Region. In a first experiment, GEM-Surf, the near surface and land surface modeling system, is driven by operational atmospheric forecasts and used to refine the surface forecasts according to local surface conditions such as elevation and vegetation type. In this simple form, temperature and snow depth forecasts are improved mainly as a result of the better representation of real elevation. In a second experiment, screen level observations and operational atmospheric forecasts are blended to drive a continuous cycle of near surface and land surface hindcasts. Hindcasts of the previous day conditions are then regarded as today's optimized initial conditions. Hence, in this experiment, given observations are available, observation driven hindcasts continuously ensure that daily forecasts are issued from improved initial conditions. GEM-Surf forecasts obtained from improved short-range hindcasts produced using these better conditions result in improved snow depth forecasts. In a third experiment, assimilation of snow depth data is applied to further optimize GEM-Surf's initial conditions, in addition to the use of blended observations and forecasts for forcing. Results show that snow depth and summer temperature forecasts are further improved by the addition of snow depth data assimilation.

  10. An application and verification of ensemble forecasting on wind power to assess operational risk indicators in power grids

    Energy Technology Data Exchange (ETDEWEB)

    Alessandrini, S.; Ciapessoni, E.; Cirio, D.; Pitto, A.; Sperati, S. [Ricerca sul Sistema Energetico RSE S.p.A., Milan (Italy). Power System Development Dept. and Environment and Sustainable Development Dept.; Pinson, P. [Technical University of Denmark, Lyngby (Denmark). DTU Informatics

    2012-07-01

    Wind energy is part of the so-called not schedulable renewable sources, i.e. it must be exploited when it is available, otherwise it is lost. In European regulation it has priority of dispatch over conventional generation, to maximize green energy production. However, being variable and uncertain, wind (and solar) generation raises several issues for the security of the power grids operation. In particular, Transmission System Operators (TSOs) need as accurate as possible forecasts. Nowadays a deterministic approach in wind power forecasting (WPF) could easily be considered insufficient to face the uncertainty associated to wind energy. In order to obtain information about the accuracy of a forecast and a reliable estimation of its uncertainty, probabilistic forecasting is becoming increasingly widespread. In this paper we investigate the performances of the COnsortium for Small-scale MOdelling Limited area Ensemble Prediction System (COSMO-LEPS). First the ensemble application is followed by assessment of its properties (i.e. consistency, reliability) using different verification indices and diagrams calculated on wind power. Then we provide examples of how EPS based wind power forecast can be used in power system security analyses. Quantifying the forecast uncertainty allows to determine more accurately the regulation reserve requirements, hence improving security of operation and reducing system costs. In particular, the paper also presents a probabilistic power flow (PPF) technique developed at RSE and aimed to evaluate the impact of wind power forecast accuracy on the probability of security violations in power systems. (orig.)

  11. Forecasting the condition of petroleum impregnated load bearing ...

    African Journals Online (AJOL)

    Petroleum products (PP) used in industrial processes systematically fall on the load-bearing CRC structures and gradually impregnate therein. Currently, available guidelines for the assessment of technical condition and reliability of load-bearing CRC structures do not fully take into account the effect of viscosity of PP that ...

  12. Improving Energy Use Forecast for Campus Micro-grids using Indirect Indicators

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Computer Science; Simmhan, Yogesh [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Electrical Engineering; Prasanna, Viktor K. [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Electrical Engineering

    2011-12-11

    The rising global demand for energy is best addressed by adopting and promoting sustainable methods of power consumption. We employ an informatics approach towards forecasting the energy consumption patterns in a university campus micro-grid which can be used for energy use planning and conservation. We use novel indirect indicators of energy that are commonly available to train regression tree models that can predict campus and building energy use for coarse (daily) and fine (15-min) time intervals, utilizing 3 years of sensor data collected at 15min intervals from 170 smart power meters. We analyze the impact of individual features used in the models to identify the ones best suited for the application. Our models show a high degree of accuracy with CV-RMSE errors ranging from 7.45% to 19.32%, and a reduction in error from baseline models by up to 53%.

  13. Methods of forecasting crack growth rate under creep conditions

    International Nuclear Information System (INIS)

    Ol'kin, S.I.

    1979-01-01

    Using construction aluminium alloy application possibility of linear mechanics of the destruction for quantitative description of crack development process under creepage conditions is investigated. It is shown, that the grade dependence between the stress intensity coefficient and the crack growth rate takes place only at certain combination of the sample geometry and creepage parameters, and consequently, its applicability in every given case must necessarily be tested experimentally

  14. Forecasting the Rupture Directivity of Large Earthquakes: Centroid Bias of the Conditional Hypocenter Distribution

    Science.gov (United States)

    Donovan, J.; Jordan, T. H.

    2012-12-01

    Forecasting the rupture directivity of large earthquakes is an important problem in probabilistic seismic hazard analysis (PSHA), because directivity is known to strongly influence ground motions. We describe how rupture directivity can be forecast in terms of the "conditional hypocenter distribution" or CHD, defined to be the probability distribution of a hypocenter given the spatial distribution of moment release (fault slip). The simplest CHD is a uniform distribution, in which the hypocenter probability density equals the moment-release probability density. For rupture models in which the rupture velocity and rise time depend only on the local slip, the CHD completely specifies the distribution of the directivity parameter D, defined in terms of the degree-two polynomial moments of the source space-time function. This parameter, which is zero for a bilateral rupture and unity for a unilateral rupture, can be estimated from finite-source models or by the direct inversion of seismograms (McGuire et al., 2002). We compile D-values from published studies of 65 large earthquakes and show that these data are statistically inconsistent with the uniform CHD advocated by McGuire et al. (2002). Instead, the data indicate a "centroid biased" CHD, in which the expected distance between the hypocenter and the hypocentroid is less than that of a uniform CHD. In other words, the observed directivities appear to be closer to bilateral than predicted by this simple model. We discuss the implications of these results for rupture dynamics and fault-zone heterogeneities. We also explore their PSHA implications by modifying the CyberShake simulation-based hazard model for the Los Angeles region, which assumed a uniform CHD (Graves et al., 2011).

  15. Modeling and Forecasting the Onset and Duration of Severe Radiation Fog under Frost Conditions

    NARCIS (Netherlands)

    van der Velde, I. R.; Steeneveld, G. J.; Schreur, B. G. J. Wichers; Holtslag, A. A. M.

    2010-01-01

    A case of a severe radiation fog during frost conditions is analyzed as a benchmark for the development of a very high-resolution NWP model Results by the Weather Research and Forecasting model (WRF) and the High Resolution Limited Area Model (H I RLAM) are evaluated against detailed observations to

  16. Modeling and Forecasting the Onset and Duration of Severe Radiation Fog under Frost Conditions

    NARCIS (Netherlands)

    Velde, van der I.R.; Steeneveld, G.J.; Wichers Schreur, B.G.J.; Holtslag, A.A.M.

    2010-01-01

    A case of a severe radiation fog during frost conditions is analyzed as a benchmark for the development of a very high resolution NWP model. Results by the Weather Research and Forecasting model (WRF) and the High resolution limited area model (HIRLAM) are evaluated against detailed observations to

  17. USDA Foreign Agricultural Service overview for operational monitoring of current crop conditions and production forecasts.

    Science.gov (United States)

    Crutchfield, J.

    2016-12-01

    The presentation will discuss the current status of the International Production Assessment Division of the USDA ForeignAgricultural Service for operational monitoring and forecasting of current crop conditions, and anticipated productionchanges to produce monthly, multi-source consensus reports on global crop conditions including the use of Earthobservations (EO) from satellite and in situ sources.United States Department of Agriculture (USDA) Foreign Agricultural Service (FAS) International Production AssessmentDivision (IPAD) deals exclusively with global crop production forecasting and agricultural analysis in support of the USDAWorld Agricultural Outlook Board (WAOB) lockup process and contributions to the World Agricultural Supply DemandEstimates (WASE) report. Analysts are responsible for discrete regions or countries and conduct in-depth long-termresearch into national agricultural statistics, farming systems, climatic, environmental, and economic factors affectingcrop production. IPAD analysts become highly valued cross-commodity specialists over time, and are routinely soughtout for specialized analyses to support governmental studies. IPAD is responsible for grain, oilseed, and cotton analysison a global basis. IPAD is unique in the tools it uses to analyze crop conditions around the world, including customweather analysis software and databases, satellite imagery and value-added image interpretation products. It alsoincorporates all traditional agricultural intelligence resources into its forecasting program, to make the fullest use ofavailable information in its operational commodity forecasts and analysis. International travel and training play animportant role in learning about foreign agricultural production systems and in developing analyst knowledge andcapabilities.

  18. Shared investment projects and forecasting errors: setting framework conditions for coordination and sequencing data quality activities.

    Science.gov (United States)

    Leitner, Stephan; Brauneis, Alexander; Rausch, Alexandra

    2015-01-01

    In this paper, we investigate the impact of inaccurate forecasting on the coordination of distributed investment decisions. In particular, by setting up a computational multi-agent model of a stylized firm, we investigate the case of investment opportunities that are mutually carried out by organizational departments. The forecasts of concern pertain to the initial amount of money necessary to launch and operate an investment opportunity, to the expected intertemporal distribution of cash flows, and the departments' efficiency in operating the investment opportunity at hand. We propose a budget allocation mechanism for coordinating such distributed decisions The paper provides guidance on how to set framework conditions, in terms of the number of investment opportunities considered in one round of funding and the number of departments operating one investment opportunity, so that the coordination mechanism is highly robust to forecasting errors. Furthermore, we show that-in some setups-a certain extent of misforecasting is desirable from the firm's point of view as it supports the achievement of the corporate objective of value maximization. We then address the question of how to improve forecasting quality in the best possible way, and provide policy advice on how to sequence activities for improving forecasting quality so that the robustness of the coordination mechanism to errors increases in the best possible way. At the same time, we show that wrong decisions regarding the sequencing can lead to a decrease in robustness. Finally, we conduct a comprehensive sensitivity analysis and prove that-in particular for relatively good forecasters-most of our results are robust to changes in setting the parameters of our multi-agent simulation model.

  19. Shared investment projects and forecasting errors: setting framework conditions for coordination and sequencing data quality activities.

    Directory of Open Access Journals (Sweden)

    Stephan Leitner

    Full Text Available In this paper, we investigate the impact of inaccurate forecasting on the coordination of distributed investment decisions. In particular, by setting up a computational multi-agent model of a stylized firm, we investigate the case of investment opportunities that are mutually carried out by organizational departments. The forecasts of concern pertain to the initial amount of money necessary to launch and operate an investment opportunity, to the expected intertemporal distribution of cash flows, and the departments' efficiency in operating the investment opportunity at hand. We propose a budget allocation mechanism for coordinating such distributed decisions The paper provides guidance on how to set framework conditions, in terms of the number of investment opportunities considered in one round of funding and the number of departments operating one investment opportunity, so that the coordination mechanism is highly robust to forecasting errors. Furthermore, we show that-in some setups-a certain extent of misforecasting is desirable from the firm's point of view as it supports the achievement of the corporate objective of value maximization. We then address the question of how to improve forecasting quality in the best possible way, and provide policy advice on how to sequence activities for improving forecasting quality so that the robustness of the coordination mechanism to errors increases in the best possible way. At the same time, we show that wrong decisions regarding the sequencing can lead to a decrease in robustness. Finally, we conduct a comprehensive sensitivity analysis and prove that-in particular for relatively good forecasters-most of our results are robust to changes in setting the parameters of our multi-agent simulation model.

  20. New forecasting methodology indicates more disease and earlier mortality ahead for today's younger Americans.

    Science.gov (United States)

    Reither, Eric N; Olshansky, S Jay; Yang, Yang

    2011-08-01

    Traditional methods of projecting population health statistics, such as estimating future death rates, can give inaccurate results and lead to inferior or even poor policy decisions. A new "three-dimensional" method of forecasting vital health statistics is more accurate because it takes into account the delayed effects of the health risks being accumulated by today's younger generations. Applying this forecasting technique to the US obesity epidemic suggests that future death rates and health care expenditures could be far worse than currently anticipated. We suggest that public policy makers adopt this more robust forecasting tool and redouble efforts to develop and implement effective obesity-related prevention programs and interventions.

  1. Process-conditioned bias correction for seasonal forecasting: a case-study with ENSO in Peru

    Science.gov (United States)

    Manzanas, R.; Gutiérrez, J. M.

    2018-05-01

    This work assesses the suitability of a first simple attempt for process-conditioned bias correction in the context of seasonal forecasting. To do this, we focus on the northwestern part of Peru and bias correct 1- and 4-month lead seasonal predictions of boreal winter (DJF) precipitation from the ECMWF System4 forecasting system for the period 1981-2010. In order to include information about the underlying large-scale circulation which may help to discriminate between precipitation affected by different processes, we introduce here an empirical quantile-quantile mapping method which runs conditioned on the state of the Southern Oscillation Index (SOI), which is accurately predicted by System4 and is known to affect the local climate. Beyond the reduction of model biases, our results show that the SOI-conditioned method yields better ROC skill scores and reliability than the raw model output over the entire region of study, whereas the standard unconditioned implementation provides no added value for any of these metrics. This suggests that conditioning the bias correction on simple but well-simulated large-scale processes relevant to the local climate may be a suitable approach for seasonal forecasting. Yet, further research on the suitability of the application of similar approaches to the one considered here for other regions, seasons and/or variables is needed.

  2. Antibiotic use in Brazilian broiler and pig production: an indication and forecast of trends

    NARCIS (Netherlands)

    Bokma-Bakker, M.H.; Bondt, N.; Neijenhuis, F.; Mevius, D.J.; Ruiter, S.J.M.

    2014-01-01

    To gain insight in antibiotic use in relation to imported products the current use of antibiotics in pork and broiler production in Brazil are identified and trend forecasting of antibiotic use in the coming 3-5 years is performed.

  3. Continued Evaluation of Gear Condition Indicator Performance on Rotorcraft Fleet

    Science.gov (United States)

    Delgado, Irebert R.; Dempsey, Paula J.; Antolick, Lance J.; Wade, Daniel R.

    2013-01-01

    This paper details analyses of condition indicator performance for the helicopter nose gearbox within the U.S. Army's Condition-Based Maintenance Program. Ten nose gearbox data sets underwent two specific analyses. A mean condition indicator level analysis was performed where condition indicator performance was based on a 'batting average' measured before and after part replacement. Two specific condition indicators, Diagnostic Algorithm 1 and Sideband Index, were found to perform well for the data sets studied. A condition indicator versus gear wear analysis was also performed, where gear wear photographs and descriptions from Army tear-down analyses were categorized based on ANSI/AGMA 1010-E95 standards. Seven nose gearbox data sets were analyzed and correlated with condition indicators Diagnostic Algorithm 1 and Sideband Index. Both were found to be most responsive to gear wear cases of micropitting and spalling. Input pinion nose gear box condition indicators were found to be more responsive to part replacement during overhaul than their corresponding output gear nose gear box condition indicators.

  4. Shared Investment Projects and Forecasting Errors: Setting Framework Conditions for Coordination and Sequencing Data Quality Activities

    Science.gov (United States)

    Leitner, Stephan; Brauneis, Alexander; Rausch, Alexandra

    2015-01-01

    In this paper, we investigate the impact of inaccurate forecasting on the coordination of distributed investment decisions. In particular, by setting up a computational multi-agent model of a stylized firm, we investigate the case of investment opportunities that are mutually carried out by organizational departments. The forecasts of concern pertain to the initial amount of money necessary to launch and operate an investment opportunity, to the expected intertemporal distribution of cash flows, and the departments’ efficiency in operating the investment opportunity at hand. We propose a budget allocation mechanism for coordinating such distributed decisions The paper provides guidance on how to set framework conditions, in terms of the number of investment opportunities considered in one round of funding and the number of departments operating one investment opportunity, so that the coordination mechanism is highly robust to forecasting errors. Furthermore, we show that—in some setups—a certain extent of misforecasting is desirable from the firm’s point of view as it supports the achievement of the corporate objective of value maximization. We then address the question of how to improve forecasting quality in the best possible way, and provide policy advice on how to sequence activities for improving forecasting quality so that the robustness of the coordination mechanism to errors increases in the best possible way. At the same time, we show that wrong decisions regarding the sequencing can lead to a decrease in robustness. Finally, we conduct a comprehensive sensitivity analysis and prove that—in particular for relatively good forecasters—most of our results are robust to changes in setting the parameters of our multi-agent simulation model. PMID:25803736

  5. Humans as Sensors: Assessing the Information Value of Qualitative Farmer's Crop Condition Surveys for Crop Yield Monitoring and Forecasting

    Science.gov (United States)

    Beguería, S.

    2017-12-01

    While large efforts are devoted to developing crop status monitoring and yield forecasting systems trough the use of Earth observation data (mostly remotely sensed satellite imagery) and observational and modeled weather data, here we focus on the information value of qualitative data on crop status from direct observations made by humans. This kind of data has a high value as it reflects the expert opinion of individuals directly involved in the development of the crop. However, they have issues that prevent their direct use in crop monitoring and yield forecasting systems, such as their non-spatially explicit nature, or most importantly their qualitative nature. Indeed, while the human brain is good at categorizing the status of physical systems in terms of qualitative scales (`very good', `good', `fair', etcetera), it has difficulties in quantifying it in physical units. This has prevented the incorporation of this kind of data into systems that make extensive use of numerical information. Here we show an example of using qualitative crop condition data to estimate yields of the most important crops in the US early in the season. We use USDA weekly crop condition reports, which are based on a sample of thousands of reporters including mostly farmers and people in direct contact with them. These reporters provide subjective evaluations of crop conditions, in a scale including five levels ranging from `very poor' to `excellent'. The USDA report indicates, for each state, the proportion of reporters fort each condition level. We show how is it possible to model the underlying non-observed quantitative variable that reflects the crop status on each state, and how this model is consistent across states and years. Furthermore, we show how this information can be used to monitor the status of the crops and to produce yield forecasts early in the season. Finally, we discuss approaches for blending this information source with other, more classical earth data sources

  6. 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.

  7. Demand Forecasting at Low Aggregation Levels using Factored Conditional Restricted Boltzmann Machine

    DEFF Research Database (Denmark)

    Mocanu, Elena; Nguyen, Phuong H.; Gibescu, Madeleine

    2016-01-01

    electric power consumption, local price and meteorological data collected from 1900 customers. The households are equipped with local generation and smart appliances capable of responding to realtime pricing signals. The results show that for the short-term (5 minute to 1 day ahead) prediction problems......The electrical demand forecasting problem can be regarded as a nonlinear time series prediction problem depending on many complex factors since it is required at various aggregation levels and at high temporal resolution. To solve this challenging problem, various time series and machine learning...... developed deep learning model for time series prediction, namely Factored Conditional Restricted Boltzmann Machine (FCRBM), and extend it for electrical demand forecasting. The assessment is made on the EcoGrid dataset, originating from the Bornholm island experiment in Denmark, consisting of aggregated...

  8. 30 Fulton's condition, organ indices and haematological response of ...

    African Journals Online (AJOL)

    `123456789jkl''''#

    Abstract. This study was conducted to assess the Fulton's condition, organ indices and haematological response of catfish hybrid ... Haematological study is of immense importance .... give information on the stock composite, age at maturity ...

  9. Short-term forecasting of Czech quarterly GDP using monthly indicators

    Czech Academy of Sciences Publication Activity Database

    Arnoštová, K.; Havrlant, D.; Růžička, L.; Tóth, Peter

    2011-01-01

    Roč. 61, č. 6 (2011), s. 566-583 ISSN 0015-1920 Institutional research plan: CEZ:MSM0021620846 Keywords : GDP forecasting * bridge models * principal components Subject RIV: AH - Economics Impact factor: 0.346, year: 2011 http://journal.fsv.cuni.cz/storage/1235_toth.pdf

  10. An experimental seasonal hydrological forecasting system over the Yellow River basin - Part 1: Understanding the role of initial hydrological conditions

    Science.gov (United States)

    Yuan, Xing; Ma, Feng; Wang, Linying; Zheng, Ziyan; Ma, Zhuguo; Ye, Aizhong; Peng, Shaoming

    2016-06-01

    The hydrological cycle over the Yellow River has been altered by the climate change and human interventions greatly during past decades, with a decadal drying trend mixed with a large variation of seasonal hydrological extremes. To provide support for the adaptation to a changing environment, an experimental seasonal hydrological forecasting system is established over the Yellow River basin. The system draws from a legacy of a global hydrological forecasting system that is able to make use of real-time seasonal climate predictions from North American Multimodel Ensemble (NMME) climate models through a statistical downscaling approach but with a higher resolution and a spatially disaggregated calibration procedure that is based on a newly compiled hydrological observation dataset with 5 decades of naturalized streamflow at 12 mainstream gauges and a newly released meteorological observation dataset including 324 meteorological stations over the Yellow River basin. While the evaluation of the NMME-based seasonal hydrological forecasting will be presented in a companion paper to explore the added values from climate forecast models, this paper investigates the role of initial hydrological conditions (ICs) by carrying out 6-month Ensemble Streamflow Prediction (ESP) and reverse ESP-type simulations for each calendar month during 1982-2010 with the hydrological models in the forecasting system, i.e., a large-scale land surface hydrological model and a global routing model that is regionalized over the Yellow River. In terms of streamflow predictability, the ICs outweigh the meteorological forcings up to 2-5 months during the cold and dry seasons, but the latter prevails over the former in the predictability after the first month during the warm and wet seasons. For the streamflow forecasts initialized at the end of the rainy season, the influence of ICs for lower reaches of the Yellow River can be 5 months longer than that for the upper reaches, while such a difference

  11. Solar irradiance forecasting at one-minute intervals for different sky conditions using sky camera images

    International Nuclear Information System (INIS)

    Alonso-Montesinos, J.; Batlles, F.J.; Portillo, C.

    2015-01-01

    Highlights: • The solar resource has been predicted for three hours at 1-min intervals. • Digital image levels and cloud motion vectors are joint for irradiance forecasting. • The three radiation components have been predicted under different sky conditions. • Diffuse and global radiation has an nRMSE value around 10% in all sky conditions. • Beam irradiance is predicted with an nRMSE value of about 15% in overcast skies. - Abstract: In the search for new techniques to predict atmospheric features that might be useful to solar power plant operators, we have carried out solar irradiance forecasting using emerging sky camera technology. Digital image levels are converted into irradiances and then the maximum cross-correlation method is applied to obtain future predictions. This methodology is a step forward in the study of the solar resource, essential to solar plant operators in adapting a plant’s operating procedures to atmospheric conditions and to improve electricity generation. The results are set out using different statistical parameters, in which beam, diffuse and global irradiances give a constant normalized root-mean-square error value over the time interval for all sky conditions. The average measure is 25.44% for beam irradiance; 11.60% for diffuse irradiance and 11.17% for global irradiance.

  12. Assessment of senior pupils’ physical fitness considering physical condition indicators

    Directory of Open Access Journals (Sweden)

    I.R. Bodnar

    2016-12-01

    Full Text Available Consideration of physical condition indicators in assessment pupils’ physical fitness permits to differentiate training and health restoration processes at physical culture lessons. Purpose: to substantiate criteria for pupils’ physical fitness assessment, considering their physical condition indicators. Material: in the research 10-11 form pupils (n=406; 211boys and 195 girls participated. After physical fitness testing by requirement of acting programs we carried out diagnostic of pupils’ psycho-emotional state. Results: by results of physical; fitness we observed substantial deviation from universal law of normal distribution. It was found that physical condition indicators of most pupils are beyond normal. It was also determined that the most informative indicators are body length, chest circumference and body relative mass. We substantiated that it is necessary to consider physical condition indicators, when determining physical fitness level. We also substantiated and worked out differentiated normative for assessment pupils’ physical fitness. Conclusions: testing without consideration physical condition indicators does not facilitate pupils’ motivation for further physical self-perfection. Such testing results in high situational anxiety and unfavorable psycho-emotional state of pupils.

  13. Forecast daily indices of solar activity, F10.7, using support vector regression method

    International Nuclear Information System (INIS)

    Huang Cong; Liu Dandan; Wang Jingsong

    2009-01-01

    The 10.7 cm solar radio flux (F10.7), the value of the solar radio emission flux density at a wavelength of 10.7 cm, is a useful index of solar activity as a proxy for solar extreme ultraviolet radiation. It is meaningful and important to predict F10.7 values accurately for both long-term (months-years) and short-term (days) forecasting, which are often used as inputs in space weather models. This study applies a novel neural network technique, support vector regression (SVR), to forecasting daily values of F10.7. The aim of this study is to examine the feasibility of SVR in short-term F10.7 forecasting. The approach, based on SVR, reduces the dimension of feature space in the training process by using a kernel-based learning algorithm. Thus, the complexity of the calculation becomes lower and a small amount of training data will be sufficient. The time series of F10.7 from 2002 to 2006 are employed as the data sets. The performance of the approach is estimated by calculating the norm mean square error and mean absolute percentage error. It is shown that our approach can perform well by using fewer training data points than the traditional neural network. (research paper)

  14. THE ANALYSIS OF THE COMMODITY PRICE FORECASTING SUCCESS CONSIDERING DIFFERENT LENGTHS OF THE INITIAL CONDITION DRIFT

    Directory of Open Access Journals (Sweden)

    Marcela Lascsáková

    2015-09-01

    Full Text Available In the paper the numerical model based on the exponential approximation of commodity stock exchanges was derived. The price prognoses of aluminium on the London Metal Exchange were determined as numerical solution of the Cauchy initial problem for the 1st order ordinary differential equation. To make the numerical model more accurate the idea of the modification of the initial condition value by the stock exchange was realized. By having analyzed the forecasting success of the chosen initial condition drift types, the initial condition drift providing the most accurate prognoses for the commodity price movements was determined. The suggested modification of the original model made the commodity price prognoses more accurate.

  15. DEPENDENCE OF WASTE PAPER QUALITATIVE INDICES ON ITS STORAGE CONDITIONS

    Directory of Open Access Journals (Sweden)

    I. Karpunin

    2012-01-01

    Full Text Available The paper investigates an influence of component quantity (lignin, cellulose and hemicellulose on qualitative (physical and mechanical indices of waste-paper in relation to its storage period and weather conditions. It has been established that while storing (in waste dumps waste paper it is to be kept at a definite temperature and humidity in order to reduce impact of weather conditions.

  16. Dynamic Forecasting Conditional Probability of Bombing Attacks Based on Time-Series and Intervention Analysis.

    Science.gov (United States)

    Li, Shuying; Zhuang, Jun; Shen, Shifei

    2017-07-01

    In recent years, various types of terrorist attacks occurred, causing worldwide catastrophes. According to the Global Terrorism Database (GTD), among all attack tactics, bombing attacks happened most frequently, followed by armed assaults. In this article, a model for analyzing and forecasting the conditional probability of bombing attacks (CPBAs) based on time-series methods is developed. In addition, intervention analysis is used to analyze the sudden increase in the time-series process. The results show that the CPBA increased dramatically at the end of 2011. During that time, the CPBA increased by 16.0% in a two-month period to reach the peak value, but still stays 9.0% greater than the predicted level after the temporary effect gradually decays. By contrast, no significant fluctuation can be found in the conditional probability process of armed assault. It can be inferred that some social unrest, such as America's troop withdrawal from Afghanistan and Iraq, could have led to the increase of the CPBA in Afghanistan, Iraq, and Pakistan. The integrated time-series and intervention model is used to forecast the monthly CPBA in 2014 and through 2064. The average relative error compared with the real data in 2014 is 3.5%. The model is also applied to the total number of attacks recorded by the GTD between 2004 and 2014. © 2016 Society for Risk Analysis.

  17. Air Pollution Forecasts: An Overview

    Science.gov (United States)

    Bai, Lu; Wang, Jianzhou; Lu, Haiyan

    2018-01-01

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies. PMID:29673227

  18. Air Pollution Forecasts: An Overview.

    Science.gov (United States)

    Bai, Lu; Wang, Jianzhou; Ma, Xuejiao; Lu, Haiyan

    2018-04-17

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  19. Air Pollution Forecasts: An Overview

    Directory of Open Access Journals (Sweden)

    Lu Bai

    2018-04-01

    Full Text Available Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  20. Condition Indicators for Inspection Planning of Concrete Structures

    DEFF Research Database (Denmark)

    Faber, Michael Havbro; Sørensen, John Dalsgaard

    2002-01-01

    Based on previous work by the authors a Bayesian formulation of condition indicators is developed further whereby in conjunction with a systems modelling of concrete structures the experience and expertise of the inspection personnel may be fully utilized. It is shown how the predicted evolution ...

  1. AHP for indicators of sustainable forestry under Mediterranean conditions

    International Nuclear Information System (INIS)

    Valls-Donderis, P.; Vallés-Planells, M.; Galiana, F.

    2017-01-01

    Aim of study: To verify and prioritise a set of sustainable forestry indicators using the Analytic Hierarchy Process (AHP). Area of study: Participants were Spanish; indicators were meant to be applied in forest management units (FMUs) under Mediterranean conditions. Material and methods: An AHP questionnaire was developed and sent to experts. Main Results: the set of indicators aimed to be comprehensive. Indicators were ranked and the ranking allows ascertaining what aspects are more relevant in relation to Mediterranean sustainable forestry. Issues like regeneration or habitats conservation got high values, whereas others like hunting activity were not seen as important by most experts. Research highlights: - Sustainable forest management (SFM) considerations for Mediterranean forests. - Indicators adapt to ecosystem services.

  2. AHP for indicators of sustainable forestry under Mediterranean conditions

    Energy Technology Data Exchange (ETDEWEB)

    Valls-Donderis, P.; Vallés-Planells, M.; Galiana, F.

    2017-11-01

    Aim of study: To verify and prioritise a set of sustainable forestry indicators using the Analytic Hierarchy Process (AHP). Area of study: Participants were Spanish; indicators were meant to be applied in forest management units (FMUs) under Mediterranean conditions. Material and methods: An AHP questionnaire was developed and sent to experts. Main Results: the set of indicators aimed to be comprehensive. Indicators were ranked and the ranking allows ascertaining what aspects are more relevant in relation to Mediterranean sustainable forestry. Issues like regeneration or habitats conservation got high values, whereas others like hunting activity were not seen as important by most experts. Research highlights: - Sustainable forest management (SFM) considerations for Mediterranean forests. - Indicators adapt to ecosystem services.

  3. Evaluating Microbial Indicators of Environmental Condition in Oregon Rivers

    Science.gov (United States)

    Pennington, Alan T.; Harding, Anna K.; Hendricks, Charles W.; Campbell, Heidi M. K.

    2001-12-01

    Traditional bacterial indicators used in public health to assess water quality and the Biolog® system were evaluated to compare their response to biological, chemical, and physical habitat indicators of stream condition both within the state of Oregon and among ecoregion aggregates (Coast Range, Willamette Valley, Cascades, and eastern Oregon). Forty-three randomly selected Oregon river sites were sampled during the summer in 1997 and 1998. The public health indicators included heterotrophic plate counts (HPC), total coliforms (TC), fecal coliforms (FC) and Escherichia coli (EC). Statewide, HPC correlated strongly with physical habitat (elevation, riparian complexity, % canopy presence, and indices of agriculture, pavement, road, pasture, and total disturbance) and chemistry (pH, dissolved O2, specific conductance, acid-neutralizing capacity, dissolved organic carbon, total N, total P, SiO2, and SO4). FC and EC were significantly correlated generally with the river chemistry indicators. TC bacteria significantly correlated with riparian complexity, road disturbance, dissolved O2, and SiO2 and FC. Analyzing the sites by ecoregion, eastern Oregon was characterized by high HPC, FC, EC, nutrient loads, and indices of human disturbance, whereas the Cascades ecoregion had correspondingly low counts of these indicators. The Coast Range and Willamette Valley presented inconsistent indicator patterns that are more difficult to characterize. Attempts to distinguish between ecoregions with the Biolog system were not successful, nor did a statistical pattern emerge between the first five principle components and the other environmental indicators. Our research suggests that some traditional public health microbial indicators may be useful in measuring the environmental condition of lotic systems.

  4. Analysis and forecast of the economic indicators of S.C DEDEMAN.SRL

    Directory of Open Access Journals (Sweden)

    Mihai FÂNARU

    2016-07-01

    Full Text Available The increasing pace of change characteristic to the contemporary era requires anticipating them on larger period of time. Researching the future becomes a constant concern of both individuals and professionals as well as some national and international bodies and institutions. As John Naisbitt states, "a man can survive only by its ability to act in the present, based on past experience, with consequences in the future. Assuming ones future, the man makes his present bearable and its past significant. Past, present and future alternatives are intertwined in anticipation and forecasting of future actions. "The bricolage market is estimated at a value of 2 billion euro, being currently dominated by Romanian players like Dedeman, Arabesque and Ambient. The approximate knowledge of the future is a way through which the bricolage company Dedeman is preparing to face the unexpected.

  5. The case for indicator condition-guided HIV screening

    DEFF Research Database (Denmark)

    Lazarus, J V; Hoekstra, M; Raben, D

    2013-01-01

    One-half of the estimated 2.5 million people who now live with HIV in the World Health Organization (WHO) European Region are still diagnosed late. A central question is which clinical scenarios should trigger an HIV test recommendation in order to avoid late presentation. Drawing on the work...... of the HIV Indicator Diseases across Europe Study (HIDES), new guidance brings together in one place a list of the conditions that should result in an HIV screening recommendation....

  6. Evaluation of Gear Condition Indicator Performance on Rotorcraft Fleet

    Science.gov (United States)

    Antolick, Lance J.; Branning, Jeremy S.; Wade, Daniel R.; Dempsey, Paula J.

    2010-01-01

    The U.S. Army is currently expanding its fleet of Health Usage Monitoring Systems (HUMS) equipped aircraft at significant rates, to now include over 1,000 rotorcraft. Two different on-board HUMS, the Honeywell Modern Signal Processing Unit (MSPU) and the Goodrich Integrated Vehicle Health Management System (IVHMS), are collecting vibration health data on aircraft that include the Apache, Blackhawk, Chinook, and Kiowa Warrior. The objective of this paper is to recommend the most effective gear condition indicators for fleet use based on both a theoretical foundation and field data. Gear diagnostics with better performance will be recommended based on both a theoretical foundation and results of in-fleet use. In order to evaluate the gear condition indicator performance on rotorcraft fleets, results of more than five years of health monitoring for gear faults in the entire HUMS equipped Army helicopter fleet will be presented. More than ten examples of gear faults indicated by the gear CI have been compiled and each reviewed for accuracy. False alarms indications will also be discussed. Performance data from test rigs and seeded fault tests will also be presented. The results of the fleet analysis will be discussed, and a performance metric assigned to each of the competing algorithms. Gear fault diagnostic algorithms that are compliant with ADS-79A will be recommended for future use and development. The performance of gear algorithms used in the commercial units and the effectiveness of the gear CI as a fault identifier will be assessed using the criteria outlined in the standards in ADS-79A-HDBK, an Army handbook that outlines the conversion from Reliability Centered Maintenance to the On-Condition status of Condition Based Maintenance.

  7. Analysis of Urine as Indicators of Specific Body Conditions

    Science.gov (United States)

    Dey, Souradeep; Saha, Triya; Narendrakumar, Uttamchand

    2017-11-01

    Urinalysis can be defined as a procedure for examining various factors of urine, which include physical properties, particulate matter, cells, casts, crystals, organisms and solutes. Urinalysis is recommended to be a part of the initial examination of all patients as its cheap, feasible and gives productive results. This paper focuses on the analysis of urine collected at specific body conditions. Here we illustrate the urine profile of different persons having various body conditions, which include, having urinary tract infection, undergoing strenuous exercise, having back pain regularly, having very low urine output and a person who is on 24 hours of diet. Examination of urine collected from different persons having specific body conditions usually helps us in the diagnosis of various diseases, which it indicates.

  8. Evaluating how variants of floristic quality assessment indicate wetland condition.

    Science.gov (United States)

    Kutcher, Thomas E; Forrester, Graham E

    2018-03-28

    Biological indicators are useful tools for the assessment of ecosystem condition. Multi-metric and multi-taxa indicators may respond to a broader range of disturbances than simpler indicators, but their complexity can make them difficult to interpret, which is critical to indicator utility for ecosystem management. Floristic Quality Assessment (FQA) is an example of a biological assessment approach that has been widely tested for indicating freshwater wetland condition, but less attention has been given to clarifying the factors controlling its response. FQA quantifies the aggregate of vascular plant species tolerance to habitat degradation (conservatism), and model variants have incorporated species richness, abundance, and indigenity (native or non-native). To assess bias, we tested FQA variants in open-canopy freshwater wetlands against three independent reference measures, using practical vegetation sampling methods. FQA variants incorporating species richness did not correlate with our reference measures and were influenced by wetland size and hydrogeomorphic class. In contrast, FQA variants lacking measures of species richness responded linearly to reference measures quantifying individual and aggregate stresses, suggesting a broad response to cumulative degradation. FQA variants incorporating non-native species, and a variant additionally incorporating relative species abundance, improved performance over using only native species. We relate our empirical findings to ecological theory to clarify the functional properties and implications of the FQA variants. Our analysis indicates that (1) aggregate conservatism reliably declines with increased disturbance; (2) species richness has varying relationships with disturbance and increases with site area, confounding FQA response; and (3) non-native species signal human disturbance. We propose that incorporating species abundance can improve FQA site-level relevance with little extra sampling effort. Using our

  9. West-WRF Sensitivity to Sea Surface Temperature Boundary Condition in California Precipitation Forecasts of AR Related Events

    Science.gov (United States)

    Zhang, X.; Cornuelle, B. D.; Martin, A.; Weihs, R. R.; Ralph, M.

    2017-12-01

    We evaluated the merit in coastal precipitation forecasts by inclusion of high resolution sea surface temperature (SST) from blended satellite and in situ observations as a boundary condition (BC) to the Weather Research and Forecast (WRF) mesoscale model through simple perturbation tests. Our sensitivity analyses shows that the limited improvement of watershed scale precipitation forecast is credible. When only SST BC is changed, there is an uncertainty introduced because of artificial model state equilibrium and the nonlinear nature of the WRF model system. With the change of SST on the order of a fraction of a degree centigrade, we found that the part of random perturbation forecast response is saturated after 48 hours when it reaches to the order magnitude of the linear response. It is important to update the SST at a shorter time period, so that the independent excited nonlinear modes can cancel each other. The uncertainty in our SST configuration is quantitatively equivalent to adding to a spatially uncorrelated Guasian noise of zero mean and 0.05 degree of standard deviation to the SST. At this random noise perturbation magnitude, the ensemble average behaves well within a convergent range. It is also found that the sensitivity of forecast changes in response to SST changes. This is measured by the ratio of the spatial variability of mean of the ensemble perturbations over the spatial variability of the corresponding forecast. The ratio is about 10% for surface latent heat flux, 5 % for IWV, and less than 1% for surface pressure.

  10. Scavenging rate ecoassay: a potential indicator of estuary condition.

    Science.gov (United States)

    Porter, Augustine G; Scanes, Peter R

    2015-01-01

    Monitoring of estuary condition is essential due to the highly productive and often intensely impacted nature of these ecosystems. Assessment of the physico-chemical condition of estuaries is expensive and difficult due to naturally fluctuating water quality and biota. Assessing the vigour of ecosystem processes is an alternative method with potential to overcome much of the variability associated with physico-chemical measures. Indicators of estuary condition should have small spatial and temporal variability, have a predictable response to perturbation and be ecologically relevant. Here, we present tests of the first criterion, the spatio-temporal variability of a potential ecoassay measuring the rate of scavenging in estuaries. We hypothesised that the proposed scavenging ecoassay would not vary significantly among A) sites in an estuary, B) trips separated by weeks, or C) days in a trip. Because not all habitats are present in all estuaries, this test was undertaken in two habitats. When conducted over bare substrate there were occasional significant differences, but no discernible patterns, within levels of the experiment. When conducted over vegetated substrate, days within a trip did not vary significantly, but later trips experienced greater scavenging. This scavenging ecoassay shows potential as a tool for assessing the condition of estuarine ecosystems, and further exploration of this protocol is warranted by implementation in estuaries across a gradient of anthropogenic stress.

  11. Probabilistic Solar Wind Forecasting Using Large Ensembles of Near-Sun Conditions With a Simple One-Dimensional "Upwind" Scheme

    Science.gov (United States)

    Owens, Mathew J.; Riley, Pete

    2017-11-01

    Long lead-time space-weather forecasting requires accurate prediction of the near-Earth solar wind. The current state of the art uses a coronal model to extrapolate the observed photospheric magnetic field to the upper corona, where it is related to solar wind speed through empirical relations. These near-Sun solar wind and magnetic field conditions provide the inner boundary condition to three-dimensional numerical magnetohydrodynamic (MHD) models of the heliosphere out to 1 AU. This physics-based approach can capture dynamic processes within the solar wind, which affect the resulting conditions in near-Earth space. However, this deterministic approach lacks a quantification of forecast uncertainty. Here we describe a complementary method to exploit the near-Sun solar wind information produced by coronal models and provide a quantitative estimate of forecast uncertainty. By sampling the near-Sun solar wind speed at a range of latitudes about the sub-Earth point, we produce a large ensemble (N = 576) of time series at the base of the Sun-Earth line. Propagating these conditions to Earth by a three-dimensional MHD model would be computationally prohibitive; thus, a computationally efficient one-dimensional "upwind" scheme is used. The variance in the resulting near-Earth solar wind speed ensemble is shown to provide an accurate measure of the forecast uncertainty. Applying this technique over 1996-2016, the upwind ensemble is found to provide a more "actionable" forecast than a single deterministic forecast; potential economic value is increased for all operational scenarios, but particularly when false alarms are important (i.e., where the cost of taking mitigating action is relatively large).

  12. Probabilistic Solar Wind Forecasting Using Large Ensembles of Near-Sun Conditions With a Simple One-Dimensional "Upwind" Scheme.

    Science.gov (United States)

    Owens, Mathew J; Riley, Pete

    2017-11-01

    Long lead-time space-weather forecasting requires accurate prediction of the near-Earth solar wind. The current state of the art uses a coronal model to extrapolate the observed photospheric magnetic field to the upper corona, where it is related to solar wind speed through empirical relations. These near-Sun solar wind and magnetic field conditions provide the inner boundary condition to three-dimensional numerical magnetohydrodynamic (MHD) models of the heliosphere out to 1 AU. This physics-based approach can capture dynamic processes within the solar wind, which affect the resulting conditions in near-Earth space. However, this deterministic approach lacks a quantification of forecast uncertainty. Here we describe a complementary method to exploit the near-Sun solar wind information produced by coronal models and provide a quantitative estimate of forecast uncertainty. By sampling the near-Sun solar wind speed at a range of latitudes about the sub-Earth point, we produce a large ensemble (N = 576) of time series at the base of the Sun-Earth line. Propagating these conditions to Earth by a three-dimensional MHD model would be computationally prohibitive; thus, a computationally efficient one-dimensional "upwind" scheme is used. The variance in the resulting near-Earth solar wind speed ensemble is shown to provide an accurate measure of the forecast uncertainty. Applying this technique over 1996-2016, the upwind ensemble is found to provide a more "actionable" forecast than a single deterministic forecast; potential economic value is increased for all operational scenarios, but particularly when false alarms are important (i.e., where the cost of taking mitigating action is relatively large).

  13. Forecasting East Asian Indices Futures via a Novel Hybrid of Wavelet-PCA Denoising and Artificial Neural Network Models

    Science.gov (United States)

    2016-01-01

    The motivation behind this research is to innovatively combine new methods like wavelet, principal component analysis (PCA), and artificial neural network (ANN) approaches to analyze trade in today’s increasingly difficult and volatile financial futures markets. The main focus of this study is to facilitate forecasting by using an enhanced denoising process on market data, taken as a multivariate signal, in order to deduct the same noise from the open-high-low-close signal of a market. This research offers evidence on the predictive ability and the profitability of abnormal returns of a new hybrid forecasting model using Wavelet-PCA denoising and ANN (named WPCA-NN) on futures contracts of Hong Kong’s Hang Seng futures, Japan’s NIKKEI 225 futures, Singapore’s MSCI futures, South Korea’s KOSPI 200 futures, and Taiwan’s TAIEX futures from 2005 to 2014. Using a host of technical analysis indicators consisting of RSI, MACD, MACD Signal, Stochastic Fast %K, Stochastic Slow %K, Stochastic %D, and Ultimate Oscillator, empirical results show that the annual mean returns of WPCA-NN are more than the threshold buy-and-hold for the validation, test, and evaluation periods; this is inconsistent with the traditional random walk hypothesis, which insists that mechanical rules cannot outperform the threshold buy-and-hold. The findings, however, are consistent with literature that advocates technical analysis. PMID:27248692

  14. Impact of chemical lateral boundary conditions in a regional air quality forecast model on surface ozone predictions during stratospheric intrusions

    Science.gov (United States)

    Pendlebury, Diane; Gravel, Sylvie; Moran, Michael D.; Lupu, Alexandru

    2018-02-01

    A regional air quality forecast model, GEM-MACH, is used to examine the conditions under which a limited-area air quality model can accurately forecast near-surface ozone concentrations during stratospheric intrusions. Periods in 2010 and 2014 with known stratospheric intrusions over North America were modelled using four different ozone lateral boundary conditions obtained from a seasonal climatology, a dynamically-interpolated monthly climatology, global air quality forecasts, and global air quality reanalyses. It is shown that the mean bias and correlation in surface ozone over the course of a season can be improved by using time-varying ozone lateral boundary conditions, particularly through the correct assignment of stratospheric vs. tropospheric ozone along the western lateral boundary (for North America). Part of the improvement in surface ozone forecasts results from improvements in the characterization of near-surface ozone along the lateral boundaries that then directly impact surface locations near the boundaries. However, there is an additional benefit from the correct characterization of the location of the tropopause along the western lateral boundary such that the model can correctly simulate stratospheric intrusions and their associated exchange of ozone from stratosphere to troposphere. Over a three-month period in spring 2010, the mean bias was seen to improve by as much as 5 ppbv and the correlation by 0.1 depending on location, and on the form of the chemical lateral boundary condition.

  15. The TC-PSI indicator for forecasting the potential for market power in wholesale electricity markets

    International Nuclear Information System (INIS)

    Hesamzadeh, Mohammad R.; Biggar, Darryl R.; Hosseinzadeh, Nasser

    2011-01-01

    Wholesale electricity market regulators have long sought a simple, reliable, transparent indicator of the likely impact of wholesale market developments on the exercise of market power. Conventional indicators, such as the Pivotal Supplier Indicator (PSI) and the Residual Supply Index (RSI) cannot be extended to apply to meshed transmission networks, especially when generating companies hold a portfolio of generating units at different locations on the network. This paper proposes a generalisation of these standard measures termed the 'Transmission-Constrained Pivotal Supplier Indicator (TC-PSI)'. The TC-PSI of a generating company is defined as the maximum must-run generation for any subset of generating plant while allowing for strategic operation of other plant in the portfolio. We illustrate the use of the TC-PSI using a five-node model of the Australian NEM. - Highlights: → An indicator for assessing the pivotality of generating portfolios is proposed. → Transmission constraints are modelled explicitly in the proposed indicator. → Strategic behaviours of a generating portfolio in using its units are modelled. → This approach was illustrated using a 5-node model of the Australian NEM.

  16. Lichens as indicators of the ecological conditions of the habitat

    Energy Technology Data Exchange (ETDEWEB)

    Rydzak, J

    1968-01-01

    The susceptibility of lichens to changes in the urban environment make them good indicators of the intensity of air pollution. Studies covering a number of large and small towns, mostly in Europe and some over an extended time, explored the toxic influence of air pollution on 12 species on lichens. A comparison after 18 years with the lichen flora of Lublin, Poland found the lichen population impoverished. The toxic hypothesis, which blames increased coal consumption and automobile use, is inadequate to explain the condition. The drought hypothesis, which postulates that the occurrence and distribution of individual species is the result of a complex of numerous macro- and microclimatic, edaphic, geographical, historical, and other factors, gives a uniform view of the problem and stimulates investigations of the ecology of lichens in their natural habitat as well as in towns. 40 references, 12 figures, 3 tables.

  17. Groundwater vulnerability indices conditioned by Supervised Intelligence Committee Machine (SICM).

    Science.gov (United States)

    Nadiri, Ata Allah; Gharekhani, Maryam; Khatibi, Rahman; Sadeghfam, Sina; Moghaddam, Asghar Asghari

    2017-01-01

    This research presents a Supervised Intelligent Committee Machine (SICM) model to assess groundwater vulnerability indices of an aquifer. SICM uses Artificial Neural Networks (ANN) to overarch three Artificial Intelligence (AI) models: Support Vector Machine (SVM), Neuro-Fuzzy (NF) and Gene Expression Programming (GEP). Each model uses the DRASTIC index, the acronym of 7 geological, hydrological and hydrogeological parameters, which collectively represents intrinsic (or natural) vulnerability and gives a sense of contaminants, such as nitrate-N, penetrating aquifers from the surface. These models are trained to modify or condition their DRASTIC index values by measured nitrate-N concentration. The three AI-techniques often perform similarly but have differences as well and therefore SICM exploits the situation to improve the modeled values by producing a hybrid modeling results through selecting better performing SVM, NF and GEP components. The models of the study area at Ardabil aquifer show that the vulnerability indices by the DRASTIC framework produces sharp fronts but AI models smoothen the fronts and reflect a better correlation with observed nitrate values; SICM improves on the performances of three AI models and cope well with heterogeneity and uncertain parameters. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Biothermal conditions on Mt. Zlatibor based on thermophysiological indices

    Directory of Open Access Journals (Sweden)

    Pecelj Milica

    2017-01-01

    Full Text Available This paper presents part of the research in the field of human bioclimatology and refers to biothermal conditions in different geographical environments in Serbia: an urban area and a mountain of medium height. The goal of the paper was to show bioclimatic differences during the summer between the city of Belgrade (116 m a.s.l. and the mountain resort of Zlatibor (1498 m a.s.l.. The basic principle of bioclimatic analysis is the human heat balance between man and environment. This methodological approach is a combination of physiological and meteorological parameters that result in thermophysiological bioclimatic indices: heat load (HL in man and the Universal Thermal Climate Index (UTCI. For this analysis, weather data for July, as the warmest month, was obtained, using daily meteorological data for the decade from 2000 to 2010. Results for July indicate a considerable difference between the two abovementioned environments. HL in Belgrade was dominated by degrees of comfort “hot” and “extremely hot, with the highest value of 4.540, while for Zlatibor the dominant degree of comfort was “warm”. The UTCI in Belgrade has dominated by strong heat stress and moderate heat stress, compared to Zlatibor where the UTCI is dominated by moderate heat stress. In addition, a significant part of the monitored decade on Mt. Zlatibor was without heat stress, with the exception of 2006 and 2007, indicating favorable biothermal characteristics. Therefore, compared to Belgrade, with its considerably lower overall heat stress Zlatibor has the characteristics of a site with favorable bioclimatic qualities.

  19. Evaluating Weather Research and Forecasting Model Sensitivity to Land and Soil Conditions Representative of Karst Landscapes

    Science.gov (United States)

    Johnson, Christopher M.; Fan, Xingang; Mahmood, Rezaul; Groves, Chris; Polk, Jason S.; Yan, Jun

    2018-03-01

    Due to their particular physiographic, geomorphic, soil cover, and complex surface-subsurface hydrologic conditions, karst regions produce distinct land-atmosphere interactions. It has been found that floods and droughts over karst regions can be more pronounced than those in non-karst regions following a given rainfall event. Five convective weather events are simulated using the Weather Research and Forecasting model to explore the potential impacts of land-surface conditions on weather simulations over karst regions. Since no existing weather or climate model has the ability to represent karst landscapes, simulation experiments in this exploratory study consist of a control (default land-cover/soil types) and three land-surface conditions, including barren ground, forest, and sandy soils over the karst areas, which mimic certain karst characteristics. Results from sensitivity experiments are compared with the control simulation, as well as with the National Centers for Environmental Prediction multi-sensor precipitation analysis Stage-IV data, and near-surface atmospheric observations. Mesoscale features of surface energy partition, surface water and energy exchange, the resulting surface-air temperature and humidity, and low-level instability and convective energy are analyzed to investigate the potential land-surface impact on weather over karst regions. We conclude that: (1) barren ground used over karst regions has a pronounced effect on the overall simulation of precipitation. Barren ground provides the overall lowest root-mean-square errors and bias scores in precipitation over the peak-rain periods. Contingency table-based equitable threat and frequency bias scores suggest that the barren and forest experiments are more successful in simulating light to moderate rainfall. Variables dependent on local surface conditions show stronger contrasts between karst and non-karst regions than variables dominated by large-scale synoptic systems; (2) significant

  20. Predicting favorable conditions for early leaf spot of peanut using output from the Weather Research and Forecasting (WRF) model

    Science.gov (United States)

    Olatinwo, Rabiu O.; Prabha, Thara V.; Paz, Joel O.; Hoogenboom, Gerrit

    2012-03-01

    Early leaf spot of peanut ( Arachis hypogaea L.), a disease caused by Cercospora arachidicola S. Hori, is responsible for an annual crop loss of several million dollars in the southeastern United States alone. The development of early leaf spot on peanut and subsequent spread of the spores of C. arachidicola relies on favorable weather conditions. Accurate spatio-temporal weather information is crucial for monitoring the progression of favorable conditions and determining the potential threat of the disease. Therefore, the development of a prediction model for mitigating the risk of early leaf spot in peanut production is important. The specific objective of this study was to demonstrate the application of the high-resolution Weather Research and Forecasting (WRF) model for management of early leaf spot in peanut. We coupled high-resolution weather output of the WRF, i.e. relative humidity and temperature, with the Oklahoma peanut leaf spot advisory model in predicting favorable conditions for early leaf spot infection over Georgia in 2007. Results showed a more favorable infection condition in the southeastern coastline of Georgia where the infection threshold were met sooner compared to the southwestern and central part of Georgia where the disease risk was lower. A newly introduced infection threat index indicates that the leaf spot threat threshold was met sooner at Alma, GA, compared to Tifton and Cordele, GA. The short-term prediction of weather parameters and their use in the management of peanut diseases is a viable and promising technique, which could help growers make accurate management decisions, and lower disease impact through optimum timing of fungicide applications.

  1. Instability indices and forecasting thunderstorms: the case of 30 April 2009

    Directory of Open Access Journals (Sweden)

    S. Tajbakhsh

    2012-02-01

    Full Text Available In this paper, one meteorological case study for two Iranian airports are presented. Attempts have been made to study the predefined threshold amounts of some instability indices such as vertical velocity and relative humidity. Two important output variables from a numerical weather prediction model have been used to survey thunderstorms. The climatological state of thunder days in Iran has been determined to aid in choosing the airports for the case studies. The synoptic pattern, atmospheric thermodynamics and output from a numerical weather prediction model have been studied to evaluate the occurrence of storms and to verify the threshold instability indices that are based on Gordon and Albert (2000 and Miller (1972.

    Using data from the Statistics and Data Center of the Iran Meteorological Organization, 195 synoptic stations were used to study the climatological pattern of thunderstorm days in Iran during a 15-yr period (1991–2005. Synoptic weather maps and thermodynamic diagrams have been drawn using data from synoptic stations and radiosonde data. A 15-km resolution version of the WRF numerical model has been implemented for the Middle East region with the assistance of global data from University Corporation for Atmospheric Research (UCAR.

    The Tabriz airport weather station has been selected for further study due to its high frequency of thunderstorms (more than 35 thunderstorm days per year and the existence of an upper air station. Despite the fact that storms occur less often at the Tehran weather station, the station has been chosen as the second case study site due to its large amount of air traffic. Using these two case studies (Tehran at 00:00 UTC, 31 April 2009 and Tabriz at 12:00 UTC, 31 April 2009, the results of this research show that the threshold amounts of 30 °C for KI, −2 °C for LI and −3 °C for SI suggests the occurrence and non-occurrence of thunderstorms at the Tehran and Tabriz stations

  2. On Forecasting Macro-Economic Indicators with the Help of Finite-Difference Equations and Econometric Methods

    Directory of Open Access Journals (Sweden)

    Polshkov Yulian M.

    2013-11-01

    Full Text Available The article considers data on the gross domestic product, consumer expenditures, gross investments and volume of foreign trade for the national economy. It is assumed that time is a discrete variable with one year iteration. The article uses finite-difference equations. It considers models with a high degree of the regulatory function of the state with respect to the consumer market. The econometric component is based on the hypothesis that each of the above said macro-economic indicators for this year depends on the gross domestic product for the previous time periods. Such an assumption gives a possibility to engage the least-squares method for building up linear models of the pair regression. The article obtains the time series model, which allows building point and interval forecasts for the gross domestic product for the next year based on the values of the gross domestic product for the current and previous years. The article draws a conclusion that such forecasts could be considered justified at least in the short-term prospect. From the mathematical point of view the built model is a heterogeneous finite-difference equation of the second order with constant ratios. The article describes specific features of such equations. It illustrates graphically the analytical view of solutions of the finite-difference equation. This gives grounds to differentiate national economies as sustainable growth economies, one-sided, weak or being in the stage of successful re-formation. The article conducts comparison of the listed types with specific economies of modern states.

  3. Combining Diffusion Models and Macroeconomic Indicators with a Modified Genetic Programming Method: Implementation in Forecasting the Number of Mobile Telecommunications Subscribers in OECD Countries

    Directory of Open Access Journals (Sweden)

    Konstantinos Salpasaranis

    2014-01-01

    Full Text Available This paper proposes a modified Genetic Programming method for forecasting the mobile telecommunications subscribers’ population. The method constitutes an expansion of the hybrid Genetic Programming (hGP method improved by the introduction of diffusion models for technological forecasting purposes in the initial population, such as the Logistic, Gompertz, and Bass, as well as the Bi-Logistic and LogInLog. In addition, the aforementioned functions and models expand the function set of hGP. The application of the method in combination with macroeconomic indicators such as Gross Domestic Product per Capita (GDPpC and Consumer Prices Index (CPI leads to the creation of forecasting models and scenarios for medium- and long-term level of predictability. The forecasting module of the program has also been improved with the multi-levelled use of the statistical indices as fitness functions and model selection indices. The implementation of the modified-hGP in the datasets of mobile subscribers in the Organisation for Economic Cooperation and Development (OECD countries shows very satisfactory forecasting performance.

  4. Ecoclimatic indicators to study crop suitability in present and future climatic conditionsTIC CONDITIONS

    Science.gov (United States)

    Caubel, Julie; Garcia de Cortazar Atauri, Inaki; Huard, Frédéric; Launay, Marie; Ripoche, Dominique; Gouache, David; Bancal, Marie-Odile; Graux, Anne-Isabelle; De Noblet, Nathalie

    2013-04-01

    Climate change is expected to affect both regional and global food production through changes in overall agroclimatic conditions. It is therefore necessary to develop simple tools of crop suitability diagnosis in a given area so that stakeholders can envisage land use adaptations under climate change conditions. The most common way to investigate potential impacts of climate on the evolution of agrosystems is to make use of an array of agroclimatic indicators, which provide synthetic information derived from climatic variables and calculated within fixed periods (i.e. January first - 31th July). However, the information obtained during these periods does not enable to take account of the plant response to climate. In this work, we present some results of the research program ORACLE (Opportunities and Risks of Agrosystems & forests in response to CLimate, socio-economic and policy changEs in France (and Europe). We proposed a suite of relevant ecoclimatic indicators, based on temperature and rainfall, in order to evaluate crop suitability for both present and new climatic conditions. Ecoclimatic indicators are agroclimatic indicators (e.g., grain heat stress) calculated during specific phenological phases so as to take account of the plant response to climate (e.g., the grain filling period, flowering- harvest). These indicators are linked with the ecophysiological processes they characterize (for e.g., the grain filling). To represent this methodology, we studied the suitability of winter wheat in future climatic conditions through three distinct French sites, Toulouse, Dijon and Versailles. Indicators have been calculated using climatic data from 1950 to 2100 simulated by the global climate model ARPEGE forced by a greenhouse effect corresponding to the SRES A1B scenario. The Quantile-Quantile downscaling method was applied to obtain data for the three locations. Phenological stages (emergence, ear 1 cm, flowering, beginning of grain filling and harvest) have been

  5. Indicators of working conditions in the European Union

    OpenAIRE

    Dhondt, S.; Houtman, I.

    1997-01-01

    The goal of the report is to develop social indicators for the working environment in Europe on the basis of existing working environment statistics. Social indicators (chapter 2) contain information about the social situation in a country or international community. They give information about policy and about policy effects. It shows also what the level is of certain fundamental social needs develop over the time. Indicators on the working environment (chapter 3) give information about the ...

  6. Indicators of working conditions in the European Union

    NARCIS (Netherlands)

    Dhondt, S.; Houtman, I.

    1997-01-01

    The goal of the report is to develop social indicators for the working environment in Europe on the basis of existing working environment statistics. Social indicators (chapter 2) contain information about the social situation in a country or international community. They give information about

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

    Science.gov (United States)

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

    2014-12-01

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

  8. Forecasting of flowrate under rolling motion flow instability condition based on on-line sequential extreme learning machine

    International Nuclear Information System (INIS)

    Chen Hanying; Gao Puzhen; Tan Sichao; Tang Jiguo; Hou Xiaofan; Xu Huiqiang; Wu Xiangcheng

    2015-01-01

    The coupling of multiple thermal-hydraulic parameters can result in complex flow instability in natural circulation system under rolling motion. A real-time thermal-hydraulic condition prediction is helpful to the operation of systems in such condition. A single hidden layer feedforward neural networks algorithm named extreme learning machine (ELM) is considered as suitable method for this application because of its extremely fast training time, good accuracy and simplicity. However, traditional ELM assumes that all the training data are ready before the training process, while the training data is received sequentially in practical forecasting of flowrate. Therefore, this paper proposes a forecasting method for flowrate under rolling motion based on on-line sequential ELM (OS-ELM), which can learn the data one by one or chunk-by-chunk. The experiment results show that the OS-ELM method can achieve a better forecasting performance than basic ELM method and still keep the advantage of fast training and simplicity. (author)

  9. Identification of appropriate lags and temporal resolutions for low flow indicators in the River Rhine to forecast low flows with different lead times

    NARCIS (Netherlands)

    Demirel, M.C.; Booij, Martijn J.; Hoekstra, Arjen Ysbert

    2013-01-01

    The aim of this paper is to assess the relative importance of low flow indicators for the River Rhine and to identify their appropriate temporal lag and resolution. This is done in the context of low flow forecasting with lead times of 14 and 90 days. First, the Rhine basin is subdivided into seven

  10. Fate of indicator microorganisms under nutrient management plan conditions.

    Science.gov (United States)

    Bradford, Scott A; Segal, Eran

    2009-01-01

    Nutrient management plans (NMPs) for application of wastewater from concentrated animal feeding operations are designed to meet crop water and nutrient requirements, but implicitly assume that pathogenic microorganisms in the wastewater will be retained and die-off in the root zone. A NMP was implemented on a field plot to test this assumption by monitoring the fate of several fecal indicator microorganisms (Enterococcus, fecal coliforms, somatic coliphage, and total Escherichia coli). When well-water and wastewater were applied to meet measured evapotranspiration (ET), little advective transport of the indicator microorganisms occurred below the root zone and the remaining microorganisms rapidly died-off (within 1 mo). Additional experiments were conducted in the laboratory to better quantify microorganism transport and survival in the field soil. Batch survival experiments revealed much more rapid die-off rates for the bacterial indicator microorganisms in native than in sterilized soil, suggesting that biotic factors controlled survival. Saturated column experiments with packed field soil, demonstrated much greater transport potential for somatic coliphage than bacterial indicators (Enterococcus and total E. coli) and that the retention rates for the indicator microorganisms were not log-linear with depth. A worst case transport scenario of ponded infiltration on a large undistributed soil column from the field was also initiated and indicator microorganisms were not detected in the column outflow or in the soil at a depth of 65 cm. All of these observations support the hypothesis that a NMP at this site will protect groundwater supplies from microorganism contamination, especially when applied water and wastewater meet ET.

  11. Use of urine in snow to indicate condition of wolves

    Science.gov (United States)

    Mech, L.D.; Seal, U.S.; DelGiudice, G.D.

    1987-01-01

    Urine deposited in snow by wild gray wolves (Canis lupus) and by fed and fasted captive wolves was analyzed for urea nitrogen, calcium, sodium, potassium, and creatinine. Ratios of the elements with creatinine were considerably higher for fed than for fasted animals, and ratios for fed wolves compared favorably with ratios from wolf urine in snow along trails leading from kills. Thus, wolf urine in the snow can indicate whether wolves have fed recently, and a series of such urine collections from any given pack can indicate relative nutritional state.

  12. Indications, medical conditions and services related to gastrostomy ...

    African Journals Online (AJOL)

    gastrostomy, is used in paediatric patients when long-term enteral feeding is required.1 This form of ... Gastrostomy feeding may also be indicated in paediatric patients with structural abnormalities, or those who ... with cardiac defects may have difficulty with feeding endurance, resulting in poor weight gain and the need for.

  13. Hybrid support vector regression and autoregressive integrated moving average models improved by particle swarm optimization for property crime rates forecasting with economic indicators.

    Science.gov (United States)

    Alwee, Razana; Shamsuddin, Siti Mariyam Hj; Sallehuddin, Roselina

    2013-01-01

    Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.

  14. Hybrid Support Vector Regression and Autoregressive Integrated Moving Average Models Improved by Particle Swarm Optimization for Property Crime Rates Forecasting with Economic Indicators

    Directory of Open Access Journals (Sweden)

    Razana Alwee

    2013-01-01

    Full Text Available Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR and autoregressive integrated moving average (ARIMA to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.

  15. Stock Indices as Generalizing Indicators of the Stock Markets Condition in the European Union Countries

    Directory of Open Access Journals (Sweden)

    Shuba M. V.

    2015-03-01

    Full Text Available The aim of the article is to determine the degree of interdependence of stock markets in separate countries of the European Union, namely: France, Germany, Great Britain, Poland, the Czech Republic and Hungary on the basis of studying the changes in stock indexes, as well as determining the existence of tendencies of approximating the dynamics of the national stock index «PFTS Index» to the corresponding dynamics of stock indexes in surveyed countries. The article analyzes the dynamics of changes in stock indices in the UK (FTSE, Germany (DAX 30, France (CAC 40 and pan-European ones (EURO STOXX 50, as well as changes in stock indices in Poland (WIG 20, Czech Republic (PX, Hungary (BUX. Calculations of the coefficients of pair correlation between changes in stock indices in the studied countries have been performed. The calculation results show a substantial connection between the indicators of changes in stock indices and allow to make a conclusion that in the dynamics of stock indices of national stock markets of the studied EU countries some common trends are observed, moreover, in the behavior of the considered indices common local trends are noticed as well. The author calculated the coefficient of pair correlation between the indicators of changes in the national stock index «PFTS Index» and the stock indices of the «old» and «new» EU countries. The calculations showed that the PFTS Index does not demonstrate a high level of correlation with stock indices of the «old» EU countries and has a tendency of approaching the corresponding dynamics of stock indices of the «new» EU countries.

  16. Biothermal conditions on Mt. Zlatibor based on thermophysiological indices

    OpenAIRE

    Pecelj Milica; Đorđević Aleksandar; Pecelj Milovan R.; Pecelj-Purković Jelena; Filipović Dejan; Šećerov Velimir

    2017-01-01

    This paper presents part of the research in the field of human bioclimatology and refers to biothermal conditions in different geographical environments in Serbia: an urban area and a mountain of medium height. The goal of the paper was to show bioclimatic differences during the summer between the city of Belgrade (116 m a.s.l.) and the mountain resort of Zlatibor (1498 m a.s.l.). The basic principle of bioclimatic analysis is the human heat balance between...

  17. Deficiency indices and singular boundary conditions in quantum mechanics

    International Nuclear Information System (INIS)

    Bulla, W.

    1984-01-01

    We consider Schroedinger operators H in L 2 (Rsup(n)), n from IN, with countably infinitely many local singularities of the potential which are separated from each other by a positive distance. It is proved that due to locality each singularity yields a separate contribution to the deficiency index of H. In the special case where the singularities are pointlike and the potential exhibits certain symmetries near these points we give an explicit construction of self-adjoint boundary conditions

  18. Validation of Helicopter Gear Condition Indicators Using Seeded Fault Tests

    Science.gov (United States)

    Dempsey, Paula; Brandon, E. Bruce

    2013-01-01

    A "seeded fault test" in support of a rotorcraft condition based maintenance program (CBM), is an experiment in which a component is tested with a known fault while health monitoring data is collected. These tests are performed at operating conditions comparable to operating conditions the component would be exposed to while installed on the aircraft. Performance of seeded fault tests is one method used to provide evidence that a Health Usage Monitoring System (HUMS) can replace current maintenance practices required for aircraft airworthiness. Actual in-service experience of the HUMS detecting a component fault is another validation method. This paper will discuss a hybrid validation approach that combines in service-data with seeded fault tests. For this approach, existing in-service HUMS flight data from a naturally occurring component fault will be used to define a component seeded fault test. An example, using spiral bevel gears as the targeted component, will be presented. Since the U.S. Army has begun to develop standards for using seeded fault tests for HUMS validation, the hybrid approach will be mapped to the steps defined within their Aeronautical Design Standard Handbook for CBM. This paper will step through their defined processes, and identify additional steps that may be required when using component test rig fault tests to demonstrate helicopter CI performance. The discussion within this paper will provide the reader with a better appreciation for the challenges faced when defining a seeded fault test for HUMS validation.

  19. Extragalactic interstellar extinction curves: Indicators of local physical conditions

    Energy Technology Data Exchange (ETDEWEB)

    Cecchi-Pestellini, Cesare [INAF-Osservatorio Astronomico di Palermo, P.zza Parlamento 1, I-90134 Palermo (Italy); Viti, Serena; Williams, David A., E-mail: cecchi-pestellini@astropa.unipa.it, E-mail: sv@star.ucl.ac.uk, E-mail: daw@star.ucl.ac.uk [Department of Physics and Astronomy, University College London Gower Street, London WC1E 6BT (United Kingdom)

    2014-06-20

    Normalized interstellar extinction curves (ISECs) in the Milky Way and other galaxies show a variety of shapes. This variety is attributed to differences along different sight lines in the abundances of the several dust and gas components contributing to extinction. In this paper we propose that these abundance differences are not arbitrary but are a specific consequence of the physical conditions on those sight lines. If this proposal is correct, then it implies that ISECs contain information about physical conditions in the regions generating extinction. This may be particularly important for high redshift galaxies where information on the conditions may be difficult to obtain. We adopt a model of extinction carriers in which the solid and gaseous components are not immutable but respond time-dependently to the local physics. We validate this model by fitting extinction curves measured on sight lines in the Magellanic Clouds and obtained for the gamma-ray burst afterglow GRB 080605. We present results for this model as follows: (1) we show that computed ISECs are controlled by a small number of physical parameters, (2) we demonstrate the sensitivity of computed ISECs to these parameters, (3) we compute as examples ISECs for particular galaxy types, and (4) we note that different galaxy types have different shapes of ISEC.

  20. Using Satellite Data and Land Surface Models to Monitor and Forecast Drought Conditions in Africa and Middle East

    Science.gov (United States)

    Arsenault, K. R.; Shukla, S.; Getirana, A.; Peters-Lidard, C. D.; Kumar, S.; McNally, A.; Zaitchik, B. F.; Badr, H. S.; Funk, C. C.; Koster, R. D.; Narapusetty, B.; Jung, H. C.; Roningen, J. M.

    2017-12-01

    Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. In addition, these regions typically have sparse ground-based data networks, where sometimes remotely sensed observations may be the only data available. Long-term satellite records can help with determining historic and current drought conditions. In recent years, several new satellites have come on-line that monitor different hydrological variables, including soil moisture and terrestrial water storage. Though these recent data records may be considered too short for the use in identifying major droughts, they do provide additional information that can better characterize where water deficits may occur. We utilize recent satellite data records of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) and the European Space Agency's Advanced Scatterometer (ASCAT) soil moisture retrievals. Combining these records with land surface models (LSMs), NASA's Catchment and the Noah Multi-Physics (MP), is aimed at improving the land model states and initialization for seasonal drought forecasts. The LSMs' total runoff is routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics, which can provide an additional means of validation against in situ streamflow data. The NASA Land Information System (LIS) software framework drives the LSMs and HyMAP and also supports the capability to assimilate these satellite retrievals, such as soil moisture and TWS. The LSMs are driven for 30+ years with NASA's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS/UCSB Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) rainfall dataset. The seasonal water deficit forecasts are generated using downscaled and bias-corrected versions of NASA's Goddard Earth Observing System Model (GEOS-5), and NOAA's Climate Forecast System (CFSv2) forecasts

  1. Stable indications of relic gravitational waves in Wilkinson Microwave Anisotropy Probe data and forecasts for the Planck mission

    International Nuclear Information System (INIS)

    Zhao, W.; Baskaran, D.; Grishchuk, L. P.

    2009-01-01

    The relic gravitational waves are the cleanest probe of the violent times in the very early history of the Universe. They are expected to leave signatures in the observed cosmic microwave background anisotropies. We significantly improved our previous analysis [W. Zhao, D. Baskaran, and L. P. Grishchuk, Phys. Rev. D 79, 023002 (2009)] of the 5-year WMAP TT and TE data at lower multipoles l. This more general analysis returned essentially the same maximum likelihood result (unfortunately, surrounded by large remaining uncertainties): The relic gravitational waves are present and they are responsible for approximately 20% of the temperature quadrupole. We identify and discuss the reasons by which the contribution of gravitational waves can be overlooked in a data analysis. One of the reasons is a misleading reliance on data from very high multipoles l and another a too narrow understanding of the problem as the search for B modes of polarization, rather than the detection of relic gravitational waves with the help of all correlation functions. Our analysis of WMAP5 data has led to the identification of a whole family of models characterized by relatively high values of the likelihood function. Using the Fisher matrix formalism we formulated forecasts for Planck mission in the context of this family of models. We explore in detail various 'optimistic', 'pessimistic', and 'dream case' scenarios. We show that in some circumstances the B-mode detection may be very inconclusive, at the level of signal-to-noise ratio S/N=1.75, whereas a smarter data analysis can reveal the same gravitational wave signal at S/N=6.48. The final result is encouraging. Even under unfavorable conditions in terms of instrumental noises and foregrounds, the relic gravitational waves, if they are characterized by the maximum likelihood parameters that we found from WMAP5 data, will be detected by Planck at the level S/N=3.65.

  2. Drought Forecasting Using Adaptive Neuro-Fuzzy Inference Systems (ANFIS, Drought Time Series and Climate Indices For Next Coming Year, (Case Study: Zahedan

    Directory of Open Access Journals (Sweden)

    Hossein Hosseinpour Niknam

    2012-07-01

    Full Text Available In this research in order to forecast drought for the next coming year in Zahedan, using previous Standardized Precipitation Index (SPI data and 19 other climate indices were used.  For this purpose Adaptive Neuro-Fuzzy Inference System (ANFIS was applied to build the predicting model and SPI drought index for drought quantity.  At first calculating correlation approach for analysis between droughts and climate indices was used and the most suitable indices were selected. In the next stage drought prediction for period of 12 months was done. Different combinations among input variables in ANFIS models were entered. SPI drought index was the output of the model.  The results showed that just using time series like the previous year drought SPI index in forecasting the 12 month drought was effective. However among all climate indices that were used, Nino4 showed the most suitable results.

  3. Working environment conditions in rural areas according to psychosocial indices.

    Science.gov (United States)

    Thelin, A G

    1998-01-01

    The aim of this work was to study psychosocial working environment factors among farmers and other people living in rural areas. The study was carried out as a cross-section investigation. All persons visiting local occupational health service centres for a health check up have been asked to answer an inquiry which was based on the Karasek-Theorell questionnaire on job strain. Five extra items on worry about the future were added. The questionnaire was completed by over 3,800 persons. Three of four indices showed significant difference with respect to sex. Women experienced less stimulance at work, authority over work and had a greater fear of the future. Farmers had a significantly higher index for psychological demands, stimulance at work as well as authority over work than other occupational groups. The index for authority over work was very high in comparison with presented results for different occupations in other studies. With respect to worry about the future, the farmers had a significantly higher index than nearly all the other occupational groups. The low risk of coronary heart disease (CHD) among farmers reported in other studies can probably be related to good psychosocial working environment as measured by the indices in this study as well as other known life style factors.

  4. Economic Indicators of Condition and Tendencies of Serbian Economy

    Directory of Open Access Journals (Sweden)

    Zorica SREDOJEVIĆ

    2011-12-01

    Full Text Available Global economic crisis has, following financial crisis, hit real sector, and as after effect, large number, mostly developed countries in the world are in recession. Serbian industry is also influenced by global economic crisis. Outer debt is significantly and constantly increasing since beginning of transition process. Main cause to it is rather large disproportion between import and export. Trends in structure of outer debt indicate on notable decrease of national debt on account to private one, during whole transition period. On short term there is no significant risk for country on account of outer debt, but for long term elimination of this risk, it is necessary to considerably increase total export. Former policies should be linked to unconventional employment initiatives, as for new labour, as for redundant ones from restructuring economy branches. State has prominent role in transition process, by helping market exhibit its functions through physical and institutional infrastructure, as well trough public sector, removing most of the market obstacles, and stimulating technical-technological development and education.

  5. A Wind Forecasting System for Energy Application

    Science.gov (United States)

    Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

    2010-05-01

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

  6. Use of existing hydrographic infrastructure to forecast the environmental spawning conditions for Eastern Baltic cod.

    Science.gov (United States)

    von Dewitz, Burkhard; Tamm, Susanne; Höflich, Katharina; Voss, Rüdiger; Hinrichsen, Hans-Harald

    2018-01-01

    The semi-enclosed nature and estuarine characteristics, together with its strongly alternating bathymetry, make the Baltic Sea prone to much stronger interannual variations in the abiotic environment, than other spawning habitats of Atlantic cod (Gadus morhua). Processes determining salinity and oxygen conditions in the basins are influenced both by long term gradual climate change, e.g. global warming, but also by short-term meteorological variations and events. Specifically one main factor influencing cod spawning conditions, the advection of highly saline and well-oxygenated water masses from the North Sea, is observed in irregular frequencies and causes strong interannual variations in stock productivity. This study investigates the possibility to use the available hydrographic process knowledge to predict the annual spawning conditions for Eastern Baltic cod in its most important spawning ground, the Bornholm Basin, only by salinity measurements from a specific location in the western Baltic. Such a prediction could serve as an environmental early warning indicator to inform stock assessment and management. Here we used a hydrodynamic model to hindcast hydrographic property fields for the last 40+ years. High and significant correlations were found for months early in the year between the 33m salinity level in the Arkona Basin and the oxygen-dependent cod spawning environment in the Bornholm Basin. Direct prediction of the Eastern Baltic cod egg survival in the Bornholm Basin based on salinity values in the Arkona Basin at the 33 m depth level is shown to be possible for eggs spawned by mid-age and young females, which currently predominate the stock structure. We recommend to routinely perform short-term predictions of the Eastern Baltic cod spawning environment, in order to generate environmental information highly relevant for stock dynamics. Our statistical approach offers the opportunity to make best use of permanently existing infrastructure in the

  7. Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

    Science.gov (United States)

    Yang, Y.; Anderson, M. C.; Gao, F.; Wardlow, B.; Hain, C.; Otkin, J.; Sun, L.; Dulaney, W.

    2017-12-01

    In agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability and vegetation health and thus has been an integral part of many yield estimation efforts. The Evaporative Stress Index (ESI) describes temporal anomalies in a normalized evapotranspiration metric (fRET) as derived from satellite remote sensing and has demonstrated capacity to explain regional yield variability in water limited crop growing regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded. In this study we generated maps of ET, fRET, and ESI at high spatiotemporal resolution (30-m pixels, daily timesteps) using a multi-sensor data fusion method, integrating information from satellite platforms with good temporal coverage and other platforms that provide field-scale spatial detail. The study was conducted over the period 2010-2014, covering a region around Mead, Nebraska that includes both rainfed and irrigated crops. Correlations between ESI and measurements of corn yield are investigated at both the field and county level to assess the value of ESI as a yield forecasting tool. To examine the role of phenology in ESI-yield correlations, annual input fRET timeseries were aligned by both calendar day and by biophysically relevant dates (e.g. days since planting or emergence). Results demonstrate that mapping of fRET and ESI at 30-m has the advantage of being able to resolve different crop types with varying phenology. The study also suggests that incorporating phenological information significantly improves yield-correlations by accounting for effects of phenology such as variable planting date and emergence date. The yield-ESI relationship in this study well captures the inter-annual variability of yields

  8. Hydrological modelling for flood forecasting: Calibrating the post-fire initial conditions

    Science.gov (United States)

    Papathanasiou, C.; Makropoulos, C.; Mimikou, M.

    2015-10-01

    Floods and forest fires are two of the most devastating natural hazards with severe socioeconomic, environmental as well as aesthetic impacts on the affected areas. Traditionally, these hazards are examined from different perspectives and are thus investigated through different, independent systems, overlooking the fact that they are tightly interrelated phenomena. In fact, the same flood event is more severe, i.e. associated with increased runoff discharge and peak flow and decreased time to peak, if it occurs over a burnt area than that occurring over a land not affected by fire. Mediterranean periurban areas, where forests covered with flammable vegetation coexist with agricultural land and urban zones, are typical areas particularly prone to the combined impact of floods and forest fires. Hence, the accurate assessment and effective management of post-fire flood risk becomes an issue of priority. The research presented in this paper aims to develop a robust methodological framework, using state of art tools and modern technologies to support the estimation of the change in time of five representative hydrological parameters for post-fire conditions. The proposed methodology considers both longer- and short-term initial conditions in order to assess the dynamic evolution of the selected parameters. The research focuses on typical Mediterranean periurban areas that are subjected to both hazards and concludes with a set of equations that associate post-fire and pre-fire conditions for five Fire Severity (FS) classes and three soil moisture states. The methodology has been tested for several flood events on the Rafina catchment, a periurban catchment in Eastern Attica (Greece). In order to validate the methodology, simulated hydrographs were produced and compared against available observed data. Results indicate a close convergence of observed and simulated flows. The proposed methodology is particularly flexible and thus easily adaptable to catchments with similar

  9. The Advantages of Hybrid 4DEnVar in the Context of the Forecast Sensitivity to Initial Conditions

    Science.gov (United States)

    Song, Hyo-Jong; Shin, Seoleun; Ha, Ji-Hyun; Lim, Sujeong

    2017-11-01

    Hybrid four-dimensional ensemble variational data assimilation (hybrid 4DEnVar) is a prospective successor to three-dimensional variational data assimilation (3DVar) in operational weather prediction centers currently developing a new weather prediction model and those that do not operate adjoint models. In experiments using real observations, hybrid 4DEnVar improved Northern Hemisphere (NH; 20°N-90°N) 500 hPa geopotential height forecasts up to 5 days in a NH summer month compared to 3DVar, with statistical significance. This result is verified against ERA-Interim through a Monte Carlo test. By a regression analysis, the sensitivity of 5 day forecast is associated with the quality of the initial condition. The increased analysis skill for midtropospheric midlatitude temperature and subtropical moisture has the most apparent effect on forecast skill in the NH including a typhoon prediction case. Through attributing the analysis improvements by hybrid 4DEnVar separately to the ensemble background error covariance (BEC), its four-dimensional (4-D) extension, and climatological BEC, it is revealed that the ensemble BEC contributes to the subtropical moisture analysis, whereas the 4-D extension does to the midtropospheric midlatitude temperature. This result implies that hourly wind-mass correlation in 6 h analysis window is required to extract the potential of hybrid 4DEnVar for the midlatitude temperature analysis to the maximum. However, the temporal ensemble correlation, in hourly time scale, between moisture and another variable is invalid so that it could not work for improving the hybrid 4DEnVar analysis.

  10. Mechanistic Drifting Forecast Model for A Small Semi-Submersible Drifter Under Tide-Wind-Wave Conditions

    Science.gov (United States)

    Zhang, Wei-Na; Huang, Hui-ming; Wang, Yi-gang; Chen, Da-ke; Zhang, lin

    2018-03-01

    Understanding the drifting motion of a small semi-submersible drifter is of vital importance regarding monitoring surface currents and the floating pollutants in coastal regions. This work addresses this issue by establishing a mechanistic drifting forecast model based on kinetic analysis. Taking tide-wind-wave into consideration, the forecast model is validated against in situ drifting experiment in the Radial Sand Ridges. Model results show good performance with respect to the measured drifting features, characterized by migrating back and forth twice a day with daily downwind displacements. Trajectory models are used to evaluate the influence of the individual hydrodynamic forcing. The tidal current is the fundamental dynamic condition in the Radial Sand Ridges and has the greatest impact on the drifting distance. However, it loses its leading position in the field of the daily displacement of the used drifter. The simulations reveal that different hydrodynamic forces dominate the daily displacement of the used drifter at different wind scales. The wave-induced mass transport has the greatest influence on the daily displacement at Beaufort wind scale 5-6; while wind drag contributes mostly at wind scale 2-4.

  11. Robust Approaches to Forecasting

    OpenAIRE

    Jennifer Castle; David Hendry; Michael P. Clements

    2014-01-01

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

  12. Forecast salt regime unwatered mine reclaimed dump in unstable conditions in Western Donbass

    Directory of Open Access Journals (Sweden)

    Yevhrashkina H.P.

    2016-02-01

    Full Text Available On the based theory of physical-chemical hydrodynamic of porous media was executed prognosis salt rate no suppying with water mine dumps of minimum sense transhiration in conditions no established rate.

  13. Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird

    OpenAIRE

    Milenkaya, Olga; Catlin, Daniel H.; Legge, Sarah; Walters, Jeffrey R.

    2015-01-01

    Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch), a sedentary, tropical passerine, for reproductive success and survival ove...

  14. Probabilistic Solar Wind Forecasting Using Large Ensembles of Near‐Sun Conditions With a Simple One‐Dimensional “Upwind” Scheme

    Science.gov (United States)

    Riley, Pete

    2017-01-01

    Abstract Long lead‐time space‐weather forecasting requires accurate prediction of the near‐Earth solar wind. The current state of the art uses a coronal model to extrapolate the observed photospheric magnetic field to the upper corona, where it is related to solar wind speed through empirical relations. These near‐Sun solar wind and magnetic field conditions provide the inner boundary condition to three‐dimensional numerical magnetohydrodynamic (MHD) models of the heliosphere out to 1 AU. This physics‐based approach can capture dynamic processes within the solar wind, which affect the resulting conditions in near‐Earth space. However, this deterministic approach lacks a quantification of forecast uncertainty. Here we describe a complementary method to exploit the near‐Sun solar wind information produced by coronal models and provide a quantitative estimate of forecast uncertainty. By sampling the near‐Sun solar wind speed at a range of latitudes about the sub‐Earth point, we produce a large ensemble (N = 576) of time series at the base of the Sun‐Earth line. Propagating these conditions to Earth by a three‐dimensional MHD model would be computationally prohibitive; thus, a computationally efficient one‐dimensional “upwind” scheme is used. The variance in the resulting near‐Earth solar wind speed ensemble is shown to provide an accurate measure of the forecast uncertainty. Applying this technique over 1996–2016, the upwind ensemble is found to provide a more “actionable” forecast than a single deterministic forecast; potential economic value is increased for all operational scenarios, but particularly when false alarms are important (i.e., where the cost of taking mitigating action is relatively large). PMID:29398982

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

    Science.gov (United States)

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

    2017-10-01

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

  16. Impact of AIRS Thermodynamic Profile on Regional Weather Forecast

    Science.gov (United States)

    Chou, Shih-Hung; Zavodsky, Brad; Jedlovee, Gary

    2010-01-01

    Prudent assimilation of AIRS thermodynamic profiles and quality indicators can improve initial conditions for regional weather models. AIRS-enhanced analysis has warmer and moister PBL. Forecasts with AIRS profiles are generally closer to NAM analyses than CNTL. Assimilation of AIRS leads to an overall QPF improvement in 6-h accumulated precipitation forecasts. Including AIRS profiles in assimilation process enhances the moist instability and produces stronger updrafts and a better precipitation forecast than the CNTL run.

  17. INFORMATION-ANALYTICAL SYSTEM OF FORECAST VEGETATION FIRES IN NATURAL CONDITIONS

    Directory of Open Access Journals (Sweden)

    R. M. Kogan

    2015-01-01

    Full Text Available A system for spatial prediction for fire danger as function of weather and pyrological vegetation characteristics was constructed. The method of calculating the time conducted vegetable combustible materials in fire condition of each month of the season was suggested. Calculate the probability of fires and danger periods of plant formations in a monsoon climate. The geographic information system was developed, it was tested in the Middle Amur region in the Russian Far East.

  18. Forecasts of forest conditions in regions of the United States under future scenarios: a technical document supporting the Forest Service 2012 RPA Assessment

    Science.gov (United States)

    David N. Wear; Robert Huggett; Ruhong Li; Benjamin Perryman; Shan Liu

    2013-01-01

    The 626 million acres of forests in the conterminous United States represent significant reserves of biodiversity and terrestrial carbon and provide substantial flows of highly valued ecosystem services, including timber products, watershed protection benefits, and recreation. This report describes forecasts of forest conditions for the conterminous United States in...

  19. Forecasts of geomagnetic activities and HF radio propagation conditions made at Hiraiso/Japan

    Science.gov (United States)

    Marubashi, K.; Miyamoto, Y.; Kidokoro, T.; Ishii, T.

    1979-01-01

    The Hiraiso Branch of RRL prediction techniques are summarized separately for the 27 day recurrent storm and the flare-associated storm. The storm predictions are compared with the actual geomagnetic activities in two ways. The first one is the comparison on a day to day basis. In the second comparison, the accuracy of the storm predictions during 1965-1976 are evaluated. In addition to the storm prediction, short-term predictions of HF radio propagation conditions are conducted at Hiraiso. The HF propagation predictions are briefly described as an example of the applications of the magnetic storm prediction.

  20. Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird.

    Directory of Open Access Journals (Sweden)

    Olga Milenkaya

    Full Text Available Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch, a sedentary, tropical passerine, for reproductive success and survival over four breeding seasons, and sampled them for commonly used condition indices: mass adjusted for body size, muscle and fat scores, packed cell volume, hemoglobin concentration, total plasma protein, and heterophil to lymphocyte ratio. Our study population is well suited for this research because individuals forage in common areas and do not hold territories such that variation in condition between individuals is not confounded by differences in habitat quality. Furthermore, we controlled for factors that are known to impact condition indices in our study population (e.g., breeding stage such that we assessed individual condition relative to others in the same context. Condition indices that reflect energy reserves predicted both the probability of an individual fledging young and the number of young produced that survived to independence, but only during some years. Those that were relatively heavy for their body size produced about three times more independent young compared to light individuals. That energy reserves are a meaningful predictor of reproductive success in a sedentary passerine supports the idea that energy reserves are at least sometimes predictors of fitness. However, hematological indices failed to predict reproductive success and none of the indices predicted survival. Therefore, some but not all condition indices may be informative, but because we found that most indices did not predict any component of fitness, we question the ubiquitous

  1. Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird.

    Science.gov (United States)

    Milenkaya, Olga; Catlin, Daniel H; Legge, Sarah; Walters, Jeffrey R

    2015-01-01

    Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch), a sedentary, tropical passerine, for reproductive success and survival over four breeding seasons, and sampled them for commonly used condition indices: mass adjusted for body size, muscle and fat scores, packed cell volume, hemoglobin concentration, total plasma protein, and heterophil to lymphocyte ratio. Our study population is well suited for this research because individuals forage in common areas and do not hold territories such that variation in condition between individuals is not confounded by differences in habitat quality. Furthermore, we controlled for factors that are known to impact condition indices in our study population (e.g., breeding stage) such that we assessed individual condition relative to others in the same context. Condition indices that reflect energy reserves predicted both the probability of an individual fledging young and the number of young produced that survived to independence, but only during some years. Those that were relatively heavy for their body size produced about three times more independent young compared to light individuals. That energy reserves are a meaningful predictor of reproductive success in a sedentary passerine supports the idea that energy reserves are at least sometimes predictors of fitness. However, hematological indices failed to predict reproductive success and none of the indices predicted survival. Therefore, some but not all condition indices may be informative, but because we found that most indices did not predict any component of fitness, we question the ubiquitous interpretation of

  2. An ensemble prediction approach to weekly Dengue cases forecasting based on climatic and terrain conditions

    Directory of Open Access Journals (Sweden)

    Sougata Deb

    2017-11-01

    Full Text Available Introduction: Dengue fever has been one of the most concerning endemic diseases of recent times. Every year, 50-100 million people get infected by the dengue virus across the world. Historically, it has been most prevalent in Southeast Asia and the Pacific Islands. In recent years, frequent dengue epidemics have started occurring in Latin America as well. This study focused on assessing the impact of different short and long-term lagged climatic predictors on dengue cases. Additionally, it assessed the impact of building an ensemble model using multiple time series and regression models, in improving prediction accuracy. Materials and Methods: Experimental data were based on two Latin American cities, viz. San Juan (Puerto Rico and Iquitos (Peru. Due to weather and geographic differences, San Juan recorded higher dengue incidences than Iquitos. Using lagged cross-correlations, this study confirmed the impact of temperature and vegetation on the number of dengue cases for both cities, though in varied degrees and time lags. An ensemble of multiple predictive models using an elaborate set of derived predictors was built and validated. Results: The proposed ensemble prediction achieved a mean absolute error of 21.55, 4.26 points lower than the 25.81 obtained by a standard negative binomial model. Changes in climatic conditions and urbanization were found to be strong predictors as established empirically in other researches. Some of the predictors were new and informative, which have not been explored in any other relevant studies yet. Discussion and Conclusions: Two original contributions were made in this research. Firstly, a focused and extensive feature engineering aligned with the mosquito lifecycle. Secondly, a novel covariate pattern-matching based prediction approach using past time series trend of the predictor variables. Increased accuracy of the proposed model over the benchmark model proved the appropriateness of the analytical approach

  3. Towards leprosy elimination by 2020: forecasts of epidemiological indicators of leprosy in Corrientes, a province of northeastern Argentina that is a pioneer in leprosy elimination

    Directory of Open Access Journals (Sweden)

    Elisa Petri de Odriozola

    Full Text Available BACKGROUND Corrientes, a province of northeastern Argentina with endemic leprosy, has improved its epidemiological indicators, however, a study of the dynamics over time is lacking. OBJECTIVES We analysed data of 1308 leprosy patients between 1991 to 2014, and the forecast for 2020. METHODS Descriptive statistics and stepwise Bayesian model selection were performed. Forecasts were made using the median of 100,000 projections using the parameters calculated via Monte Carlo methods. RESULTS We found a decreasing number of new leprosy cases (-2.04 cases/year; this decrease is expected to continue by an estimated 20.28 +/- 10.00 cases by 2020, evidenced by a sustained decline in detection rate (from 11 to 2.9/100,000 inhabitants. Age groups that were most affected were 15-44 (40.13% and 45-64 (38.83% year olds. Multibacillary forms (MB predominated (70.35% and while gradually declining, between 10 and 30% developed disability grade 2 (DG2 (0.175 (0.110 - 0.337 DG2/MB cases, with a time delay between 0 to 15 years (median = 0. The proportion of MB clinic forms and DG2 increased and will continuously increase in the short term (0.036 +/- 0.018 logit (MB/total of cases. MAIN CONCLUSIONS Corrientes is on the way to eliminating leprosy by 2020, however the increased proportion of MB clinical forms and DG2 signals a warning for disease control efforts.

  4. Towards leprosy elimination by 2020: forecasts of epidemiological indicators of leprosy in Corrientes, a province of northeastern Argentina that is a pioneer in leprosy elimination.

    Science.gov (United States)

    Odriozola, Elisa Petri de; Quintana, Ana María; González, Victor; Pasetto, Roque Antonio; Utgés, María Eugenia; Bruzzone, Octavio Augusto; Arnaiz, María Rosa

    2017-06-01

    Corrientes, a province of northeastern Argentina with endemic leprosy, has improved its epidemiological indicators, however, a study of the dynamics over time is lacking. We analysed data of 1308 leprosy patients between 1991 to 2014, and the forecast for 2020. Descriptive statistics and stepwise Bayesian model selection were performed. Forecasts were made using the median of 100,000 projections using the parameters calculated via Monte Carlo methods. We found a decreasing number of new leprosy cases (-2.04 cases/year); this decrease is expected to continue by an estimated 20.28 +/- 10.00 cases by 2020, evidenced by a sustained decline in detection rate (from 11 to 2.9/100,000 inhabitants). Age groups that were most affected were 15-44 (40.13%) and 45-64 (38.83%) year olds. Multibacillary forms (MB) predominated (70.35%) and while gradually declining, between 10 and 30% developed disability grade 2 (DG2) (0.175 (0.110 - 0.337) DG2/MB cases), with a time delay between 0 to 15 years (median = 0). The proportion of MB clinic forms and DG2 increased and will continuously increase in the short term (0.036 +/- 0.018 logit (MB/total of cases). Corrientes is on the way to eliminating leprosy by 2020, however the increased proportion of MB clinical forms and DG2 signals a warning for disease control efforts.

  5. A combination of body condition measurements is more informative than conventional condition indices: temporal variation in body condition and corticosterone in brown tree snakes (Boiga irregularis).

    Science.gov (United States)

    Waye, Heather L; Mason, Robert T

    2008-02-01

    The body condition index is a common method for quantifying the energy reserves of individual animals. Because good body condition is necessary for reproduction in many species, body condition indices can indicate the potential reproductive output of a population. Body condition is related to glucocorticoid production, in that low body condition is correlated to high concentrations of corticosterone in reptiles. We compared the body condition index and plasma corticosterone levels of brown tree snakes on Guam in 2003 to those collected in 1992/1993 to determine whether that population still showed the chronic stress and poor condition apparent in the earlier study. We also examined the relationship between fat mass, body condition and plasma corticosterone concentrations as indicators of physiological condition of individuals in the population. Body condition was significantly higher in 2003 than in the earlier sample for mature male and female snakes, but not for juveniles. The significantly lower levels of corticosterone in all three groups in 2003 suggests that although juveniles did not have significantly improved energy stores they, along with the mature males and females, were no longer under chronic levels of stress. Although the wet season of 2002 was unusually rainy, low baseline levels of corticosterone measured in 2000 indicate that the improved body condition of snakes in 2003 is likely the result of long-term changes in prey populations rather than annual variation in response to environmental conditions.

  6. [Corrective effect of aromatherapy on indices of heart rate variability in students under exam stress conditions].

    Science.gov (United States)

    Abrahamyan, H T; Minasyan, S M

    2016-01-01

    There were investigated changes in indices of the activity of regulatory mechanisms of heart rhythm in student under exam stress conditions and the possibility of their correction with aid of aromatherapy. The examination stress was established to be accompanied by pronounced shifts of integral and spectral indices of heart rhythm in students, indicating to the activation of the sympathetic circuit of Autonomic Nervous System in conditions of examination stress. A positive, relaxation impact of the essential oil of orange on the investigated indices was also recorded. The latter is expressed by weakly pronounced changes or lack of them in data of integral and spectral heart rate indices in students from the experimental group, that indicates to the stabilizing effect of used ethereal oil on the psycho-physiological state of students in conditions of exam stress

  7. Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

    Science.gov (United States)

    In global agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability an...

  8. Examples of landscape indicators for assessing environmental conditions and problems in urban and suburban areas

    Science.gov (United States)

    Martin-Duque, J. F.; Godfrey, A.; Diez, A.; Cleaves, E.; Pedraza, J.; Sanz, M.A.; Carrasco, R.M.; Bodoque, J.; Brebbia, C.A.; Martin-Duque, J.F.; Wadhwa, L.C.

    2002-01-01

    Geo-indicators can help to assess environmental conditions in city urban and suburban areas. Those indicators should be meaningful for understanding environmental changes. From examples of Spanish and American cities, geo-indicators for assessing environmental conditions and changes in urban and suburban areas are proposed. The paper explore two types of geo-indicators. The first type presents general information that can be used to indicate the presence of a broad array of geologic conditions, either favouring or limiting various kinds of uses of the land. The second type of geo-indicator is the one most commonly used, and as a group most easily understood; these are site and problem specific and they are generally used after a problem is identified. Among them, watershed processes, seismicity and physiographic diversity are explained in more detail. A second dimension that is considered when discussing geo-indicators is the issue of scale. Broad scale investigations, covering extensive areas are only efficient at cataloguing general conditions common to much of the area or some outstanding feature within the area. This type of information is best used for policy type decisions. Detailed scale investigations can provide information about local conditions, but are not efficient at cataloguing vast areas. Information gathered at the detailed level is necessary for project design and construction.

  9. About some indicators of environment condition at the Semipalatinsk tests site

    International Nuclear Information System (INIS)

    Bakhtin, M.M.; Sejsebaev, A.T.

    2002-01-01

    The paper discusses the opportunity to select methods and indicators of the environment contamination. Using a water object - Chironomini - as an example, methods for assessment of ionizing radiation cytogenetic effects are considered. Indices of chromosomal aberrations generated in living organism cells serve as criteria of the environment ecological condition. (author)

  10. Cladocera from bottom deposits as an indicator of changes in climate and ecological conditions

    Science.gov (United States)

    Frolova, L. A.

    2018-01-01

    Diatoms, pollen, and remains of higher vegetation are used as indicator groups in paleoecological studies. Using certain groups of zoological indicators such as planktonic and benthic organisms (Ostracoda, Cladocera, Chironomidae) has recently become popular in paleolimnology and paleoecology. This study aims to estimate the possibilities, benefits, problems and prospects of Cladocera use in the composition of zoothanatocoenosis of lakes’ sediments as one of the biological indicators in paleoenvironmental studies and paleoreconstructions of abiotic conditions of the past.

  11. Activation analysis of several species of marine invertebrates as indicators of environmental conditions

    International Nuclear Information System (INIS)

    Fukushima, M.; Tamate, H.; Nakano, Y.

    2000-01-01

    Marine invertebrates are well known to accumulate trace metals from seawater, plankton, sea plants, and sediments. To test the usefulness of such organisms as a bio-indicator of environmental conditions, we have determined levels of trace elements in tissue of twelve species of marine invertebrates by photon and neutron activation analysis. Relatively higher concentration of elements were observed for Ni and Sn in mid-gut gland, for Cu and Zn in oyster tissues, for Se in swimming crabs, for Cu, Fe, and Se in gills of swimming crabs. Our results indicate that mid-gut gland of ear-shell will be useful as the indicator of environmental conditions. (author)

  12. Forecast Combinations

    OpenAIRE

    Timmermann, Allan G

    2005-01-01

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

  13. Forecast combinations

    OpenAIRE

    Aiolfi, Marco; Capistrán, Carlos; Timmermann, Allan

    2010-01-01

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

  14. A conditional extreme value theory approach in value-at-risk forecasting: Evidence from Southeastern Europe and USA market

    Directory of Open Access Journals (Sweden)

    Totić Selena

    2015-01-01

    Full Text Available As a consequence of the recent financial crisis, the adequacy of different Value-at-Risk (VaR methodologies was heavily questioned. Current practice in VaR assessment relies on modeling the whole distribution of returns. As an alternative, in this paper we model tail behavior of returns, and thus VaR, using conditional Extreme Value Theory (EVT, which combines EVT and GARCH methodology. Moreover, we examine the performance of conditional EVT with the daily returns of seven stock market indices, of which six are from Southeastern Europe (BelexLine, BET, BUX, CROBEX, SBITOP, SOFIX from the period of September 2004 - April 2013, and one from USA market (Standard&Poors 500 Index from the period January 1998 - April 2013. Backtesting of historical daily returns proves that conditional EVT model gives good predictions for all indices and for all confidence levels.

  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. Useful model organisms, indicators, or both? Ground beetles (Coleoptera, Carabidae) reflecting environmental conditions.

    Science.gov (United States)

    Koivula, Matti J

    2011-01-01

    Classic studies have successfully linked single-species abundances, life-history traits, assemblage structures and biomass of carabid beetles to past and present, human-caused environmental impacts and variation in 'natural' conditions. This evidence has led many to suggest carabids to function as 'indicators' - a term that bears multiple meanings. Here, a conservation-oriented definition for an indicator is used, carabid indicator potential from seven views is evaluated, and ways to proceed in indicator research are discussed. (1) Carabid species richness poorly indicates the richness and abundance of other taxa, which underlines the importance of using multiple taxa in environmental assessments. The ability of assemblage indices and specialist or functional-group abundances to reflect rare species and habitats should be examined in detail. (2) Experimental evidence suggests that carabids may potentially serve as keystone indicators. (3) Carabids are sensitive to human-altered abiotic conditions, such as pesticide use in agro-ecosystems and heavy metal contamination of soils. Carabids might thus reflect ecological sustainability and 'ecosystem health'. (4) Carabid assemblages host abundant species characteristic of particular habitat types or successional stages, which makes them promising dominance indicators. (5) Carabids reflect variation in 'natural' conditions, but vegetation and structural features are more commonly adopted as condition indicators. Carabids nevertheless provide yet another, equally accurate, view on the structure of the environment. (6) Carabids may function as early-warning signalers, as suggested by recent studies linking climate and carabid distributions. (7) Carabids reflect natural and human-caused disturbances and management, but the usefulness of these responses for conservation purposes requires further research. In summary, European carabids appear useful model organisms and possibly indicators because they are diverse

  17. Grey Forecast Rainfall with Flow Updating Algorithm for Real-Time Flood Forecasting

    Directory of Open Access Journals (Sweden)

    Jui-Yi Ho

    2015-04-01

    Full Text Available The dynamic relationship between watershed characteristics and rainfall-runoff has been widely studied in recent decades. Since watershed rainfall-runoff is a non-stationary process, most deterministic flood forecasting approaches are ineffective without the assistance of adaptive algorithms. The purpose of this paper is to propose an effective flow forecasting system that integrates a rainfall forecasting model, watershed runoff model, and real-time updating algorithm. This study adopted a grey rainfall forecasting technique, based on existing hourly rainfall data. A geomorphology-based runoff model can be used for simulating impacts of the changing geo-climatic conditions on the hydrologic response of unsteady and non-linear watershed system, and flow updating algorithm were combined to estimate watershed runoff according to measured flow data. The proposed flood forecasting system was applied to three watersheds; one in the United States and two in Northern Taiwan. Four sets of rainfall-runoff simulations were performed to test the accuracy of the proposed flow forecasting technique. The results indicated that the forecast and observed hydrographs are in good agreement for all three watersheds. The proposed flow forecasting system could assist authorities in minimizing loss of life and property during flood events.

  18. Large scale network management. Condition indicators for network stations, high voltage power conductions and cables

    International Nuclear Information System (INIS)

    Eggen, Arnt Ove; Rolfseng, Lars; Langdal, Bjoern Inge

    2006-02-01

    In the Strategic Institute Programme (SIP) 'Electricity Business enters e-business (eBee)' SINTEF Energy research has developed competency that can help the energy business employ ICT systems and computer technology in an improved way. Large scale network management is now a reality, and it is characterized by large entities with increasing demands on efficiency and quality. These are goals that can only be reached by using ICT systems and computer technology in a more clever way than what is the case today. At the same time it is important that knowledge held by experienced co-workers is consulted when formal rules for evaluations and decisions in ICT systems are developed. In this project an analytical concept for evaluation of networks based information in different ICT systems has been developed. The method estimating the indicators to describe different conditions in a network is general, and indicators can be made to fit different levels of decision and network levels, for example network station, transformer circuit, distribution network and regional network. Moreover, the indicators can contain information about technical aspects, economy and HSE. An indicator consists of an indicator name, an indicator value, and an indicator colour based on a traffic-light analogy to indicate a condition or a quality for the indicator. Values on one or more indicators give an impression of important conditions in the network, and make up the basis for knowing where more detailed evaluations have to be conducted before a final decision on for example maintenance or renewal is made. A prototype has been developed for testing the new method. The prototype has been developed in Excel, and especially designed for analysing transformer circuits in a distribution network. However, the method is a general one, and well suited for implementation in a commercial computer system (ml)

  19. Useful model organisms, indicators, or both? Ground beetles (Coleoptera, Carabidae reflecting environmental conditions

    Directory of Open Access Journals (Sweden)

    Matti Koivula

    2011-05-01

    Full Text Available Classic studies have successfully linked single-species abundances, life-history traits, assemblage structures and biomass of carabid beetles to past and present, human-caused environmental impacts and variation in ‘natural’ conditions. This evidence has led many to suggest carabids to function as ‘indicators’ − a term that bears multiple meanings. Here, a conservation-oriented definition for an indicator is used, carabid indicator potential from seven views is evaluated, and ways to proceed in indicator research are discussed. (1 Carabid species richness poorly indicates the richness and abundance of other taxa, which underlines the importance of using multiple taxa in environmental assessments. The ability of assemblage indices and specialist or functional-group abundances to reflect rare species and habitats should be examined in detail. (2 Experimental evidence suggests that carabids may potentially serve as keystone indicators. (3 Carabids are sensitive to human-altered abiotic conditions, such as pesticide use in agro-ecosystems and heavy metal contamination of soils. Carabids might thus reflect ecological sustainability and ‘ecosystem health’. (4 Carabid assemblages host abundant species characteristic of particular habitat types or successional stages, which makes them promising dominance indicators. (5 Carabids reflect variation in ‘natural’ conditions, but vegetation and structural features are more commonly adopted as condition indicators. Carabids nevertheless provide yet another, equally accurate, view on the structure of the environment. (6 Carabids may function as early-warning signalers, as suggested by recent studies linking climate and carabid distributions. (7 Carabids reflect natural and human-caused disturbances and management, but the usefulness of these responses for conservation purposes requires further research. In summary, European carabids appear useful model organisms and possibly indicators because

  20. Chironomidae (Diptera, Chironomidae) as biological indicators of water bodies ecological condition

    International Nuclear Information System (INIS)

    Bakhtin, M.M.; Sejsebaev, A.T.

    2002-01-01

    The paper presents data confirming that Chironomidae are good to be used as an indicative criterion when classifying lakes. It was found that their quantity and presence of certain species could serve as an index in assessment of water body ecological condition. Results of cytotaxonomic analysis helped to reveal the nature of Chironomini species diversity in STS water bodies. (author)

  1. Indicators of wetland condition for the prairie pothole region of the United States.

    Science.gov (United States)

    Guntenspergen, G R; Peterson, S A; Leibowitz, S G; Cowardin, L M

    2002-09-01

    We describe a study designed to evaluate the performance of wetland condition indicators of the Prairie Pothole Region (PPR) of the north central United States. Basin and landscape scale indicators were tested in 1992 and 1993 to determine their ability to discriminate between the influences of grassland dominated and cropland dominated landscapes in the PPR. Paired plots were selected from each of the major regions of the PPR. Among the landscape scale indicators tested, those most capable of distinguishing between the two landscapes were: 1) frequency of drained wetland basins. 2) total length of drainage ditch per plot, 3) amount of exposed soil in the upland subject to erosion, 4) indices of change in area of wetland covered by water, and 5) number of breeding duck pairs. Basin scale indicators including soil phosphorus concentrations and invertebrate taxa richness showed some promise: however, plant species richness was the only statistically significant basin scale indicator distinguishing grassland dominated from cropland dominated landscapes. Although our study found a number of promising candidate indicators, one of our conclusions is that basin scale indicators present a number of implementation problems. including: skill level requirements, site access denials, and recession of site access by landowners. Alternatively, we suggest that the use of landscape indicators based on remote sensing can be an effective means of assessing wetland integrity.

  2. Comparison of Test Stand and Helicopter Oil Cooler Bearing Condition Indicators

    Science.gov (United States)

    Dempsey, Paula J.; Branning, Jeremy; Wade, Damiel R.; Bolander, Nathan

    2010-01-01

    The focus of this paper was to compare the performance of HUMS condition indicators (CI) when detecting a bearing fault in a test stand or on a helicopter. This study compared data from two sources: first, CI data collected from accelerometers installed on two UH-60 Black Hawk helicopters when oil cooler bearing faults occurred, along with data from helicopters with no bearing faults; and second, CI data that was collected from ten cooler bearings, healthy and faulted, that were removed from fielded helicopters and installed in a test stand. A method using Receiver Operating Characteristic (ROC) curves to compare CI performance was demonstrated. Results indicated the bearing energy CI responded differently for the helicopter and the test stand. Future research is required if test stand data is to be used validate condition indicator performance on a helicopter.

  3. 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.

  4. 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

  5. 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.

  6. Toward evaluating the effect of climate change on investments in the water resources sector: insights from the forecast and analysis of hydrological indicators in developing countries

    International Nuclear Information System (INIS)

    Strzepek, Kenneth; Jacobsen, Michael; Boehlert, Brent; Neumann, James

    2013-01-01

    The World Bank has recently developed a method to evaluate the effects of climate change on six hydrological indicators across 8951 basins of the world. The indicators are designed for decision-makers and stakeholders to consider climate risk when planning water resources and related infrastructure investments. Analysis of these hydrological indicators shows that, on average, mean annual runoff will decline in southern Europe; most of Africa; and in southern North America and most of Central and South America. Mean reference crop water deficit, on the other hand, combines temperature and precipitation and is anticipated to increase in nearly all locations globally due to rising global temperatures, with the most dramatic increases projected to occur in southern Europe, southeastern Asia, and parts of South America. These results suggest overall guidance on which regions to focus water infrastructure solutions that could address future runoff flow uncertainty. Most important, we find that uncertainty in projections of mean annual runoff and high runoff events is higher in poorer countries, and increases over time. Uncertainty increases over time for all income categories, but basins in the lower and lower-middle income categories are forecast to experience dramatically higher increases in uncertainty relative to those in the upper-middle and upper income categories. The enhanced understanding of the uncertainty of climate projections for the water sector that this work provides strongly support the adoption of rigorous approaches to infrastructure design under uncertainty, as well as design that incorporates a high degree of flexibility, in response to both risk of damage and opportunity to exploit water supply ‘windfalls’ that might result, but would require smart infrastructure investments to manage to the greatest benefit. (letter)

  7. Toward evaluating the effect of climate change on investments in the water resources sector: insights from the forecast and analysis of hydrological indicators in developing countries

    Science.gov (United States)

    Strzepek, Kenneth; Jacobsen, Michael; Boehlert, Brent; Neumann, James

    2013-12-01

    The World Bank has recently developed a method to evaluate the effects of climate change on six hydrological indicators across 8951 basins of the world. The indicators are designed for decision-makers and stakeholders to consider climate risk when planning water resources and related infrastructure investments. Analysis of these hydrological indicators shows that, on average, mean annual runoff will decline in southern Europe; most of Africa; and in southern North America and most of Central and South America. Mean reference crop water deficit, on the other hand, combines temperature and precipitation and is anticipated to increase in nearly all locations globally due to rising global temperatures, with the most dramatic increases projected to occur in southern Europe, southeastern Asia, and parts of South America. These results suggest overall guidance on which regions to focus water infrastructure solutions that could address future runoff flow uncertainty. Most important, we find that uncertainty in projections of mean annual runoff and high runoff events is higher in poorer countries, and increases over time. Uncertainty increases over time for all income categories, but basins in the lower and lower-middle income categories are forecast to experience dramatically higher increases in uncertainty relative to those in the upper-middle and upper income categories. The enhanced understanding of the uncertainty of climate projections for the water sector that this work provides strongly support the adoption of rigorous approaches to infrastructure design under uncertainty, as well as design that incorporates a high degree of flexibility, in response to both risk of damage and opportunity to exploit water supply ‘windfalls’ that might result, but would require smart infrastructure investments to manage to the greatest benefit.

  8. Early forecasting of crop condition using an integrative remote sensing method for corn and soybeans in Iowa and Illinois, USA

    Science.gov (United States)

    Seo, Bumsuk; Lee, Jihye; Kang, Sinkyu

    2017-04-01

    The weather-related risks in crop production is not only crucial for farmers but also for market participants and policy makers since securing food supply is an important issue for society. While crop growth condition and phenology are essential information about such risks, the extensive observations on those are often non-existent in many parts of the world. In this study, we have developed a novel integrative approach to remotely sense crop growth condition and phenology at a large scale. For corn and soybeans in Iowa and Illinois of USA (2003-2014), we assessed crop growth condition and crop phenology by EO data and validated it against the United States Department of Agriculture (USDA) National Agriculture Statistics System (NASS) crop statistics. For growth condition, we used two distinguished approaches to acquire crop condition indicators: a process-based crop growth modelling and a satellite NDVI based method. Based on their pixel-wise historic distributions, we determined relative growth conditions and scaled-down to the state-level. For crop phenology, we calculated three crop phenology metrics [i.e., start of season (SOS), end of season (EOS), and peak of season (POS)] at the pixel level from MODIS 8-day Normalized Difference Vegetation Index (NDVI). The estimates were compared with the Crop Progress and Condition (CPC) data of NASS. For the condition, the state-level 10-day estimates showed a moderate agreement (RMSE 70%). Notably, the condition estimates corresponded to the severe soybeans disease in 2003 and the drought in 2012 for both crops. For the phenology, the average RMSE of the estimates was 8.6 day for the all three metrics. The average |ME| was smaller than 1.0 day after bias correction. The proposed method enables us to evaluate crop growth at any given period and place. Global climate changes are increasing the risk in agricultural production such as long-term drought. We hope that the presented remote sensing method for crop condition

  9. Role of Ocean Initial Conditions to Diminish Dry Bias in the Seasonal Prediction of Indian Summer Monsoon Rainfall: A Case Study Using Climate Forecast System

    Science.gov (United States)

    Koul, Vimal; Parekh, Anant; Srinivas, G.; Kakatkar, Rashmi; Chowdary, Jasti S.; Gnanaseelan, C.

    2018-03-01

    Coupled models tend to underestimate Indian summer monsoon (ISM) rainfall over most of the Indian subcontinent. Present study demonstrates that a part of dry bias is arising from the discrepancies in Oceanic Initial Conditions (OICs). Two hindcast experiments are carried out using Climate Forecast System (CFSv2) for summer monsoons of 2012-2014 in which two different OICs are utilized. With respect to first experiment (CTRL), second experiment (AcSAL) differs by two aspects: usage of high-resolution atmospheric forcing and assimilation of only ARGO observed temperature and salinity profiles for OICs. Assessment of OICs indicates that the quality of OICs is enhanced due to assimilation of actual salinity profiles. Analysis reveals that AcSAL experiment showed 10% reduction in the dry bias over the Indian land region during the ISM compared to CTRL. This improvement is consistently apparent in each month and is highest for June. The better representation of upper ocean thermal structure of tropical oceans at initial stage supports realistic upper ocean stability and mixing. Which in fact reduced the dominant cold bias over the ocean, feedback to air-sea interactions and land sea thermal contrast resulting better representation of monsoon circulation and moisture transport. This reduced bias of tropospheric moisture and temperature over the Indian land mass and also produced better tropospheric temperature gradient over land as well as ocean. These feedback processes reduced the dry bias in the ISM rainfall. Study concludes that initializing the coupled models with realistic OICs can reduce the underestimation of ISM rainfall prediction.

  10. How crucial is it to account for the antecedent moisture conditions in flood forecasting? Comparison of event-based and continuous approaches on 178 catchments

    Directory of Open Access Journals (Sweden)

    L. Berthet

    2009-06-01

    Full Text Available This paper compares event-based and continuous hydrological modelling approaches for real-time forecasting of river flows. Both approaches are compared using a lumped hydrologic model (whose structure includes a soil moisture accounting (SMA store and a routing store on a data set of 178 French catchments. The main focus of this study was to investigate the actual impact of soil moisture initial conditions on the performance of flood forecasting models and the possible compensations with updating techniques. The rainfall-runoff model assimilation technique we used does not impact the SMA component of the model but only its routing part. Tests were made by running the SMA store continuously or on event basis, everything else being equal. The results show that the continuous approach remains the reference to ensure good forecasting performances. We show, however, that the possibility to assimilate the last observed flow considerably reduces the differences in performance. Last, we present a robust alternative to initialize the SMA store where continuous approaches are impossible because of data availability problems.

  11. Genetics of body condition score as an indicator of dairy cattle fertility. A review

    OpenAIRE

    Bastin, C.; Gengler, N.

    2013-01-01

    Body condition score (BCS) is a subjective measure of the amount of metabolizable energy stored in a live animal. Change in BCS of dairy cows is considered to be an indicator of the extent and the duration of postpartum negative energy balance. Although change in BCS over lactation is lowly heritable, heritability estimates of level of BCS range from 0.20 to 0.50. Also, BCS tends to be more heritable in mid-lactation indicating that genetic differences are more related to how well cows recove...

  12. Ecoclimatic indicators to study crop suitability in present and future climatic conditions

    Science.gov (United States)

    Caubel, Julie; Garcia de Cortazar Atauri, Inaki; Huard, Frédéric; Launay, Marie; Ripoche, Dominique; Gouache, David; Bancal, Marie-Odile; Graux, Anne-Isabelle; De Noblet, Nathalie

    2013-04-01

    Climate change is expected to affect both regional and global food production through changes in overall agroclimatic conditions. It is therefore necessary to develop simple tools of crop suitability diagnosis in a given area so that stakeholders can envisage land use adaptations under climate change conditions. The most common way to investigate potential impacts of climate on the evolution of agrosystems is to make use of an array of agroclimatic indicators, which provide synthetic information derived from climatic variables and calculated within fixed periods (i.e. January first - 31th July). However, the information obtained during these periods does not enable to take account of the plant response to climate. In this work, we present some results of the research program ORACLE (Opportunities and Risks of Agrosystems & forests in response to CLimate, socio-economic and policy changEs in France (and Europe). We proposed a suite of relevant ecoclimatic indicators, based on temperature and rainfall, in order to evaluate crop suitability for both present and new climatic conditions. Ecoclimatic indicators are agroclimatic indicators (e.g., grain heat stress) calculated during specific phenological phases so as to take account of the plant response to climate (e.g., the grain filling period, flowering- harvest). These indicators are linked with the ecophysiological processes they characterize (for e.g., the grain filling). To represent this methodology, we studied the suitability of winter wheat in future climatic conditions through three distinct French sites, Toulouse, Dijon and Versailles. Indicators have been calculated using climatic data from 1950 to 2100 simulated by the global climate model ARPEGE forced by a greenhouse effect corresponding to the SRES A1B scenario. The Quantile-Quantile downscaling method was applied to obtain data for the three locations. Phenological stages (emergence, ear 1 cm, flowering, beginning of grain filling and harvest) have been

  13. Indicators for monitoring of safety operation and condition of nuclear power stations

    International Nuclear Information System (INIS)

    Manova, D.

    2001-01-01

    A common goal of all employees in the nuclear power field is safety operation of nuclear power stations. The evaluation and control of NPP safety operation are a part of the elements of safety management. The present report is related only to a part of the total assessment and control of the plant safety operation, namely - the indicator system for monitoring of Kozloduy NPP operation and condition. (author)

  14. Feather conditions and clinical scores as indicators of broilers welfare at the slaughterhouse.

    Science.gov (United States)

    Saraiva, S; Saraiva, C; Stilwell, G

    2016-08-01

    The objective of this study was to evaluate the welfare of 64 different broiler farms on the basis of feather conditions and clinical scores measures collected at the slaughterhouse. A 3-point scale (0, 1 or 2) was used to classify dirty feathers, footpad dermatitis and hock burns measures, and a 2-point scale (present or absent) was used to classify breast burns, breast blisters and breast ulcer measures. Flocks were allocated into three body weight (BW) classes (A, B, C): class A (light) ≥1.43 and ≤1.68kg, class B (medium) ≥1.69 and ≤1.93kg; class C (heavy) ≥1.94 and ≤2.41kg. The absence of hock burns was more common in class A, while mild hock burns was more common in class B flocks. Breast ulcer was observed in class C flocks. The association observed for mild hock burns, breast burns and severe footpad dermatitis can indicate a simultaneous occurrence of these painful lesions. Very dirty feathers and severe footpad dermatitis relationship suggest litter humidity to be the common underlying cause. In conclusion, it was shown that clinical indicators can be used at the slaughterhouse to identify welfare problems. In the studied flocks, footpad dermatitis, feather conditions and hock burns were the main restrictions for good welfare and should be considered significant welfare indicators of the on-farm rearing conditions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. The Evolving Role of Coliforms as Indicators of Unhygienic Processing Conditions in Dairy Foods

    Directory of Open Access Journals (Sweden)

    Nicole Helen Martin

    2016-09-01

    Full Text Available Testing for coliforms has a long history in the dairy industry and has helped to identify raw milk and dairy products that may have been exposed to unsanitary conditions. Coliform standards are included in a number of regulatory documents (e.g., the U. S. Food and Drug Administration’s Grade A Pasteurized Milk Ordinance. As a consequence, detection above a threshold of members of this method-defined, but diverse, group of bacteria can result in a wide range of regulatory outcomes. Coliforms are defined as aerobic or facultatively anaerobic, Gram negative, non-sporeforming rods capable of fermenting lactose to produce gas and acid within 48 hours at 32-35°C; 19 genera currently include at least some strains that represent coliforms. Most bacterial genera that comprise the coliform group (e.g., Escherichia, Klebsiella and Serratia are within the family Enterobacteriaceae, while at least one genus with strains recognized as coliforms, Aeromonas, is in the family Aeromonadaceae. The presence of coliforms has long been thought to indicate fecal contamination, however, recent discoveries regarding this diverse group of bacteria indicates that only a fraction are fecal in origin, while the majority are environmental contaminants. In the US dairy industry in particular, testing for coliforms as indicators of unsanitary conditions and post-processing contamination is widespread. While coliforms are easily and rapidly detected, and are not found in pasteurized dairy products that have not been exposed to post-processing contamination, advances in knowledge of bacterial populations most commonly associated with post-processing contamination in dairy foods has led to questions regarding the utility of coliforms as indicators of unsanitary conditions for dairy products. For example, Pseudomonas spp. frequently contaminate dairy products after pasteurization, yet they are not detected by coliform tests. This review will address the role that coliforms play

  16. The Evolving Role of Coliforms As Indicators of Unhygienic Processing Conditions in Dairy Foods

    Science.gov (United States)

    Martin, Nicole H.; Trmčić, Aljoša; Hsieh, Tsung-Han; Boor, Kathryn J.; Wiedmann, Martin

    2016-01-01

    Testing for coliforms has a long history in the dairy industry and has helped to identify raw milk and dairy products that may have been exposed to unsanitary conditions. Coliform standards are included in a number of regulatory documents (e.g., the U.S. Food and Drug Administration’s Grade “A” Pasteurized Milk Ordinance). As a consequence, detection above a threshold of members of this method-defined, but diverse, group of bacteria can result in a wide range of regulatory outcomes. Coliforms are defined as aerobic or facultatively anaerobic, Gram negative, non-sporeforming rods capable of fermenting lactose to produce gas and acid within 48 h at 32–35°C; 19 genera currently include at least some strains that represent coliforms. Most bacterial genera that comprise the coliform group (e.g., Escherichia, Klebsiella, and Serratia) are within the family Enterobacteriaceae, while at least one genus with strains recognized as coliforms, Aeromonas, is in the family Aeromonadaceae. The presence of coliforms has long been thought to indicate fecal contamination, however, recent discoveries regarding this diverse group of bacteria indicates that only a fraction are fecal in origin, while the majority are environmental contaminants. In the US dairy industry in particular, testing for coliforms as indicators of unsanitary conditions and post-processing contamination is widespread. While coliforms are easily and rapidly detected, and are not found in pasteurized dairy products that have not been exposed to post-processing contamination, advances in knowledge of bacterial populations most commonly associated with post-processing contamination in dairy foods has led to questions regarding the utility of coliforms as indicators of unsanitary conditions for dairy products. For example, Pseudomonas spp. frequently contaminate dairy products after pasteurization, yet they are not detected by coliform tests. This review will address the role that coliforms play in raw and

  17. Evaluation of HIV testing recommendations in specialty guidelines for the management of HIV indicator conditions

    DEFF Research Database (Denmark)

    Lord, E; Stockdale, A J; Malek, R

    2017-01-01

    OBJECTIVES: European guidelines recommend HIV testing for individuals presenting with indicator conditions (ICs) including AIDS-defining conditions (ADCs). The extent to which non-HIV specialty guidelines recommend HIV testing in ICs and ADCs is unknown. Our aim was to pilot a methodology in the UK...... are piloting methods to engage with guideline development groups to ensure that patients diagnosed with ICs/ADCs are tested for HIV. We then plan to apply our methodology in other European settings as part of the Optimising Testing and Linkage to Care for HIV across Europe (OptTEST) project....... to review specialty guidelines and ascertain if HIV was discussed and testing recommended. METHODS: UK and European HIV testing guidelines were reviewed to produce a list of 25 ADCs and 49 ICs. UK guidelines for these conditions were identified from searches of the websites of specialist societies...

  18. Use of erythrocyte indicators of health and condition in vertebrate ecophysiology: a review and appraisal.

    Science.gov (United States)

    Johnstone, Christopher P; Lill, Alan; Reina, Richard D

    2017-02-01

    We review evidence for and against the use of erythrocyte indicators of health status and condition, parasite infection level and physiological stress in free-living vertebrates. The use of indicators that are measured directly from the blood, such as haemoglobin concentration, haematocrit and erythrocyte sedimentation rate, and parameters that are calculated from multiple measured metrics, such as mean cell volume, mean cell haemoglobin content or mean cell haemoglobin concentration is evaluated. The evidence for or against the use of any given metric is equivocal when the relevant research is considered in total, although there is sometimes strong support for using a particular metric in a particular taxon. Possibly the usefulness of these metrics is taxon, environment or condition specific. Alternatively, in an uncontrolled environment where multiple factors are influencing a metric, its response to environmental change will sometimes, but not always, be predictable. We suggest that (i) researchers should validate a metricfres utility before use, (ii) multiple metrics should be used to construct an overall erythrocyte profile for an individual or population, (iii) there is a need for researchers to compile reference ranges for free-living species, and (iv) some metrics which are useful under controlled, clinical conditions may not have the same utility or applicability for free-living vertebrates. Erythrocyte metrics provide useful information about health and condition that can be meaningfully interpreted in free-living vertebrates, but their use requires careful forethought about confounding factors. © 2015 Cambridge Philosophical Society.

  19. [Differences in living conditions and health between cities: construction of a composite indicator].

    Science.gov (United States)

    Luiz, Olinda do Carmo; Heimann, Luiza Sterman; Boaretto, Roberta Cristina; Pacheco, Adriana Galvão; Pessoto, Umberto Catarino; Ibanhes, Lauro Cesar; Castro, Iracema Ester do Nascimento; Kayano, Jorge; Junqueira, Virginia; Rocha, Jucilene Leite da; Cortizo, Carlos Tato; Telesi Junior, Emílio

    2009-02-01

    To describe an index to identify inequities in living conditions and health and its relationship with health planning. Variables and indicators that would reflect demographic, economic, environment and education processes as well as supply and production of health services were applied for nondimensional scaling and clustering of 5,507 Brazilian municipalities. Data sources were the 2000 Census and the Brazilian Ministry of Health information systems. Z-score test statistic and cluster analysis were performed allowing to defining 4 groups of municipalities by living conditions. There was seen a polarization between the group with the best living conditions and health (Group 1) and the group with the worst living conditions (Group 4). Group 1 consisted of municipalities with larger populations while Group 4 comprised mainly the smallest municipalities. As for Brazilian macroregions, municipalities in Group 1 are clustered in the south and southeast and those in Group 4 are in the Northeast. The living conditions and health index comprises reality dimensions such as housing, environment and health which allows to identifying the most vulnerable municipalities and can provide input for setting priorities, and developing criteria for more equitable financing and resource allocation.

  20. Some implications of time series analysis for describing climatologic conditions and for forecasting. An illustrative case: Veracruz, Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Gay, C.; Estrada, F.; Conde, C. [Centro de Ciencias de la Atmosfera, Universidad Nacional Autonoma de Mexico, Mexico, D.F. (Mexico)]. E:mail: feporrua@atmosfera.unam.mx

    2007-04-15

    The common practice of using 30-year sub-samples of climatological data for describing past, present and future conditions has been widely applied, in many cases without considering the properties of the time series analyzed. This paper shows that this practice can lead to an inefficient use of the information contained in the data and to an inaccurate characterization of present, and especially future, climatological conditions because parameters are time and sub-sample size dependent. Furthermore, this approach can lead to the detection of spurious changes in distribution parameters. The time series analysis of observed monthly temperature in Veracruz, Mexico, is used to illustrate the fact that these techniques permit to make a better description of the mean and variability of the series, which in turn allows (depending on the class of process) to restrain uncertainty of forecasts, and therefore provides a better estimation of present and future risk of observing values outside a given coping range. Results presented in this paper show that, although a significant trend is found in the temperatures, giving possible evidence of observed climate change in the region, there is no evidence to support changes in the variability of the series and therefore there is neither observed evidence to support that monthly temperature variability will increase (or decrease) in the future. That is, if climate change is already occurring, it has manifested itself as a change-in-the-mean of these processes and has not affected other moments of their distributions (homogeneous non-stationary processes). The Magicc-Scengen, a software useful for constructing climate change scenarios, uses 20-year sub-samples to estimate future climate variability. For comparison purposes, possible future probability density functions are constructed following two different approaches: one, using solely the Magicc-Scengen output, and another one using a combination of this information and the time

  1. Tochilinite: A Sensitive Indicator of Alteration Conditions on the CM Asteroidal Parent Body

    Science.gov (United States)

    Browning, L. B.; Bourcier, W. L.

    1996-03-01

    Each CM chondrite experienced a different degree of aqueous alteration. As a group, then, these meteorites preserve tangible evidence of asteroidal reactions that were interrupted at many different stages of completion. Geochemical modeling of CM reaction progress should elucidate the nature of the accreted CM materials and the specific types of asteroidal processes and conditions that subsequently influenced them. However, most of the minerals in CM chondrites are stable under a wide range of environmental conditions, which hinders efforts to capitalize on the diverse degree of CM alteration. Petrologic evidence suggests that Fe-rich tochilinite, the widespread mineralic component of CM chondrites previously referred to as "poorly characterized phase (PCP)", may be the most sensitive indicator of the conditions of CM alteration. This possibility has not previously been explored because thermodynamic data for tochilinite are lacking. We have estimated the thermodynamic properties of tochilinite from mixing equations and then calculated its stability limits with associated non-silicate phases as a function of PS2, PO2, and PCO2. The resultant phase relations : a) are consistent with mineral association in CM chondrites, b) indicate that the CM fluids were S-depleted and extremely reducing, c) imply the possibility of H2 gas seeps on the CM parent body, and d) suggest that the alteration of CM materials occurred at significant asteroidal depths.

  2. Load forecasting

    International Nuclear Information System (INIS)

    Mak, H.

    1995-01-01

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

  3. Key risk indicators for accident assessment conditioned on pre-crash vehicle trajectory.

    Science.gov (United States)

    Shi, X; Wong, Y D; Li, M Z F; Chai, C

    2018-08-01

    Accident events are generally unexpected and occur rarely. Pre-accident risk assessment by surrogate indicators is an effective way to identify risk levels and thus boost accident prediction. Herein, the concept of Key Risk Indicator (KRI) is proposed, which assesses risk exposures using hybrid indicators. Seven metrics are shortlisted as the basic indicators in KRI, with evaluation in terms of risk behaviour, risk avoidance, and risk margin. A typical real-world chain-collision accident and its antecedent (pre-crash) road traffic movements are retrieved from surveillance video footage, and a grid remapping method is proposed for data extraction and coordinates transformation. To investigate the feasibility of each indicator in risk assessment, a temporal-spatial case-control is designed. By comparison, Time Integrated Time-to-collision (TIT) performs better in identifying pre-accident risk conditions; while Crash Potential Index (CPI) is helpful in further picking out the severest ones (the near-accident). Based on TIT and CPI, the expressions of KRIs are developed, which enable us to evaluate risk severity with three levels, as well as the likelihood. KRI-based risk assessment also reveals predictive insights about a potential accident, including at-risk vehicles, locations and time. Furthermore, straightforward thresholds are defined flexibly in KRIs, since the impact of different threshold values is found not to be very critical. For better validation, another independent real-world accident sample is examined, and the two results are in close agreement. Hierarchical indicators such as KRIs offer new insights about pre-accident risk exposures, which is helpful for accident assessment and prediction. Copyright © 2018 Elsevier Ltd. All rights reserved.

  4. Using fish larvae as indicators of estuarine ecosystem condition in Rio de Janeiro State, Brazil

    Directory of Open Access Journals (Sweden)

    Regis Vinícius Souza Santos

    2015-11-01

    Full Text Available Estuaries enhance growth and maximize the survivorship of initial development stages of fish species, functioning as nursery grounds for many species. However, estuaries throughout the world host a wide variety of human activities, and fish communities can be severely impacted. Protection of aquatic biodiversity and proper management of these coastal systems require robust tools to assess habitat integrity and ecological quality status. Thus, the present study investigated the use of fish larvae as indicators of estuarine ecosystem condition in Brazil, testing the hypothesis that estuaries with different human impacts and environmental conditions carry distinct larval fish assemblages. For this, four estuaries were analysed with: similar environmental conditions (the same water mass surveyed, similar pool of species (the same geographical region and no seasonal influences (different periods analysed separately. Surveys were conducted in Macaé, São João, Bracuí and Perequê-Açu estuaries located in Rio de Janeiro State, Brazil. Sampling surveys were conducted every two months between May 2013 and March 2015. All samples were taken in the estuary middle region (salinity 15-25 during nightly ebb tides. At each estuary, ichthyoplankton subsurface tows were perfomed using a Bongo net. Water parameters were measured by a multiparameter probe and surface water samples collected for further analytical analyses. Fish larvae were identified and species were assigned into functional guilds. The water conditions were assessed based on water temperature, pH, chlorophyll a, dissolved oxygen and total particulate matter. Faecal coliforms, nutrient load (NO3, NO2, NH3, PO4, SiO3 and presence/absence of dams, dredging and mangroves were used as anthropogenic pressure descriptors. The species composition and ecological guilds of Macaé and Perequê-Açu differed significantly of São João and Bracuí, separating the impacted versus non-impacted estuaries

  5. A national-scale seasonal hydrological forecast system: development and evaluation over Britain

    Directory of Open Access Journals (Sweden)

    V. A. Bell

    2017-09-01

    Full Text Available Skilful winter seasonal predictions for the North Atlantic circulation and northern Europe have now been demonstrated and the potential for seasonal hydrological forecasting in the UK is now being explored. One of the techniques being used combines seasonal rainfall forecasts provided by operational weather forecast systems with hydrological modelling tools to provide estimates of seasonal mean river flows up to a few months ahead. The work presented here shows how spatial information contained in a distributed hydrological model typically requiring high-resolution (daily or better rainfall data can be used to provide an initial condition for a much simpler forecast model tailored to use low-resolution monthly rainfall forecasts. Rainfall forecasts (hindcasts from the GloSea5 model (1996 to 2009 are used to provide the first assessment of skill in these national-scale flow forecasts. The skill in the combined modelling system is assessed for different seasons and regions of Britain, and compared to what might be achieved using other approaches such as use of an ensemble of historical rainfall in a hydrological model, or a simple flow persistence forecast. The analysis indicates that only limited forecast skill is achievable for Spring and Summer seasonal hydrological forecasts; however, Autumn and Winter flows can be reasonably well forecast using (ensemble mean rainfall forecasts based on either GloSea5 forecasts or historical rainfall (the preferred type of forecast depends on the region. Flow forecasts using ensemble mean GloSea5 rainfall perform most consistently well across Britain, and provide the most skilful forecasts overall at the 3-month lead time. Much of the skill (64 % in the 1-month ahead seasonal flow forecasts can be attributed to the hydrological initial condition (particularly in regions with a significant groundwater contribution to flows, whereas for the 3-month ahead lead time, GloSea5 forecasts account for  ∼ 70

  6. Using remotely sensed vegetation indices to model ecological pasture conditions in Kara-Unkur watershed, Kyrgyzstan

    Science.gov (United States)

    Masselink, Loes; Baartman, Jantiene; Verbesselt, Jan; Borchardt, Peter

    2017-04-01

    Kyrgyzstan has a long history of nomadic lifestyle in which pastures play an important role. However, currently the pastures are subject to severe grazing-induced degradation. Deteriorating levels of biomass, palatability and biodiversity reduce the pastures' productivity. To counter this and introduce sustainable pasture management, up-to-date information regarding the ecological conditions of the pastures is essential. This research aimed to investigate the potential of a remote sensing-based methodology to detect changing ecological pasture conditions in the Kara-Unkur watershed, Kyrgyzstan. The relations between Vegetation Indices (VIs) from Landsat ETM+ images and biomass, palatability and species richness field data were investigated. Both simple and multiple linear regression (MLR) analyses, including terrain attributes, were applied. Subsequently, trends of these three pasture conditions were mapped using time series analysis. The results show that biomass is most accurately estimated by a model including the Modified Soil Adjusted Vegetation Index (MSAVI) and a slope factor (R2 = 0.65, F = 0.0006). Regarding palatability, a model including the Enhanced Vegetation Index (EVI), Northness Index, Near Infrared (NIR) and Red band was most accurate (R2 = 0.61, F = 0.0160). Species richness was most accurately estimated by a model including Topographic Wetness Index (TWI), Eastness Index and estimated biomass (R2 = 0.81, F = 0.0028). Subsequent trend analyses of all three estimated ecological pasture conditions presented very similar trend patterns. Despite the need for a more robust validation, this study confirms the high potential of a remote sensing based methodology to detect changing ecological pasture conditions.

  7. Are glendonites reliable indicators of cold conditions? Evidence from the Lower Cretaceous of Spitsbergen

    Science.gov (United States)

    Vickers, Madeleine; Price, Gregory; Watkinson, Matthew; Jerrett, Rhodri

    2017-04-01

    Glendonites are pseudomorphs after the mineral ikaite, and have been found in marine sediments throughout geological time. Ikaite is a metastable, hydrated form of calcium carbonate, which is only stable under specific conditions: between -2 and +5 °C, and with high alkalinity and phosphate concentrations. Glendonites are often associated with cold climates due to the strong temperature control on ikaite growth, and the coincidence in the geological record with episodes of global cooling. Glendonites are found in the Lower Cretaceous succession in Spitsbergen. During the Early Cretaceous, Spitsbergen was at a palaeolatitude of 60°N, and was part of a shallow epicontinental sea that formed during the Mesozoic as Atlantic rifting propagated northwards. Though the Early Cretaceous was generally characterised by greenhouse climate conditions, episodic cold snaps occurred during the Valanginian (the "Weissert Event") and during Aptian-Albian. Using high resolution carbon-isotope stratigraphy, we show that the first occurrences of glendonites are in the upper Lower Hauterivian and in the very upper Upper Hauterivian, stratigraphically higher than the Valanginian cooling event. Glendonites are also found in horizons in the Upper Aptian, coincident with the Aptian-Albian cold snap. Petrological analysis of the glendonite structure reveals differences between the Hauterivian and Aptian glendonites, with evidence for multiple diagenetic phases of growth in the Hauterivian glendonites, suggesting oscillating chemical conditions. This evidence suggests that local environmental conditions may have a stronger control on glendonite formation and preservation than global climate. We present a new model for ikaite growth and slow transformation to glendonite in marine sediments, which points to a more complex suite of diagenetic transformations than previously modelled. Furthermore, we critically assess whether such pseudomorphs after marine sedimentary ikaite may be indicators

  8. MANAGEMENT SYSTEM OF THE ORGANIZATION PERFORMANCE INDICATORS IN THE CONDITIONS OF BUSINESS PROCESSES REALIZATION

    Directory of Open Access Journals (Sweden)

    Aleksandr Vladimirovich Gagarinskii

    2016-12-01

    Full Text Available This article discusses the problem of the effective work of managers of industrial enterprises, which is the basis of economic development in modern Russia. The authors suggest that the management of the system of performance indicators in managers in the conditions of realization of various business processes can reduce the risk of crises in the enterprise, and improve the efficiency of labour management and productivity in the company in a whole. According to the authors, improving the efficiency of management in the conditions of implementation of the various business processes of industrial enterprises is an integral element of the overall strategic development of the company. The article presents the results of work performance assessment of managers in the implementation of business process management. In this article there is developed performance business process management on the example of the metal cutting enterprise management levels: the corporate level, the first operational level, the second operational level, and the line level. For these indicators the performers are defined and criteria are given.

  9. Genetics of body condition score as an indicator of dairy cattle fertility. A review

    Directory of Open Access Journals (Sweden)

    Bastin, C.

    2013-01-01

    Full Text Available Body condition score (BCS is a subjective measure of the amount of metabolizable energy stored in a live animal. Change in BCS of dairy cows is considered to be an indicator of the extent and the duration of postpartum negative energy balance. Although change in BCS over lactation is lowly heritable, heritability estimates of level of BCS range from 0.20 to 0.50. Also, BCS tends to be more heritable in mid-lactation indicating that genetic differences are more related to how well cows recover from the negative energy balance state. BCS measurements are generally highly correlated within and between lactations. Genetic correlations with BCS are unfavorable for milk, fat, and protein yield, suggesting that genetically superior producers tend to have lower BCS, especially during the lactation. Genetic correlations are generally moderate and favorable with fertility indicating that cows with higher levels of BCS would have a greater chance to conceive after insemination and fewer number of days when not pregnant. Because direct selection to improve fertility might be complicated by several factors, selection for higher levels of BCS, especially in mid-lactation, appears to be a good option to indirectly improve fertility in dairy cows.

  10. The Effect of Body Weight on Heat Strain Indices in Hot and Dry Climatic Conditions

    Directory of Open Access Journals (Sweden)

    Habibi

    2016-03-01

    Full Text Available Background Being overweight is a characteristic that may influence a person’s heat exchange. Objectives The purpose of this study was to assess the effect of body weight on heat strain indices in hot and dry climatic conditions. Materials and Methods This study was completed with a sample of 30 participants with normal weights, as well as 25 participants who were overweight. The participants were physically inactive for a period of 120 minutes in a climatic chamber with hot and dry conditions (22 - 32°C and with 40% relative humidity (RH.The physiological strain index (PSI and heat strain score index (HSSI questionnaires were used. Simultaneous measurements were completed during heat exposure for periods of five minutes. The resting periods acted as the initial measurements for 15 minutes. Results In both groups, oral temperature, heart rate, and thermal perceptual responses increased during heat exposure. The means and standard deviations of heart rate and oral temperature were gathered when participants were in hot and dry climatic conditions and were not physically active. The heart rates and oral temperatures were 79.21 ± 5.93 bpm and 36.70 ± 0.45°C, respectively, for those with normal weights. For overweight individuals, the measurements for heart rate and oral temperature reached 82.21 ± 8.9 bpm and 37.84 ± 0.37°C, respectively. Conclusions The results showed that, compared to participants with normal weights, physiological and thermal perceptual responses were higher in overweight participants. Therefore, overweight individuals should avoid hot/dry weather conditions to decrease the amount of heat strain.

  11. High-Resolution Hydrological Sub-Seasonal Forecasting for Water Resources Management Over Europe

    Science.gov (United States)

    Wood, E. F.; Wanders, N.; Pan, M.; Sheffield, J.; Samaniego, L. E.; Thober, S.; Kumar, R.; Prudhomme, C.; Houghton-Carr, H.

    2017-12-01

    For decision-making at the sub-seasonal and seasonal time scale, hydrological forecasts with a high temporal and spatial resolution are required by water managers. So far such forecasts have been unavailable due to 1) lack of availability of meteorological seasonal forecasts, 2) coarse temporal resolution of meteorological seasonal forecasts, requiring temporal downscaling, 3) lack of consistency between observations and seasonal forecasts, requiring bias-correction. The EDgE (End-to-end Demonstrator for improved decision making in the water sector in Europe) project commissioned by the ECMWF (C3S) created a unique dataset of hydrological seasonal forecasts derived from four global climate models (CanCM4, FLOR-B01, ECMF, LFPW) in combination with four global hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP), resulting in 208 forecasts for any given day. The forecasts provide a daily temporal and 5-km spatial resolution, and are bias corrected against E-OBS meteorological observations. The forecasts are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs), created in collaboration with the end-user community of the EDgE project (e.g. the percentage of ensemble realizations above the 10th percentile of monthly river flow, or below the 90th). Results show skillful forecasts for discharge from 3 months to 6 months (latter for N Europe due to snow); for soil moisture up to three months due precipitation forecast skill and short initial condition memory; and for groundwater greater than 6 months (lowest skill in western Europe.) The SCIIs are effective in communicating both forecast skill and uncertainty. Overall the new system provides an unprecedented ensemble for seasonal forecasts with significant skill over Europe to support water management. The consistency in both the GCM forecasts and the LSM parameterization ensures a stable and reliable forecast framework and methodology, even if additional GCMs or LSMs are added in the future.

  12. Inflow forecasting at BPA

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-07-01

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

  13. Say what? Coral reef sounds as indicators of community assemblages and reef conditions

    Science.gov (United States)

    Mooney, T. A.; Kaplan, M. B.

    2016-02-01

    Coral reefs host some of the highest diversity of life on the planet. Unfortunately, reef health and biodiversity is declining or is threatened as a result of climate change and human influences. Tracking these changes is necessary for effective resource management, yet estimating marine biodiversity and tracking trends in ecosystem health is a challenging and expensive task, especially in many pristine reefs which are remote and difficult to access. Many fishes, mammals and invertebrates make sound. These sounds are reflective of a number of vital biological processes and are a cue for settling reef larvae. Biological sounds may be a means to quantify ecosystem health and biodiversity, however the relationship between coral reef soundscapes and the actual taxa present remains largely unknown. This study presents a comparative evaluation of the soundscape of multiple reefs, naturally differing in benthic cover and fish diversity, in the U.S. Virgin Islands National Park. Using multiple recorders per reef we characterized spacio-temporal variation in biological sound production within and among reefs. Analyses of sounds recorded over 4 summer months indicated diel trends in both fish and snapping shrimp acoustic frequency bands with crepuscular peaks at all reefs. There were small but statistically significant acoustic differences among sites on a given reef raising the possibility of potentially localized acoustic habitats. The strength of diel trends in lower, fish-frequency bands were correlated with coral cover and fish density, yet no such relationship was found with shrimp sounds suggesting that fish sounds may be of higher relevance to tracking certain coral reef conditions. These findings indicate that, in spite of considerable variability within reef soundscapes, diel trends in low-frequency sound production reflect reef community assemblages. Further, monitoring soundscapes may be an efficient means of establishing and monitoring reef conditions.

  14. Evaluation of Probabilistic Disease Forecasts.

    Science.gov (United States)

    Hughes, Gareth; Burnett, Fiona J

    2017-10-01

    The statistical evaluation of probabilistic disease forecasts often involves calculation of metrics defined conditionally on disease status, such as sensitivity and specificity. However, for the purpose of disease management decision making, metrics defined conditionally on the result of the forecast-predictive values-are also important, although less frequently reported. In this context, the application of scoring rules in the evaluation of probabilistic disease forecasts is discussed. An index of separation with application in the evaluation of probabilistic disease forecasts, described in the clinical literature, is also considered and its relation to scoring rules illustrated. Scoring rules provide a principled basis for the evaluation of probabilistic forecasts used in plant disease management. In particular, the decomposition of scoring rules into interpretable components is an advantageous feature of their application in the evaluation of disease forecasts.

  15. [Indicator condition guided human immunodeficiency virus requesting in primary health care: results of a collaboration].

    Science.gov (United States)

    Cayuelas-Redondo, Laia; Menacho-Pascual, Ignacio; Noguera-Sánchez, Pablo; Goicoa-Gago, Carmen; Pollio-Peña, Gernónimo; Blanco-Delgado, Rebeca; Barba-Ávila, Olga; Sequeira-Aymar, Ethel; Muns, Mercè; Clusa, Thais; García, Felipe; León, Agathe

    2015-12-01

    The search of HIV infected patients guided by indicator conditions (IC) is a strategy used to increase the early detection of HIV. The objective is to analyze whether a collaboration to raise awareness of the importance of early detection of HIV in 3 primary care centers influenced the proportion of HIV serology requested. Multicenter retrospective study was conducted comparing the baseline and a post-collaboration period. The collaboration consisted of training sessions and participation in the HIDES study (years 2009-2010). Patients between 18 and 64 years old with newly diagnosed herpes zoster, seborrheic eczema, mononucleosis syndrome, and leucopenia/thrombocytopenia in 3 primary care centers in 2008 (baseline period) and 2012 (post-collaboration period). The sociodemographic variables, HIV risk conditions, requests for HIV serology, and outcomes were evaluated. A total of 1,219 ICs were included (558 in 2008 and 661 in 2012). In 2008 the number of HIV tests in patients with an IC was 3.9%, and rose to 11.8% in 2012 (Pde Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

  16. Evaluating the spatio-temporal performance of sky imager based solar irradiance analysis and forecasts

    Science.gov (United States)

    Schmidt, T.; Kalisch, J.; Lorenz, E.; Heinemann, D.

    2015-10-01

    Clouds are the dominant source of variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the world-wide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a shortest-term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A two month dataset with images from one sky imager and high resolutive GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series in different cloud scenarios. Overall, the sky imager based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depend strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1-2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

  17. Added value of dynamical downscaling of winter seasonal forecasts over North America

    Science.gov (United States)

    Tefera Diro, Gulilat; Sushama, Laxmi

    2017-04-01

    Skillful seasonal forecasts have enormous potential benefits for socio-economic sectors that are sensitive to weather and climate conditions, as the early warning routines could reduce the vulnerability of such sectors. In this study, individual ensemble members of the ECMWF global ensemble seasonal forecasts are dynamically downscaled to produce ensemble of regional seasonal forecasts over North America using the fifth generation Canadian Regional Climate Model (CRCM5). CRCM5 forecasts are initialized on November 1st of each year and are integrated for four months for the 1991-2001 period at 0.22 degree resolution to produce a one-month lead-time forecast. The initial conditions for atmospheric variables are obtained from ERA-Interim reanalysis, whereas the initial conditions for land surface are obtained from a separate ERA-interim driven CRCM5 simulation with spectral nudging applied to the interior domain. The global and regional ensemble forecasts were then verified to investigate the skill and economic benefits of dynamical downscaling. Results indicate that both the global and regional climate models produce skillful precipitation forecast over the southern Great Plains and eastern coasts of the U.S and skillful temperature forecasts over the northern U.S. and most of Canada. In comparison to ECMWF forecasts, CRCM5 forecasts improved the temperature forecast skill over most part of the domain, but the improvements for precipitation is limited to regions with complex topography, where it improves the frequency of intense daily precipitation. CRCM5 forecast also yields a better economic value compared to ECMWF precipitation forecasts, for users whose cost to loss ratio is smaller than 0.5.

  18. Adaptive Weather Forecasting using Local Meteorological Information

    NARCIS (Netherlands)

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

    2005-01-01

    In general, meteorological parameters such as temperature, rain and global radiation are important for agricultural systems. Anticipating on future conditions is most often needed in these systems. Weather forecasts then become of substantial importance. As weather forecasts are subject to

  19. Functional traits of selected mangrove species in Brazil as biological indicators of different environmental conditions

    Energy Technology Data Exchange (ETDEWEB)

    Arrivabene, Hiulana Pereira [Universidade Federal do Espírito Santo, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, 29075-910 Vitória, Espírito Santo (Brazil); Souza, Iara [Universidade Federal de São Carlos, Centro de Ciências Biológicas e da Saúde, Departamento de Ciências Fisiológicas, 13565-905 São Carlos (Brazil); Có, Walter Luiz Oliveira [Associação Educational de Vitória, Departamento de Biologia, 29053-360 Vitória (Brazil); Rodella, Roberto Antônio [Universidade Estadual Paulista Júlio de Mesquita Filho, Campus de Botucatu, Instituto de Biociências, Departamento de Botânica, C. Postal 510, 18618-000 Botucatu, São Paulo (Brazil); Wunderlin, Daniel Alberto, E-mail: dwunder@fcq.unc.edu.ar [Instituto de Ciencia y Tecnología de Alimentos Córdoba (ICYTAC), CONICET, Dpto. Qca. Orgánica, Fac. Cs. Químicas, Universidad Nacional de Córdoba, Ciudad Universitaria, 5000, Córdoba (Argentina); and others

    2014-04-01

    Ecological studies on phenotypic plasticity illustrate the relevance of this phenomenon in nature. Conditions of biota reflect environmental changes, highlighting the adaptability of resident species that can be used as bioindicators of such changes. We report the morpho-anatomical plasticity of leaves of Avicennia schaueriana Stapf and Leechm. ex Moldenke, Laguncularia racemosa (L.) C.F.Gaertn. and Rhizophora mangle L., evaluated in three estuaries (Vitória bay, Santa Cruz and Itaúnas River; state of Espírito Santo, Brazil), considering five areas of mangrove ecosystems with diverse environmental issues. Two sampling sites are part of the Ecological Station Lameirão Island in Vitória bay, close to a harbor. A third sampling site in Cariacica (Vitória bay) is inside the Vitória harbor and also is influenced by domestic sewage. The fourth studied area (Santa Cruz) is part of Piraquê Mangrove Ecological Reservation, while the fifth (Itaúnas River) is a small mangrove, with sandy sediment and greater photosynthetically active radiation, also not strongly influenced by anthropic activity. Results pointed out the morpho-anatomical plasticity in studied species, showing that A. schaueriana and L. racemosa might be considered the most appropriate bioindicators to indicate different settings and environmental conditions. Particularly, the dry mass per leaf area (LMA) of A. schaueriana was the main biomarker measured. In our study, LMA of A. schaueriana was positively correlated with salinity (Spearman 0.71), Mn content (0.81) and pH (0.82) but negatively correlated with phosphorus content (− 0.63). Thus, the evaluation of modification in LMA of A. schaueriana pointed out changes among five studied sites, suggesting its use to reflect changes in the environment, which could be also useful in the future to evaluate the climate change. - Highlights: • We investigated adaptive modifications in plants in response to differences among three estuaries. • We used

  20. Functional traits of selected mangrove species in Brazil as biological indicators of different environmental conditions

    International Nuclear Information System (INIS)

    Arrivabene, Hiulana Pereira; Souza, Iara; Có, Walter Luiz Oliveira; Rodella, Roberto Antônio; Wunderlin, Daniel Alberto

    2014-01-01

    Ecological studies on phenotypic plasticity illustrate the relevance of this phenomenon in nature. Conditions of biota reflect environmental changes, highlighting the adaptability of resident species that can be used as bioindicators of such changes. We report the morpho-anatomical plasticity of leaves of Avicennia schaueriana Stapf and Leechm. ex Moldenke, Laguncularia racemosa (L.) C.F.Gaertn. and Rhizophora mangle L., evaluated in three estuaries (Vitória bay, Santa Cruz and Itaúnas River; state of Espírito Santo, Brazil), considering five areas of mangrove ecosystems with diverse environmental issues. Two sampling sites are part of the Ecological Station Lameirão Island in Vitória bay, close to a harbor. A third sampling site in Cariacica (Vitória bay) is inside the Vitória harbor and also is influenced by domestic sewage. The fourth studied area (Santa Cruz) is part of Piraquê Mangrove Ecological Reservation, while the fifth (Itaúnas River) is a small mangrove, with sandy sediment and greater photosynthetically active radiation, also not strongly influenced by anthropic activity. Results pointed out the morpho-anatomical plasticity in studied species, showing that A. schaueriana and L. racemosa might be considered the most appropriate bioindicators to indicate different settings and environmental conditions. Particularly, the dry mass per leaf area (LMA) of A. schaueriana was the main biomarker measured. In our study, LMA of A. schaueriana was positively correlated with salinity (Spearman 0.71), Mn content (0.81) and pH (0.82) but negatively correlated with phosphorus content (− 0.63). Thus, the evaluation of modification in LMA of A. schaueriana pointed out changes among five studied sites, suggesting its use to reflect changes in the environment, which could be also useful in the future to evaluate the climate change. - Highlights: • We investigated adaptive modifications in plants in response to differences among three estuaries. • We used

  1. 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...

  2. Strategic Forecasting

    DEFF Research Database (Denmark)

    Duus, Henrik Johannsen

    2016-01-01

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

  3. Performance indices of project companies virtual divisions in the construction in CAD conditions

    Directory of Open Access Journals (Sweden)

    Sinenko Sergey

    2017-01-01

    Full Text Available At the present time we consider the construction operations development triggered by the modern technologies development. The electronics, robotics, artificial intelligence, wireless technologies and more became the present-day production attribute. The creation of virtual organizations has become the expected solution of business communities. Following in the footsteps of information boom, in this article we consider the problem of construction field virtualisation, in particular: characteristics of virtuality and virtual structures operation, in-virtual organization work peculiarities, difficulties faced by the company manager with such form of work and criteria for the assessment of organization efficiency. The virtual organization is deemed to be the voluntary cooperation form of partners, aimed at project work type. This is the unique team, the basic resources of which are time and technologies. In general such organization does not have any geographical origin and it works using the Internet. In the context given herein, the virtual structure is considered in CAD conditions that is based on the high degree of construction field IT. Specific relations between the employees make the impact on the work process, therefore a number of both subjective (social, individual, etc. and objective (financial indices are given.

  4. National projections of forest and rangeland condition indicators: a supporting technical document for the 1999 RPA assessment.

    Science.gov (United States)

    John Hof; Curtis Flather; Tony Baltic; Stephen. Davies

    1999-01-01

    The 1999 forest and rangeland condition indicator model is a set of independent econometric production functions for environmental outputs (measured with condition indicators) at the national scale. This report documents the development of the database and the statistical estimation required by this particular production structure with emphasis on two special...

  5. A construct with fluorescent indicators for conditional expression of miRNA

    Directory of Open Access Journals (Sweden)

    Xia Xugang

    2008-10-01

    Full Text Available Abstract Background Transgenic RNAi holds promise as a simple, low-cost, and fast method for reverse genetics in mammals. It may be particularly useful for producing animal models for hypomorphic gene function. Inducible RNAi that permits spatially and temporally controllable gene silencing in vivo will enhance the power of transgenic RNAi approach. Furthermore, because microRNA (miRNA targeting specific genes can be expressed simultaneously with protein coding genes, incorporation of fluorescent marker proteins can simplify the screening and analysis of transgenic RNAi animals. Results We sought to optimally express a miRNA simultaneously with a fluorescent marker. We compared two construct designs. One expressed a red fluorescent protein (RFP and a miRNA placed in its 3' untranslated region (UTR. The other expressed the same RFP and miRNA, but the precursor miRNA (pre-miRNA coding sequence was placed in an intron that was inserted into the 3'-UTR. We found that the two constructs expressed comparable levels of miRNA. However, the intron-containing construct expressed a significantly higher level of RFP than the intron-less construct. Further experiments indicate that the 3'-UTR intron enhances RFP expression by its intrinsic gene-expression-enhancing activity and by eliminating the inhibitory effect of the pre-miRNA on the expression of RFP. Based on these findings, we incorporated the intron-embedded pre-miRNA design into a conditional expression construct that employed the Cre-loxP system. This construct initially expressed EGFP gene, which was flanked by loxP sites. After exposure to Cre recombinase, the transgene stopped EGFP expression and began expression of RFP and a miRNA, which silenced the expression of specific cellular genes. Conclusion We have designed and tested a conditional miRNA-expression construct and showed that this construct expresses both the marker genes strongly and can silence the target gene efficiently upon Cre

  6. Satellite assessment of early-season forecasts for vegetation conditions of grazing allotments in Nevada, United States

    Science.gov (United States)

    Fifteen years of enhanced vegetation index data from the MODIS sensor are examined in conjunction with precipitation and the Palmer drought severity index to assess how well growing season conditions for vegetation within grazing allotments of Nevada can be predicted at different times of the year. ...

  7. Forecasting metal prices: Do forecasters herd?

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  8. THE STUDY OF THE FORECASTING PROCESS INFRASTRUCTURAL SUPPORT BUSINESS

    Directory of Open Access Journals (Sweden)

    E. V. Sibirskaia

    2014-01-01

    Full Text Available Summary. When forecasting the necessary infrastructural support entrepreneurship predict rational distribution of the potential and expected results based on capacity development component of infrastructural maintenance, efficient use of resources, expertise and development of regional economies, the rationalization of administrative decisions, etc. According to the authors, the process of predicting business infrastructure software includes the following steps: analysis of the existing infrastructure support business to the top of the forecast period, the structure of resources, identifying disparities, their causes, identifying positive trends in the analysis and the results of research; research component of infrastructural support entrepreneurship, assesses complex system of social relations, institutions, structures and objects made findings and conclusions of the study; identification of areas of strategic change and the possibility of eliminating weaknesses and imbalances, identifying prospects for the development of entrepreneurship; identifying a set of factors and conditions affecting each component of infrastructure software, calculated the degree of influence of each of them and the total effect of all factors; adjustment indicators infrastructure forecasts. Research of views of category says a method of strategic planning and forecasting that methods of strategic planning are considered separately from forecasting methods. In a combination methods of strategic planning and forecasting, in relation to infrastructure ensuring business activity aren't given in literature. Nevertheless, authors consider that this category should be defined for the characteristic of the intrinsic and substantial nature of strategic planning and forecasting of infrastructure ensuring business activity.processing.

  9. The relationship of heavy metals and condition indices of green-lipped mussel perna viridis from contaminated and uncontaminated environments

    International Nuclear Information System (INIS)

    Ahmad Ismail; Yap Chee Kong

    1999-01-01

    Heavy metal concentrations and condition indices of green-fipped mussel Perna viridis were detemiined at two different sites of Peninsular Malaysia. Significant negative correlations (p< 0.001) between condition indices and heavy metals were observed. Samples from Kuala Perlis which relatively showed high heavy metals concentrations in mussels exhibited lower condition index while Kg. Tg. Batu with lower heavy metal levels, showed higher condition index. The environmental stress is believed to be responsible for the different physiological index in green-fipped mussel P. viridis. (author)

  10. Method of forecasting power distribution

    International Nuclear Information System (INIS)

    Kaneto, Kunikazu.

    1981-01-01

    Purpose: To obtain forecasting results at high accuracy by reflecting the signals from neutron detectors disposed in the reactor core on the forecasting results. Method: An on-line computer transfers, to a simulator, those process data such as temperature and flow rate for coolants in each of the sections and various measuring signals such as control rod positions from the nuclear reactor. The simulator calculates the present power distribution before the control operation. The signals from the neutron detectors at each of the positions in the reactor core are estimated from the power distribution and errors are determined based on the estimated values and the measured values to determine the smooth error distribution in the axial direction. Then, input conditions at the time to be forecast are set by a data setter. The simulator calculates the forecast power distribution after the control operation based on the set conditions. The forecast power distribution is corrected using the error distribution. (Yoshino, Y.)

  11. Toward a Satellite-Based System of Sugarcane Yield Estimation and Forecasting in Smallholder Farming Conditions: A Case Study on Reunion Island

    Directory of Open Access Journals (Sweden)

    Julien Morel

    2014-07-01

    Full Text Available Estimating sugarcane biomass is difficult to achieve when working with highly variable spatial distributions of growing conditions, like on Reunion Island. We used a dataset of in-farm fields with contrasted climatic conditions and farming practices to compare three methods of yield estimation based on remote sensing: (1 an empirical relationship method with a growing season-integrated Normalized Difference Vegetation Index NDVI, (2 the Kumar-Monteith efficiency model, and (3 a forced-coupling method with a sugarcane crop model (MOSICAS and satellite-derived fraction of absorbed photosynthetically active radiation. These models were compared with the crop model alone and discussed to provide recommendations for a satellite-based system for the estimation of yield at the field scale. Results showed that the linear empirical model produced the best results (RMSE = 10.4 t∙ha−1. Because this method is also the simplest to set up and requires less input data, it appears that it is the most suitable for performing operational estimations and forecasts of sugarcane yield at the field scale. The main limitation is the acquisition of a minimum of five satellite images. The upcoming open-access Sentinel-2 Earth observation system should overcome this limitation because it will provide 10-m resolution satellite images with a 5-day frequency.

  12. A nonparametric approach to forecasting realized volatility

    OpenAIRE

    Adam Clements; Ralf Becker

    2009-01-01

    A well developed literature exists in relation to modeling and forecasting asset return volatility. Much of this relate to the development of time series models of volatility. This paper proposes an alternative method for forecasting volatility that does not involve such a model. Under this approach a forecast is a weighted average of historical volatility. The greatest weight is given to periods that exhibit the most similar market conditions to the time at which the forecast is being formed...

  13. Forecast of auroral activity

    International Nuclear Information System (INIS)

    Lui, A.T.Y.

    2004-01-01

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

  14. OCCUPATIONAL ACCIDENTS AS INDICATORS OF INADEQUATE WORK CONDITIONS AND WORK ENVIRONMENT

    OpenAIRE

    Petar Babović

    2009-01-01

    Occupational accidents due to inadequate working conditions and work environment present a major problem in highly industrialised countries, as well as in developing ones. Occupational accidents are a regular and accompanying phenomenon in all human activities and one of the main health related and economic problems in modern societies.The aim of this study is the analysis of the connections of unfavourable working conditions and working environment on occupational accidents. Occurrence of oc...

  15. Using Acid Number as a Leading Indicator of Refrigeration and Air Conditioning System Performance

    Energy Technology Data Exchange (ETDEWEB)

    Dennis Cartlidge; Hans Schellhase

    2003-07-31

    number (TAN), which includes both mineral acids and organic acids, is therefore a useful indicator which can be used to monitor the condition of the system in order to perform remedial maintenance, when required, to prevent system failure. The critical TAN value is the acid level at which remedial action should be taken to prevent the onset of rapid acid formation which can result in system failure. The level of 0.05 mg KOH/g of oil was established for CFC/mineral oil systems based on analysis of 700 used lubricants from operating systems and failed units. There is no consensus within the refrigeration industry as to the critical TAN value for HFC/POE systems, however, the value will be higher than the CFC/mineral oil systems critical TAN value because of the much weaker organic acids produced from POE. A similar study of used POE lubricants should be performed to establish a critical TAN limit for POE systems. Titrimetric analysis per ASTM procedures is the most commonly used method to determine TAN values in lubricants in the refrigeration industry and other industries dealing with lubricating oils. For field measurements, acid test kits are often used since they provide rapid, semi-quantitative TAN results.

  16. EXTREME WINTERS IN XX–XXI CENTURIES AS INDICATORS OF SNOWINESS AND AVALANCHE HAZARD IN THE PAST AND EXPECTED CLIMATE CHANGE CONDITIONS

    Directory of Open Access Journals (Sweden)

    A. D. Oleynikov

    2012-01-01

    Full Text Available Currently, due to the global climate change and increasing frequency of weather events focus is on prediction of climate extremes. Large-scale meteorological anomalies can cause long-term paralysis of social and economic infrastructure of the major mountain regions and even individual states. In winter periods, these anomalies are associated with prolonged heavy snowfalls and associated with them catastrophic avalanches which cause significant social and economic damage. The climate system maintains a certain momentum during periods of adjustment and transition to other conditions in the ratio of heat and moisture and contains a climate «signal» of the climates of the past and the future. In our view seasonal and yearly extremes perform the role of these indicators, study of which enables for a deeper understanding and appreciation of the real situation of the climate periods related to the modern ones. The paper provides an overview of the criteria for selection of extreme winters. Identification of extremely cold winters during the period of instrumental observation and assessment of their snowiness and avalanche activity done for the Elbrus region, which is a model site for study of the avalanche regime in the Central Caucasus. The studies aim to identify the extreme winters in the Greater Caucasus, assess their frequency of occurrence, characterize the scale and intensity of the avalanche formation. The data obtained can be used to identify winter-analogues in the reconstruction and long-term forecast of avalanches. 

  17. The daily hour forecasting of the electrical energy production from renewable energy sources – a required condition for the operation of the new energy market model

    International Nuclear Information System (INIS)

    Kalpachka, Gergana; Kalpachki, Georgi

    2011-01-01

    The report presented the new energy market model in Bulgaria and the main attention is directed to a daily hour forecasting of the electrical energy production from renewable energy sources. The need of development of a methodology and the development of the most precise methods for predicting is reviewed and some of the used methods at the moment are presented. An analysis of the problems related to the daily hour forecasting is done using data from the producers of electrical energy from renewable energy sources in the territory of western Bulgaria. Keywords: Renewable energy sources, daily hour forecasting, electrical energy

  18. The use of morphological and histological features as nutritional condition indices of Pagrus pagrus larvae

    Directory of Open Access Journals (Sweden)

    Marina Vera Diaz

    Full Text Available Morphometrical and histological techniques were employed to characterize Pagrus pagrus larvae nutritional condition. Larvae were reared in laboratory under controlled conditions with the main objective of testing whether these methodologies allowed finding differences between larvae from different feeding treatments. Once yolk was consumed (three days after hatching larvae were assigned to a feeding treatment: starved during the whole experiment; delayed feeding, starved during three days; fed during the entire experiment. Algae (Nannochloropsis oculata and rotifers (Brachionus plicatilis were provided to larvae for feed treatments. Larvae were fixed daily; for morphometrical purposes in 5% formaldehyde solution, and in Bouin for histological sections. Results herein obtained showed that both methodologies are sensitive enough to distinguish larvae characterized by different nutritional condition states obtained from the feeding treatments. Consequently, these methodologies could be employed in wild red porgy larvae in order to asses their nutritional condition. These techniques could also be employed to check larval quality obtained with aquaculture purposes to estimate the effects of changes in rearing protocols or kind of food supply and thus, to guaranty a higher survival of early developmental stages of reared larvae.

  19. Myocardial capillary permeability for small hydrophilic indicators during normal physiological conditions and after ischemia and reperfusion

    DEFF Research Database (Denmark)

    Svendsen, J H

    1991-01-01

    Myocardial capillary permeability for small hydrophilic solutes (51Cr-EDTA or 99mTc-DTPA) has been measured using intracoronary indicator bolus injection and external radioactivity registration (the single injection, residue detection method). The method is based on kinetic separation...

  20. Dynamic preload indicators fail to predict fluid responsiveness in open-chest conditions

    NARCIS (Netherlands)

    de Waal, Eric E. C.; Rex, Steffen; Kruitwagen, Cas L. J. J.; Kalkman, Cor J.; Buhre, Wolfgang F.

    Objective: Dynamic preload indicators like pulse pressure variation (PPV) and stroke volume variation (SVV) are increasingly being used for optimizing cardiac preload since they have been demonstrated to predict fluid responsiveness in a variety of perioperative settings. However, in open-chest

  1. Interest Parity Conditions as Indicators of Financial Integration in East Asia

    OpenAIRE

    Gordon de Brouwer

    1997-01-01

    Market participants and policymakers have a growing interest in the development of East Asian financial markets, and to the extent to which these markets are open and influenced by world markets. This paper examines the information contained in interest parity conditions about the international integration of a wide range of economies in East Asia. Legal restrictions on the capital account and tests of covered, uncovered and real interest parity are presented in some detail. Using standard re...

  2. Evaluation of body condition score measured throughout lactation as an indicator of fertility in dairy cattle

    OpenAIRE

    Banos, G; Brotherstone, S; Coffey, MP

    2004-01-01

    Body condition score (BCS) records of primiparous Holstein cows were analyzed both as a single measure per animal and as repeated measures per sire of cow. The former resulted in a single, average, genetic evaluation for each sire, and the latter resulted in separate genetic evaluations per day of lactation. Repeated measure analysis yielded genetic correlations of less than unity between days of lactation, suggesting that BCS may not be the same trait across lactation. Differences between da...

  3. Nonlinear time series modeling and forecasting the seismic data of the Hindu Kush region

    Science.gov (United States)

    Khan, Muhammad Yousaf; Mittnik, Stefan

    2018-01-01

    In this study, we extended the application of linear and nonlinear time models in the field of earthquake seismology and examined the out-of-sample forecast accuracy of linear Autoregressive (AR), Autoregressive Conditional Duration (ACD), Self-Exciting Threshold Autoregressive (SETAR), Threshold Autoregressive (TAR), Logistic Smooth Transition Autoregressive (LSTAR), Additive Autoregressive (AAR), and Artificial Neural Network (ANN) models for seismic data of the Hindu Kush region. We also extended the previous studies by using Vector Autoregressive (VAR) and Threshold Vector Autoregressive (TVAR) models and compared their forecasting accuracy with linear AR model. Unlike previous studies that typically consider the threshold model specifications by using internal threshold variable, we specified these models with external transition variables and compared their out-of-sample forecasting performance with the linear benchmark AR model. The modeling results show that time series models used in the present study are capable of capturing the dynamic structure present in the seismic data. The point forecast results indicate that the AR model generally outperforms the nonlinear models. However, in some cases, threshold models with external threshold variables specification produce more accurate forecasts, indicating that specification of threshold time series models is of crucial importance. For raw seismic data, the ACD model does not show an improved out-of-sample forecasting performance over the linear AR model. The results indicate that the AR model is the best forecasting device to model and forecast the raw seismic data of the Hindu Kush region.

  4. Energy efficiency index to artificially conditioned buildings; Indice de eficiencia energetica para edificios climatizados artificialmente

    Energy Technology Data Exchange (ETDEWEB)

    Jota, Patricia Romeiro da Silva; Santos, Carla da Silva; Costa, Kelly Luciene C. [Centro Federal de Educacao Tecnologica de Minas Gerais (CEMIG/CEFET), Belo Horizonte, MG (Brazil). Centro de Pesquisa em Energia Inteligente

    2010-07-01

    Conditioning buildings has been growing in number and are responsible for a significant portion of the energy used worldwide. The building energy use can be measured by the index of energy performance and specific fuel consumption (EC). The specific consumption is an index where the energy is normalized by the factors that affect energy use in order to obtain an index to explain variations in consumption. In this paper, we present a methodology to obtain a specific consumption that takes into account one of the factors that most affect energy use in these buildings, that is, the external temperature. The study is based on analysis of consumption of air conditioning system according to temperature. Through this analysis we obtain a function to facilitate the standardization of energy use, depending on the temperature outside. This methodology was tested in previous work on real buildings without stratification of energy, and this work will be presented a case study of a building whose energy measurement is stratified. The proposed index is the ratio between the energy consumption of air conditioning system corrected by the temperature through the function K(T). It was possible to demonstrate the efficiency of the index to eliminate the effect of temperature and thus to evaluate the evolution of specific consumption over the months analyzed. (author)

  5. Integrating Condition Indicators and Usage Parameters for Improved Spiral Bevel Gear Health Monitoring

    Science.gov (United States)

    Dempsey, Paula J.; Handschuh, Robert F.; Delgado, Irebert, R.

    2013-01-01

    The objective of this study was to illustrate the importance of combining Health Usage Monitoring Systems (HUMS) data with usage monitoring system data when detecting rotorcraft transmission health. Three gear sets were tested in the NASA Glenn Spiral Bevel Gear Fatigue Rig. Damage was initiated and progressed on the gear and pinion teeth. Damage progression was measured by debris generation and documented with inspection photos at varying torque values. A contact fatigue analysis was applied to the gear design indicating the effect temperature, load and reliability had on gear life. Results of this study illustrated the benefits of combining HUMS data and actual usage data to indicate progression of damage for spiral bevel gears.

  6. Myocardial capillary permeability for small hydrophilic indicators during normal physiological conditions and after ischemia and reperfusion

    DEFF Research Database (Denmark)

    Svendsen, Jesper Hastrup

    1991-01-01

    Myocardial capillary permeability for small hydrophilic solutes (51Cr-EDTA or 99mTc-DTPA) has been measured using intracoronary indicator bolus injection and external radioactivity registration (the single injection, residue detection method). The method is based on kinetic separation of the inje......Myocardial capillary permeability for small hydrophilic solutes (51Cr-EDTA or 99mTc-DTPA) has been measured using intracoronary indicator bolus injection and external radioactivity registration (the single injection, residue detection method). The method is based on kinetic separation...... including microvascular alterations. In open chest dogs transitory increases in capillary extraction fraction and PdS for small hydrophilic solutes were seen following 20 minutes of regional myocardial ischemia and reperfusion. This response could be inhibited by treatment directed against superoxide...

  7. Body condition score and milk fatty acids as indicators of dairy cattle reproductive performances

    OpenAIRE

    Bastin, Catherine

    2013-01-01

    Improving cow fertility by means of genetic selection has become increasingly important over the last years in order to overcome the decline in dairy cow fertility that has taken place over the past decades. However, fertility traits are difficult to measure and have low heritabilities. Consequently, indicator traits are of interest for breeding value estimation for fertility especially if these traits are easier to measure, have higher heritabilities and are well correlated with fertility. T...

  8. Are gynaecological and pregnancy-associated conditions in family practice indicators of intimate partner violence?

    Science.gov (United States)

    Loeffen, Maartje J W; Lo Fo Wong, Sylvie H; Wester, Fred P J F; Laurant, Miranda G H; Lagro-Janssen, Antoine L M

    2016-08-01

    Some gynaecological and pregnancy-associated conditions are more common in abused women than in non-abused women, but this has not been examined in family practice. We aimed to investigate intimate partner violence (IPV) prevalence in family practice and to investigate whether gynaecological and pregnancy-associated conditions are more common in abused women than in non-abused women. We conducted a cross-sectional waiting room survey in 12 family practices in the Netherlands in 2012. Women were eligible if they were of 18 years or older. Questionnaires measured IPV and gynaecological and pregnancy-associated conditions. Chi-square tests were used to assess the differences in gynaecological and pregnancy-associated conditions between abused women and non-abused women. The response rate was 86% (262 of 306 women). The past-year prevalence of IPV in women who had had an intimate relationship in the past year and were not accompanied by their partner was 8.7% (n = 195). Lifetime prevalence of women who had ever had an intimate relationship, but not in the past year, was 17.6% (n = 51). Sexually transmitted infections (STIs) [odds ratio (OR) = 4.6, 95% confidence interval [CI] = 1.7-12.5, n = 240], menstrual disorders (OR = 3.7, 95% CI = 1.2-11.2, n = 143), sexual problems (OR = 3.3, 95% CI = 1.2-9.3, n = 229), miscarriages (OR = 2.5, 95% CI = 1.062-5.8, n = 202) and induced abortions (OR = 2.7, 95% CI = 1.028-7.3, n = 202) were significantly more common in abused women than in non-abused women. Family physicians should ask about IPV when women present with STIs, menstrual disorders, sexual problems, miscarriages or induced abortions. To improve the recognition of IPV, future research needs to investigate whether a combination of symptoms offers improved prediction of IPV. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  9. Soil pollution indices conditioned by medieval metallurgical activity - A case study from Krakow (Poland).

    Science.gov (United States)

    Kowalska, Joanna; Mazurek, Ryszard; Gąsiorek, Michał; Setlak, Marcin; Zaleski, Tomasz; Waroszewski, Jaroslaw

    2016-11-01

    The studied soil profile under the Main Market Square (MMS) in Krakow was characterised by the influence of medieval metallurgical activity. In the presented soil section lithological discontinuity (LD) was found, which manifests itself in the form of cultural layers (CLs). Moreover, in this paper LD detection methods based on soil texture are presented. For the first time, three different ways to identify the presence of LD in the urban soils are suggested. The presence of LD had an influence on the content and distribution of heavy metals within the soil profile. The content of heavy metals in the CLs under the MMS in Krakow was significantly higher than the content in natural horizons. In addition, there were distinct differences in the content of heavy metals within CLs. Profile variability and differences in the content of heavy metals and phosphorus within the CLs under the MMS were activity indicators of Krakow inhabitants in the past. This paper presents alternative methods for the assessment of the degree of heavy metal contamination in urban soils using selected pollution indices. On the basis of the studied total concentration of heavy metals (Zn, Pb, Cu, Mn, Cr, Cd, Ni, Sn, Ag) and total phosphorus content, the Geoaccumulation Index (I geo ), Enrichment Factor (EF), Sum of Pollution Index (PI sum ), Single Pollution Index (PI), Nemerow Pollution Index (PI Nemerow ) and Potential Ecological Risk (RI) were calculated using different local and reference geochemical backgrounds. The use of various geochemical backgrounds is helpful to evaluate the assessment of soil pollution. The individual CLs differed from each other according to the degree of pollution. The different values of pollution indices within the studied soil profile showed that LDS should not be evaluated in terms of contamination as one, homogeneous soil profile but each separate CL should be treated individually. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Hair geochemical composition of children from Vilnius kindergartens as an indicator of environmental conditions.

    Science.gov (United States)

    Taraškevičius, Ričardas; Zinkutė, Rimantė; Gedminienė, Laura; Stankevičius, Žilvinas

    2017-05-23

    The research is based on analysis data of Cr, Cu, Mn, Ni, V, Zn (metals) and S in the hair of 47 girls and 63 boys from eight Vilnius kindergartens and the distribution pattern of high metal concentrations and bioavailability in snow-cover dust, also dust samples from vents of characteristic pollution sources. The kindergartens were selected according to topsoil total contamination index and dust-related indices. Significantly higher Cu, Mn, Ni and Zn concentrations in the hair of girls (means are 1.1, 1.9, 1.3, 1.2 times higher) and the differences between hair of genders according to inter-element correlation and clustering were found. Analysis of Spearman correlation coefficients between metal concentrations in hair of each gender and dust metal concentrations or metal loading rates at their residence sites revealed that for Mn, Cu and Zn, they are insignificant, while for Cr, Ni, Pb and V, they are mainly significant positive (except V in female hair). The correlation of the contents of Cr, Ni and V in dust with respective concentrations in hair was more significant for boys (p polluted kindergartens in comparison with control. It was concluded that relationship between metal concentrations in hair and dust-related indices is more expressed for children's residence sites than for their kindergarten sites. The gender-based grouping and site-by-site study design are recommended in the studies of reflection of environmental exposure in hair.

  11. Assessment of ranges plasma indices in rainbow trout (Oncorhynchus mykiss reared under conditions of intensive aquaculture

    Directory of Open Access Journals (Sweden)

    Radovan Kopp

    2011-01-01

    Full Text Available Plasma parameters in rainbow trout (Oncorhynchus mykiss from three various trout farms in the Czech Republic were assessed using automated blood plasma analyser. Non-haemolysed serum from the heart of 48 healthy, randomly selected fish (standard length, mean ± SD = 247.3 ± 24.2 mm; body mass, mean ± SD = 262.18 ± 87.28 g was analysed for the following plasma parameters: alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, acid phosphatase, lactate dehydrogenase, creatine kinase, total protein, cholinesterase, amylase, glucose, lactate, albumin, urea, cholesterol, triglycerides, lipase, Ca, Mg, P, Fe, Na, K and Cl. All data were analysed statistically such as normality assessment by means of Kolmogorov–Smirnov test and adequate statistical testing using various parametric and non-parametric tests for each variable. With regard to data distribution, 19 indices out of 23 (aspartate aminotransferase, alkaline phosphatase, acid phosphatase, lactate dehydrogenase, total protein, amylase, glucose, lactate, albumin, urea, cholesterol, triglycerides, Ca, Mg, P, Fe, Na, K and Cl were normally distributed. The indices were affected by handling time and, accordingly to the physical and chemical properties of water. Estimates obtained were compared with previously reported ranges. The blood automated analyser proved to be a valuable and reliable instrument for the estimation of plasma parameters determining normal ranges in rainbow trout.

  12. Assessment of students’ health condition by indicators of adaptation potential, biological age and bio-energetic reserves of organism

    Directory of Open Access Journals (Sweden)

    O.V. Martyniuk

    2015-06-01

    Full Text Available Purpose: to assess students’ health condition by indicators of adaptation potential, biological age and express-assessment. Material: in the research 47 first and second year girl students participated, who belonged to main health group. Results: we distributed the girl students into three groups: 14.89% of them were included in group with “safe” health condition; 34.04% - in group of “third state”; 51.06% were related to group with “ dangerous” health condition. We established that dangerous level was characterized by energy potential of below middle and low level. It is accompanied by accelerated processes of organism’s age destructions and tension of regulation mechanisms. Conclusions: the received results permit to further develop and generalize the data of students’ health’s assessment by indicators of adaptation potentials, biological age and physical health’s condition.

  13. Exploring What Determines the Use of Forecasts of Varying Time Periods in Guanacaste, Costa Rica

    Science.gov (United States)

    Babcock, M.; Wong-Parodi, G.; Grossmann, I.; Small, M. J.

    2016-12-01

    Weather and climate forecasts are promoted as ways to improve water management, especially in the face of changing environmental conditions. However, studies indicate many stakeholders who may benefit from such information do not use it. This study sought to better understand which personal factors (e.g., trust in forecast sources, perceptions of accuracy) were important determinants of the use of 4-day, 3-month, and 12-month rainfall forecasts by stakeholders in water management-related sectors in the seasonally dry province of Guanacaste, Costa Rica. From August to October 2015, we surveyed 87 stakeholders from a mix of government agencies, local water committees, large farms, tourist businesses, environmental NGO's, and the public. The result of an exploratory factor analysis suggests that trust in "informal" forecast sources (traditional methods, family advice) and in "formal" sources (government, university and private company science) are independent of each other. The result of logistic regression analyses suggest that 1) greater understanding of forecasts is associated with a greater probability of 4-day and 3-month forecast use, but not 12-month forecast use, 2) a greater probability of 3-month forecast use is associated with a lower level of trust in "informal" sources, and 3), feeling less secure about water resources, and regularly using many sources of information (and specifically formal meetings and reports) are each associated with a greater probability of using 12-month forecasts. While limited by the sample size, and affected by the factoring method and regression model assumptions, these results do appear to suggest that while forecasts of all times scales are used to some extent, local decision makers' decisions to use 4-day and 3-month forecasts appear to be more intrinsically motivated (based on their level of understanding and trust) and the use of 12-month forecasts seems to be more motivated by a sense of requirement or mandate.

  14. A quantitative sensitivity analysis on the behaviour of common thermal indices under hot and windy conditions in Doha, Qatar

    Science.gov (United States)

    Fröhlich, Dominik; Matzarakis, Andreas

    2016-04-01

    Human thermal perception is best described through thermal indices. The most popular thermal indices applied in human bioclimatology are the perceived temperature (PT), the Universal Thermal Climate Index (UTCI), and the physiologically equivalent temperature (PET). They are analysed focusing on their sensitivity to single meteorological input parameters under the hot and windy meteorological conditions observed in Doha, Qatar. It can be noted, that the results for the three indices are distributed quite differently. Furthermore, they respond quite differently to modifications in the input conditions. All of them show particular limitations and shortcomings that have to be considered and discussed. While the results for PT are unevenly distributed, UTCI shows limitations concerning the input data accepted. PET seems to respond insufficiently to changes in vapour pressure. The indices should therefore be improved to be valid for several kinds of climates.

  15. Evaluation of body condition score measured throughout lactation as an indicator of fertility in dairy cattle.

    Science.gov (United States)

    Banos, G; Brotherstone, S; Coffey, M P

    2004-08-01

    Body condition score (BCS) records of primiparous Holstein cows were analyzed both as a single measure per animal and as repeated measures per sire of cow. The former resulted in a single, average, genetic evaluation for each sire, and the latter resulted in separate genetic evaluations per day of lactation. Repeated measure analysis yielded genetic correlations of less than unity between days of lactation, suggesting that BCS may not be the same trait across lactation. Differences between daily genetic evaluations on d 10 or 30 and subsequent daily evaluations were used to assess BCS change at different stages of lactation. Genetic evaluations for BCS level or change were used to estimate genetic correlations between BCS measures and fertility traits in order to assess the capacity of BCS to predict fertility. Genetic correlation estimates with calving interval and non-return rate were consistently higher for daily BCS than single measure BCS evaluations, but results were not always statistically different. Genetic correlations between BCS change and fertility traits were not significantly different from zero. The product of the accuracy of BCS evaluations with their genetic correlation with the UK fertility index, comprising calving interval and non-return rate, was consistently higher for daily than for single BCS evaluations, by 28 to 53%. This product is associated with the conceptual correlated response in fertility from BCS selection and was highest for early (d 10 to 75) evaluations.

  16. SOFT project: a new forecasting system based on satellite data

    Science.gov (United States)

    Pascual, Ananda; Orfila, A.; Alvarez, Alberto; Hernandez, E.; Gomis, D.; Barth, Alexander; Tintore, Joaquim

    2002-01-01

    The aim of the SOFT project is to develop a new ocean forecasting system by using a combination of satellite dat, evolutionary programming and numerical ocean models. To achieve this objective two steps are proved: (1) to obtain an accurate ocean forecasting system using genetic algorithms based on satellite data; and (2) to integrate the above new system into existing deterministic numerical models. Evolutionary programming will be employed to build 'intelligent' systems that, learning form the past ocean variability and considering the present ocean state, will be able to infer near future ocean conditions. Validation of the forecast skill will be carried out by comparing the forecasts fields with satellite and in situ observations. Validation with satellite observations will provide the expected errors in the forecasting system. Validation with in situ data will indicate the capabilities of the satellite based forecast information to improve the performance of the numerical ocean models. This later validation will be accomplished considering in situ measurements in a specific oceanographic area at two different periods of time. The first set of observations will be employed to feed the hybrid systems while the second set will be used to validate the hybrid and traditional numerical model results.

  17. Stochastic weather inputs for improved urban water demand forecasting: application of nonlinear input variable selection and machine learning methods

    Science.gov (United States)

    Quilty, J.; Adamowski, J. F.

    2015-12-01

    Urban water supply systems are often stressed during seasonal outdoor water use as water demands related to the climate are variable in nature making it difficult to optimize the operation of the water supply system. Urban water demand forecasts (UWD) failing to include meteorological conditions as inputs to the forecast model may produce poor forecasts as they cannot account for the increase/decrease in demand related to meteorological conditions. Meteorological records stochastically simulated into the future can be used as inputs to data-driven UWD forecasts generally resulting in improved forecast accuracy. This study aims to produce data-driven UWD forecasts for two different Canadian water utilities (Montreal and Victoria) using machine learning methods by first selecting historical UWD and meteorological records derived from a stochastic weather generator using nonlinear input variable selection. The nonlinear input variable selection methods considered in this work are derived from the concept of conditional mutual information, a nonlinear dependency measure based on (multivariate) probability density functions and accounts for relevancy, conditional relevancy, and redundancy from a potential set of input variables. The results of our study indicate that stochastic weather inputs can improve UWD forecast accuracy for the two sites considered in this work. Nonlinear input variable selection is suggested as a means to identify which meteorological conditions should be utilized in the forecast.

  18. Robust and predictive fuzzy key performance indicators for condition-based treatment of squats in railway infrastructures

    NARCIS (Netherlands)

    Jamshidi, A.; Nunez Vicencio, Alfredo; Dollevoet, R.P.B.J.; Li, Z.

    2017-01-01

    This paper presents a condition-based treatment methodology for a type of rail surface defect called squat. The proposed methodology is based on a set of robust and predictive fuzzy key performance indicators. A fuzzy Takagi-Sugeno interval model is used to predict squat evolution for different

  19. Life-history dependent relationships between body condition and immunity, between immunity indices in male Eurasian tree sparrows.

    Science.gov (United States)

    Zhao, Yuliang; Li, Mo; Sun, Yanfeng; Wu, Wei; Kou, Guanqun; Guo, Lingling; Xing, Danning; Wu, Yuefeng; Li, Dongming; Zhao, Baohua

    2017-08-01

    In free-living animals, recent evidence indicates that innate, and acquired, immunity varies with annual variation in the demand for, and availability of, food resources. However, little is known about how animals adjust the relationships between immunity and body condition, and between innate and acquired immunity to optimize survival over winter and reproductive success during the breeding stage. Here, we measured indices of body condition (size-corrected mass [SCM], and hematocrit [Hct]), constitutive innate immunity (plasma total complement hemolysis activity [CH 50 ]) and acquired immunity (plasma immunoglobulin A [IgA]), plus heterophil/lymphocyte (H/L) ratios, in male Eurasian tree sparrows (Passer montanus) during the wintering and the breeding stages. We found that birds during the wintering stage had higher IgA levels than those from the breeding stage. Two indices of body condition were both negatively correlated with plasma CH 50 activities, and positively with IgA levels in wintering birds, but this was not the case in the breeding birds. However, there was no correlation between CH 50 activities and IgA levels in both stages. These results suggest that the relationships between body condition and immunity can vary across life-history stage, and there are no correlations between innate and acquired immunity independent of life-history stage, in male Eurasian tree sparrows. Therefore, body condition indices predict immunological state, especially during the non-breeding stage, which can be useful indicators of individual immunocompetences for understanding the variations in innate and acquired immunity in free-living animals. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Forecasting Macedonian Business Cycle Turning Points Using Qual Var Model

    Directory of Open Access Journals (Sweden)

    Petrovska Magdalena

    2016-09-01

    Full Text Available This paper aims at assessing the usefulness of leading indicators in business cycle research and forecast. Initially we test the predictive power of the economic sentiment indicator (ESI within a static probit model as a leading indicator, commonly perceived to be able to provide a reliable summary of the current economic conditions. We further proceed analyzing how well an extended set of indicators performs in forecasting turning points of the Macedonian business cycle by employing the Qual VAR approach of Dueker (2005. In continuation, we evaluate the quality of the selected indicators in pseudo-out-of-sample context. The results show that the use of survey-based indicators as a complement to macroeconomic data work satisfactory well in capturing the business cycle developments in Macedonia.

  1. Foundry industries: environmental aspects and environmental condition indicators; Industrias de fundicion: aspectos ambientales e indicadores de condicion ambiental

    Energy Technology Data Exchange (ETDEWEB)

    Sosa, B. s.; Banda-Noriega, R. B.; Guerrero, E. M.

    2013-03-01

    Nowadays, environmental indicators are widely used as effective tools to assist decision-making in both public and private sectors. The lack of literature and research about local and regional Environmental Condition Indicators (ECI), the poor knowledge regarding solid waste generation, effluents and gas emissions from foundry industries, and their particular location in the urban area of Tandil, Argentina are the main reasons for this investigation, aiming to develop a set a of ECI to provide information about the environment in relation to the foundry industry. The study involves all the foundries located in the city between March and April 2010. The set of ECI developed includes 9 indicators for air, 5 for soil and 1 for water. Specific methodology was used for each indicator. (Author) 31 refs.

  2. kosh Terminal Aerodrome Forecast

    Data.gov (United States)

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

  3. kpdt Terminal Aerodrome Forecast

    Data.gov (United States)

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

  4. kewr 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. kiso 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. kpga 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. kbkw 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. ktcl 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. pgwt Terminal Aerodrome Forecast

    Data.gov (United States)

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

  10. kpsp Terminal Aerodrome Forecast

    Data.gov (United States)

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

  11. kbih 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. kdnl 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. kart 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. kilm Terminal Aerodrome Forecast

    Data.gov (United States)

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

  15. kpne Terminal Aerodrome Forecast

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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...

  16. kabi Terminal Aerodrome Forecast

    Data.gov (United States)

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

  17. ptpn Terminal Aerodrome Forecast

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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...

  18. kblf Terminal Aerodrome Forecast

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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...

  19. panc Terminal Aerodrome Forecast

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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...

  20. kpbi Terminal Aerodrome Forecast

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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...

  1. kgdv Terminal Aerodrome Forecast

    Data.gov (United States)

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

  2. kcmx Terminal Aerodrome Forecast

    Data.gov (United States)

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

  3. kdls Terminal Aerodrome Forecast

    Data.gov (United States)

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

  4. koaj 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. krhi 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. kbpk 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. khuf 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. kbpi 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. ktrk Terminal Aerodrome Forecast

    Data.gov (United States)

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

  10. kwmc Terminal Aerodrome Forecast

    Data.gov (United States)

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

  11. katy 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. tjmz 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. kdet 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. kcxp Terminal Aerodrome Forecast

    Data.gov (United States)

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

  15. kbur 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)

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  7. kdsm Terminal Aerodrome Forecast

    Data.gov (United States)

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

  8. kpsm Terminal Aerodrome Forecast

    Data.gov (United States)

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

  9. kgrb Terminal Aerodrome Forecast

    Data.gov (United States)

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

  10. kgmu Terminal Aerodrome Forecast

    Data.gov (United States)

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

  11. papg Terminal Aerodrome Forecast

    Data.gov (United States)

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

  12. kbgm Terminal Aerodrome Forecast

    Data.gov (United States)

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

  13. pamc Terminal Aerodrome Forecast

    Data.gov (United States)

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

  14. klrd Terminal Aerodrome Forecast

    Data.gov (United States)

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

  15. ksan Terminal Aerodrome Forecast

    Data.gov (United States)

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

  16. patk Terminal Aerodrome Forecast

    Data.gov (United States)

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

  17. kowb Terminal Aerodrome Forecast

    Data.gov (United States)

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

  18. klru Terminal Aerodrome Forecast

    Data.gov (United States)

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

  19. kfxe Terminal Aerodrome Forecast

    Data.gov (United States)

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

  20. kjct Terminal Aerodrome Forecast

    Data.gov (United States)

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

  1. kcrg Terminal Aerodrome Forecast

    Data.gov (United States)

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

  2. paaq Terminal Aerodrome Forecast

    Data.gov (United States)

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

  3. kaex Terminal Aerodrome Forecast

    Data.gov (United States)

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

  4. klbx Terminal Aerodrome Forecast

    Data.gov (United States)

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

  5. kmia Terminal Aerodrome Forecast

    Data.gov (United States)

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

  6. kpit Terminal Aerodrome Forecast

    Data.gov (United States)

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

  7. kcrw Terminal Aerodrome Forecast

    Data.gov (United States)

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

  8. paen Terminal Aerodrome Forecast

    Data.gov (United States)

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

  9. kast Terminal Aerodrome Forecast

    Data.gov (United States)

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

  10. kuin Terminal Aerodrome Forecast

    Data.gov (United States)

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

  11. kmht Terminal Aerodrome Forecast

    Data.gov (United States)

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

  12. kcys Terminal Aerodrome Forecast

    Data.gov (United States)

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

  13. 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...

  14. pakn Terminal Aerodrome Forecast

    Data.gov (United States)

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

  15. pabt Terminal Aerodrome Forecast

    Data.gov (United States)

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

  16. krdg Terminal Aerodrome Forecast

    Data.gov (United States)

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

  17. khdn Terminal Aerodrome Forecast

    Data.gov (United States)

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

  18. kjac Terminal Aerodrome Forecast

    Data.gov (United States)

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

  19. kphx Terminal Aerodrome Forecast

    Data.gov (United States)

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

  20. L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting

    Science.gov (United States)

    Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i...

  1. Evaluation of the Weather Research and Forecasting mesoscale model for GABLS3: Impact of boundary-layer schemes, boundary conditions and spin-up

    NARCIS (Netherlands)

    Kleczek, M.A.; Steeneveld, G.J.; Holtslag, A.A.M.

    2014-01-01

    We evaluated the performance of the three-dimensional Weather Research and Forecasting (WRF) mesoscale model, specifically the performance of the planetary boundary-layer (PBL) parametrizations. For this purpose, Cabauw tower observations were used, with the study extending beyond the third GEWEX

  2. Effects of Ichthyophonus hoferi on condition indices and blood chemistry of experimentally infected rainbow trout (Oncorhynchus mykiss).

    Science.gov (United States)

    Rand, T G; Cone, D K

    1990-07-01

    Body condition, hepatosomatic index and blood chemistry of Oncorhynchus mykiss experimentally infected with a tissue dwelling fish pathogenic fungus, Ichthyophonus hoferi, were monitored over a 6 wk period. This was to determine whether the infection constituted a stress manifest by changes in the hypothalamic-pituitary interrenal axis, and especially plasma cortisol levels. Infection caused anaemia and leucopenia but did not change the condition, hepatosomatic indices, or plasma chloride, cholesterol, cortisol, creatinine, glucose, osmolarity, potassium, total protein, sodium and T4. It is suggested that increased cortisol levels may not be a normal component of the stress response of fish to disease caused by invasive infectious agents.

  3. Robust forecast comparison

    OpenAIRE

    Jin, Sainan; Corradi, Valentina; Swanson, Norman

    2015-01-01

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

  4. 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...... driven by the variability of the conditional mean and portfolio weights. Simulations and a small empirical study suggest that the bias can be empirically substantial and lead to distortions in forecast evaluation. An important implication is that forecasting superiority of models using high frequency...

  5. Bayesian analyses of seasonal runoff forecasts

    Science.gov (United States)

    Krzysztofowicz, R.; Reese, S.

    1991-12-01

    Forecasts of seasonal snowmelt runoff volume provide indispensable information for rational decision making by water project operators, irrigation district managers, and farmers in the western United States. Bayesian statistical models and communication frames have been researched in order to enhance the forecast information disseminated to the users, and to characterize forecast skill from the decision maker's point of view. Four products are presented: (i) a Bayesian Processor of Forecasts, which provides a statistical filter for calibrating the forecasts, and a procedure for estimating the posterior probability distribution of the seasonal runoff; (ii) the Bayesian Correlation Score, a new measure of forecast skill, which is related monotonically to the ex ante economic value of forecasts for decision making; (iii) a statistical predictor of monthly cumulative runoffs within the snowmelt season, conditional on the total seasonal runoff forecast; and (iv) a framing of the forecast message that conveys the uncertainty associated with the forecast estimates to the users. All analyses are illustrated with numerical examples of forecasts for six gauging stations from the period 1971 1988.

  6. STUDY OF INDICATORS OF AMYLOLYTIC ACTIVITY OF MOUTH FLUID OF DENTAL HEALTHCARE WORKERS UNDER VARIOUS CONDITIONS OF PROFESSIONAL ACTIVITY

    Directory of Open Access Journals (Sweden)

    S. V. Melnikova

    2014-06-01

    Full Text Available Amylolytic activity indicators of oral liquid of dentists in different conditions of professional activity at outpatient dental care and lectures have been studied. We observed an increase in amylolytic activity of oral liquid of dentists men and women after outpatient dental care, that indicates the activation of the sympathetic-adrenal system in response to the professional stress. We also identified the gender-specific response to the α-amylase load in professional dentists: male amylolytic activity of oral fluid was higher than female. In the group of male and female dentist cadets we registered the decrease of amylolytic activity of oral fluid. The correlation analysis revealed a negative relationship between the level of α-amylase and rigidity in a group of male dentists. We suggested that male dentists reduced their adaptation to the psychosocial conditions under job stress. Keywords: dentist, professional activity, professional stress, outpatient dental care, lectures, amylolytic activity of oral fluid.

  7. A study of different indicators of Maillard reaction with whey proteins and different carbohydrates under adverse storage conditions.

    Science.gov (United States)

    Leiva, Graciela E; Naranjo, Gabriela B; Malec, Laura S

    2017-01-15

    This study examined different indicators of each stage of Maillard reaction under adverse storage conditions in a system with whey proteins and lactose or glucose. The analysis of lysine loss by the o-phthaldialdehyde method can be considered a good indicator of the early stage, showing considerable differences in reactivity when systems with mono and disaccharides were analyzed. Capillary electrophoresis proved to be a sensitive method for evaluating the extent of glycosylation of the native proteins, providing valuable information when the loss of lysine was not significant. The estimation of the Amadori compound from the determination of total 5-hydroxymethyl-2-furfuraldehyde would have correlate well with reactive lysine content if the advanced stages of the reaction had not been reached. For assessing the occurrence of the intermediate and final stages, the measurement of free 5-hydroxymethyl-2-furfuraldehyde and color, proved not to be suitable for storage conditions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. On the reliability of seasonal climate forecasts

    Science.gov (United States)

    Weisheimer, A.; Palmer, T. N.

    2014-01-01

    Seasonal climate forecasts are being used increasingly across a range of application sectors. A recent UK governmental report asked: how good are seasonal forecasts on a scale of 1–5 (where 5 is very good), and how good can we expect them to be in 30 years time? Seasonal forecasts are made from ensembles of integrations of numerical models of climate. We argue that ‘goodness’ should be assessed first and foremost in terms of the probabilistic reliability of these ensemble-based forecasts; reliable inputs are essential for any forecast-based decision-making. We propose that a ‘5’ should be reserved for systems that are not only reliable overall, but where, in particular, small ensemble spread is a reliable indicator of low ensemble forecast error. We study the reliability of regional temperature and precipitation forecasts of the current operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts, universally regarded as one of the world-leading operational institutes producing seasonal climate forecasts. A wide range of ‘goodness’ rankings, depending on region and variable (with summer forecasts of rainfall over Northern Europe performing exceptionally poorly) is found. Finally, we discuss the prospects of reaching ‘5’ across all regions and variables in 30 years time. PMID:24789559

  9. Forecaster Behaviour and Bias in Macroeconomic Forecasts

    OpenAIRE

    Roy Batchelor

    2007-01-01

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

  10. Verification of ECMWF and ECMWF/MACC's global and direct irradiance forecasts with respect to solar electricity production forecasts

    Directory of Open Access Journals (Sweden)

    M. Schroedter-Homscheidt

    2017-02-01

    Full Text Available The successful electricity grid integration of solar energy into day-ahead markets requires at least hourly resolved 48 h forecasts. Technologies as photovoltaics and non-concentrating solar thermal technologies make use of global horizontal irradiance (GHI forecasts, while all concentrating technologies both from the photovoltaic and the thermal sector require direct normal irradiances (DNI. The European Centre for Medium-Range Weather Forecasts (ECMWF has recently changed towards providing direct as well as global irradiances. Additionally, the MACC (Monitoring Atmospheric Composition & Climate near-real time services provide daily analysis and forecasts of aerosol properties in preparation of the upcoming European Copernicus programme. The operational ECMWF/IFS (Integrated Forecast System forecast system will in the medium term profit from the Copernicus service aerosol forecasts. Therefore, within the MACC‑II project specific experiment runs were performed allowing for the assessment of the performance gain of these potential future capabilities. Also the potential impact of providing forecasts with hourly output resolution compared to three-hourly resolved forecasts is investigated. The inclusion of the new aerosol climatology in October 2003 improved both the GHI and DNI forecasts remarkably, while the change towards a new radiation scheme in 2007 only had minor and partly even unfavourable impacts on the performance indicators. For GHI, larger RMSE (root mean square error values are found for broken/overcast conditions than for scattered cloud fields. For DNI, the findings are opposite with larger RMSE values for scattered clouds compared to overcast/broken cloud situations. The introduction of direct irradiances as an output parameter in the operational IFS version has not resulted in a general performance improvement with respect to biases and RMSE compared to the widely used Skartveit et al. (1998 global to direct irradiance

  11. Development history and bibliography of the US Forest Service crown-condition indicator for forest health monitoring.

    Science.gov (United States)

    Randolph, KaDonna C

    2013-06-01

    Comprehensive assessment of individual-tree crown condition by the US Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program has its origins in the concerns about widespread forest decline in Europe and North America that developed in the late 1970s and early 1980s. Programs such as the US National Acid Precipitation Assessment Program, US National Vegetation Survey, Canadian Acid Rain National Early Warning System, and joint US-Canadian North American Sugar Maple Decline Project laid the groundwork for the development of the US Forest Service crown-condition indicator. The crown-condition assessment protocols were selected and refined through literature review, peer review, and field studies in several different forest types during the late 1980s and early 1990s. Between 1980 and 2011, 126 publications relating specifically to the crown-condition indicator were added to the literature. The majority of the articles were published by the US Department of Agriculture, Forest Service or other State or Federal government agency, and more than half were published after 2004.

  12. Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts

    Science.gov (United States)

    Schmidt, Thomas; Kalisch, John; Lorenz, Elke; Heinemann, Detlev

    2016-03-01

    Clouds are the dominant source of small-scale variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the worldwide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a very short term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A 2-month data set with images from one sky imager and high-resolution GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series into different cloud scenarios. Overall, the sky-imager-based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depends strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1-2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability, which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

  13. Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts

    Directory of Open Access Journals (Sweden)

    T. Schmidt

    2016-03-01

    Full Text Available Clouds are the dominant source of small-scale variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the worldwide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a very short term global horizontal irradiance (GHI forecast experiment based on hemispheric sky images. A 2-month data set with images from one sky imager and high-resolution GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series into different cloud scenarios. Overall, the sky-imager-based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depends strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1–2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability, which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

  14. The relationships between environmental and physiological heat stress indices in Muslim women under the controlled thermal conditions

    Directory of Open Access Journals (Sweden)

    Peymaneh Habibi

    2015-01-01

    Full Text Available Aims: The aim of this study was to evaluate the relationship between environmental and physiological heat stress indices based on heart rate (HR, oral temperature for the estimation of heat strain, in veiled women in hot-dry condition in the climate chamber. Materials and Methods: The experimental study was carried out on 36 healthy Muslim women in hot-dry climatic conditions (wet bulb globe temperature (WBGT = 22-32°C in low workload for 2 h. The HR, oral temperature and WBGT index were measured. The obtained data were analyzed using descriptive statistics and Pearson correlation tests. Results: The results of the Pearson test indicated that physiological strain index was a high correlation (r = 0.975 with WBGT index (P < 0.05. Also, there was a good correlation among WBGT and HR (r = 0.779 and oral temperature (r = 0.981. Conclusion: The findings of this study illustrated that there is a good correlation between environmental and physiological heat stress indices in veiled women with Islamic clothing at the low workload over the action limit (WBGT = 31°C. So that it can be concluded that the WBGT 22-32°C is a good indicator of the heat strain in veiled women with Islamic clothing.

  15. Machine Learning Algorithms for the Forecasting of  Wastewater Quality Indicators

    Directory of Open Access Journals (Sweden)

    Francesco Granata

    2017-02-01

    Full Text Available Stormwater runoff is often contaminated by human activities. Stormwater discharge into  water bodies significantly contributes to environmental pollution. The choice of suitable treatment  technologies is dependent on the pollutant concentrations. Wastewater quality indicators such as  biochemical oxygen demand (BOD5, chemical oxygen demand (COD, total suspended solids (TSS,  and total dissolved solids (TDS give a measure of the main pollutants. The aim of this study is to  provide an indirect methodology for the estimation of the main wastewater quality indicators, based  on some characteristics of the drainage basin. The catchment is seen as a black box: the physical  processes of accumulation, washing, and transport of pollutants are not mathematically described.  Two models deriving from studies on artificial intelligence have been used in this research: Support  Vector Regression (SVR and Regression Trees (RT. Both the models showed robustness, reliability,  and high generalization capability. However, with reference to coefficient of determination R2 and  root‐mean square error, Support Vector Regression showed a better performance than Regression  Tree in predicting TSS, TDS, and COD. As regards BOD5, the two models showed a comparable  performance. Therefore, the considered machine learning algorithms may be useful for providing  an estimation of the values to be considered for the sizing of the treatment units in absence of direct  measures.

  16. Ionospheric scintillation forecasting model based on NN-PSO technique

    Science.gov (United States)

    Sridhar, M.; Venkata Ratnam, D.; Padma Raju, K.; Sai Praharsha, D.; Saathvika, K.

    2017-09-01

    The forecasting and modeling of ionospheric scintillation effects are crucial for precise satellite positioning and navigation applications. In this paper, a Neural Network model, trained using Particle Swarm Optimization (PSO) algorithm, has been implemented for the prediction of amplitude scintillation index (S4) observations. The Global Positioning System (GPS) and Ionosonde data available at Darwin, Australia (12.4634° S, 130.8456° E) during 2013 has been considered. The correlation analysis between GPS S4 and Ionosonde drift velocities (hmf2 and fof2) data has been conducted for forecasting the S4 values. The results indicate that forecasted S4 values closely follow the measured S4 values for both the quiet and disturbed conditions. The outcome of this work will be useful for understanding the ionospheric scintillation phenomena over low latitude regions.

  17. SHORT-TERM FORECASTING OF MORTGAGE LENDING

    Directory of Open Access Journals (Sweden)

    Irina V. Orlova

    2013-01-01

    Full Text Available The article considers the methodological and algorithmic problems arising in modeling and forecasting of time series of mortgage loans. Focuses on the processes of formation of the levels of time series of mortgage loans and the problem of choice and identification of models in the conditions of small samples. For forecasting options are selected and implemented a model of autoregressive and moving average, which allowed to obtain reliable forecasts.

  18. Value of Forecaster in the Loop

    Science.gov (United States)

    2014-09-01

    forecast system IFR instrument flight rules IMC instrument meteorological conditions LAMP Localized Aviation Model Output Statistics Program METOC...obtaining valuable experience. Additional factors have impacted the Navy weather forecast process. There has been a the realignment of the meteorology...forecasts that are assessed, it may be a relatively small number that have direct impact on the decision-making process. Whether the value is minimal or

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

    Directory of Open Access Journals (Sweden)

    J. Rhee

    2016-06-01

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

  20. 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....

  1. Space weather monitoring and forecasting in South America: products from the user requests to the development of regional magnetic indices and GNSS vertical error maps

    Science.gov (United States)

    Denardini, Clezio Marcos; Padilha, Antonio; Takahashi, Hisao; Souza, Jonas; Mendes, Odim; Batista, Inez S.; SantAnna, Nilson; Gatto, Rubens; Costa, D. Joaquim

    . Recently, we have release brand new products, among them, some regional magnetic indices and the GNSS vertical error map over South America. Contacting Author: C. M. Denardini (clezio.denardin@inpe.br)

  2. Forecasting olive crop yields based on long-term aero biological data series and bio climatic conditions for the southern Iberian Peninsula

    Energy Technology Data Exchange (ETDEWEB)

    Aguilera, F.; Ruiz-Valenzuela, L.

    2014-06-01

    In the present study, bio-meteorological models for predicting olive-crop production in the southern Iberian Peninsula were developed. These covered a 16-year period: 1994-2009. The forecasting models were constructed using the partial least-squares regression method, taking the annual olive yield as the dependent variable, and both aero biological and meteorological parameters as the independent variables. Two regression models were built for the prediction of crop production prior to the final harvest at two different times of the year: July and November. The percentage variance explained by the models was between 83% and 93%. Through these forecasting models, the main factors that influence olive-crop yield were identified. Pollen index and accumulated precipitation, especially as rain recorded during the pre-flowering months, were the most important parameters for providing an explanation of fluctuations in fruit production. The temperature recorded during the two months preceding budburst was another important variable, which showed positive effects on the final yield. The July model that provides accurate predictions of fruit production eight months prior to the final harvest is proposed as an optimal model to forecast fruit produced by olive trees in western Mediterranean areas. (Author)

  3. National Forecast Charts

    Science.gov (United States)

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

  4. 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,

  5. Investigation of Spiral Bevel Gear Condition Indicator Validation via AC-29-2C Using Fielded Rotorcraft HUMS Data

    Science.gov (United States)

    Dempsey, Paula J.; Wade, Daniel R.; Antolick, Lance J.; Thomas, Josiah

    2014-01-01

    This report presents the analysis of gear condition indicator data collected on a helicopter when damage occurred in spiral bevel gears. The purpose of the data analysis was to use existing in-service helicopter HUMS flight data from faulted spiral bevel gears as a Case Study, to better understand the differences between HUMS data response in a helicopter and a component test rig, the NASA Glenn Spiral Bevel Gear Fatigue Rig. The reason spiral bevel gear sets were chosen to demonstrate differences in response between both systems was the availability of the helicopter data and the availability of a test rig that was capable of testing spiral bevel gear sets to failure. The objective of the analysis presented in this paper was to re-process helicopter HUMS data with the same analysis techniques applied to the spiral bevel rig test data. The damage modes experienced in the field were mapped to the failure modes created in the test rig. A total of forty helicopters were evaluated. Twenty helicopters, or tails, experienced damage to the spiral bevel gears in the nose gearbox. Vibration based gear condition indicators data was available before and after replacement. The other twenty tails had no known anomalies in the nose gearbox within the time frame of the datasets. These twenty tails were considered the baseline dataset. The HUMS gear condition indicators evaluated included gear condition indicators (CI) Figure of Merit 4 (FM4), Root Mean Square (RMS) or Diagnostic Algorithm 1 (DA1) and +/- 3 Sideband Index (SI3). Three additional condition indicators, not currently calculated on-board, were calculated from the archived data. These three indicators were +/- 1 Sideband Index (SI1), the DA1 of the difference signal (DiffDA1) and the peak-to-peak of the difference signal (DP2P). Results found the CI DP2P, not currently available in the on-board HUMS, performed the best, responding to varying levels of damage on thirteen of the fourteen helicopters evaluated. Two

  6. [Effect of indications and pre-existing conditions on the result of McDonald's cervix-closure surgery].

    Science.gov (United States)

    Avar, Z; Tóth, B; Zacher, P

    1979-01-01

    Authors have performed the McDonald cerclage operation on 172 gravidae because of cervical incompetence. From these pregnancies 80.2 per cent of the infants have survived over the sixth day. While with operations performed on the basis of extended indications for surgery an effect of 56.5 per cent was achieved, it was in cases of classical ones 92.8 per cent. Two complicated cases are reported caused by blastospores or bacteria respectively, isolated also in the vaginal secretion which have ascended into the uterine cavity. Both cases resulted in fetal death and in a septic condition of the mother. It is emphasized that the normal vaginal bioflora is essential condition for the cervical suture.

  7. Forecasting freight flows

    DEFF Research Database (Denmark)

    Lyk-Jensen, Stéphanie

    2011-01-01

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

  8. Investigation of Spiral Bevel Gear Condition Indicator Validation Via AC-29-2C Using Damage Progression Tests

    Science.gov (United States)

    Dempsey, Paula J.

    2014-01-01

    This report documents the results of spiral bevel gear rig tests performed under a NASA Space Act Agreement with the Federal Aviation Administration (FAA) to support validation and demonstration of rotorcraft Health and Usage Monitoring Systems (HUMS) for maintenance credits via FAA Advisory Circular (AC) 29-2C, Section MG-15, Airworthiness Approval of Rotorcraft (HUMS) (Ref. 1). The overarching goal of this work was to determine a method to validate condition indicators in the lab that better represent their response to faults in the field. Using existing in-service helicopter HUMS flight data from faulted spiral bevel gears as a "Case Study," to better understand the differences between both systems, and the availability of the NASA Glenn Spiral Bevel Gear Fatigue Rig, a plan was put in place to design, fabricate and test comparable gear sets with comparable failure modes within the constraints of the test rig. The research objectives of the rig tests were to evaluate the capability of detecting gear surface pitting fatigue and other generated failure modes on spiral bevel gear teeth using gear condition indicators currently used in fielded HUMS. Nineteen final design gear sets were tested. Tables were generated for each test, summarizing the failure modes observed on the gear teeth for each test during each inspection interval and color coded based on damage mode per inspection photos. Gear condition indicators (CI) Figure of Merit 4 (FM4), Root Mean Square (RMS), +/- 1 Sideband Index (SI1) and +/- 3 Sideband Index (SI3) were plotted along with rig operational parameters. Statistical tables of the means and standard deviations were calculated within inspection intervals for each CI. As testing progressed, it became clear that certain condition indicators were more sensitive to a specific component and failure mode. These tests were clustered together for further analysis. Maintenance actions during testing were also documented. Correlation coefficients were

  9. Forecasting distribution of numbers of large fires

    Science.gov (United States)

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

    2014-01-01

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

  10. Changes in the blood indicators and body condition of high yielding Holstein cows with retained placenta and ketosis

    Directory of Open Access Journals (Sweden)

    Zenon Nogalski

    2012-01-01

    Full Text Available The aim of this study was to determine the effect of changes in body condition in the dry period and the early lactation period on the incidence of retained placenta and ketosis in 94 high-yielding Holstein-Friesian cows. Body condition scoring was performed every two weeks from the beginning of the dry period until week 18 of lactation. Blood for the measuring of indicators of metabolism was sampled in weeks 1 and 2 ante partum and in weeks 1, 2, 3, 7 and 15 post partum. Retained placenta was reported in 11 cows, and ketosis was diagnosed in 18 animals. One week ante partum, the serum profile of cows diagnosed with ketosis during lactation revealed 0.52 mmol/l β-hydroxybutyric acid and 0.29 mmol/l non-esterified fatty acids on average. One week post partum, the serum profile of cows with ketosis revealed 1.59 mmol/l β-hydroxybutyric acid and 1.09 mmol/l non-esterified fatty acids and cows with retained placenta 1.65 and 1.41, respectively. From the week 5 ante partum to the point of lowest body condition the average body condition loss reached 1.4 points in cows with retained placenta, 1.1 points in cows with ketosis, and 0.8 points in healthy cows. Retained placenta and ketosis increased significantly conception rates by 0.47 and 0.50, respectively. Our results show that monitoring changes in the body condition and non-esterified fatty acids and β-hydroxybutyric acid blood levels in high-yielding cows in the transition period, followed by taking relevant disease-control measures, may be effective in reducing the incidence of retained placenta and ketosis in dairy cattle herds.

  11. The forecaster's added value

    Science.gov (United States)

    Turco, M.; Milelli, M.

    2009-09-01

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

  12. The Impact of Weather Forecasts of Various Lead Times on Snowmaking Decisions Made for the 2010 Vancouver Olympic Winter Games

    Science.gov (United States)

    Doyle, Chris

    2014-01-01

    The Vancouver 2010 Winter Olympics were held from 12 to 28 February 2010, and the Paralympic events followed 2 weeks later. During the Games, the weather posed a grave threat to the viability of one venue and created significant complications for the event schedule at others. Forecasts of weather with lead times ranging from minutes to days helped organizers minimize disruptions to sporting events and helped ensure all medal events were successfully completed. Of comparable importance, however, were the scenarios and forecasts of probable weather for the winter in advance of the Games. Forecasts of mild conditions at the time of the Games helped the Games' organizers mitigate what would have been very serious potential consequences for at least one venue. Snowmaking was one strategy employed well in advance of the Games to prepare for the expected conditions. This short study will focus on how operational decisions were made by the Games' organizers on the basis of both climatological and snowmaking forecasts during the pre-Games winter. An attempt will be made to quantify, economically, the value of some of the snowmaking forecasts made for the Games' operators. The results obtained indicate that although the economic value of the snowmaking forecast was difficult to determine, the Games' organizers valued the forecast information greatly. This suggests that further development of probabilistic forecasts for applications like pre-Games snowmaking would be worthwhile.

  13. Effect of design and operational conditions on the performance of subsurface flow treatment wetlands: Emerging organic contaminants as indicators.

    Science.gov (United States)

    Kahl, Stefanie; Nivala, Jaime; van Afferden, Manfred; Müller, Roland A; Reemtsma, Thorsten

    2017-11-15

    Six pilot-scale subsurface flow treatment wetlands loaded with primary treated municipal wastewater were monitored over one year for classical wastewater parameters and a set of emerging organic compounds (EOCs) serving as process indicators for biodegradation: caffeine, ibuprofen, naproxen, benzotriazole, diclofenac, acesulfame, and carbamazepine. The wetland technologies investigated included conventional horizontal flow, unsaturated vertical flow (single and two-stage), horizontal flow with aeration, vertical flow with aeration, and reciprocating. Treatment efficiency for classical wastewater parameters and EOCs generally increased with increasing design complexity and dissolved oxygen concentrations. The two aerated wetlands and the two-stage vertical flow system showed the highest EOC removal, and the best performance in warm season and most robust performance in the cold season. These three systems performed better than the adjacent conventional WWTP with respect to EOC removal. Acesulfame was observed to be removed (>90%) by intensified wetland systems and with use of a tertiary treatment sand filter during the warm season. Elevated temperature and high oxygen content (aerobic conditions) proved beneficial for EOC removal. For EOCs of moderate to low biodegradability, the co-occurrence of aerobic conditions and low content of readily available carbon appears essential for efficient removal. Such conditions occurred in the aerated systems and with use of a tertiary treatment sand filter. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Correlation analysis of indicators of physical condition, health and physical fitness of soldiers involved in peacekeeping operations

    Directory of Open Access Journals (Sweden)

    S.S. Fedak

    2014-01-01

    Full Text Available Purpose: to identify the main physical qualities, which positively influence the physical state, health and military - professional career peacekeepers when performing tasks in different climatic conditions. Material : the study involved 98 military service under the contract the first age group (men. Analyzed contingent divided into groups according to climatic conditions of service: in the highlands - 37 person, in hot climates - 35 person, in towns and areas with limited space - 26 person. A correlation analysis between the results of running 100 meters, pulling, running 3 kilometre and indicators of the health and physical condition of the soldiers. Results : It was determined that the participation in peacekeeping missions in mountainous areas and in areas with a hot climate is the quality of the underlying physical endurance. With the participation in peacekeeping missions in populated areas and in areas with limited space - this is the strength and speed. Conclusions : on improving these physical qualities should focus during lessons in physical training of peacekeepers in the centers of immediate preparation for missions.

  15. Analysts' earnings forecasts and international asset allocation

    NARCIS (Netherlands)

    Huijgen, Carel; Plantinga, Auke

    1999-01-01

    The aim of this paper is to investigate whether financial analysts’ earnings forecasts are informative from the viewpoint of allocating investments across different stock markets. Therefore we develop a country forecast indicator reflecting the analysts’ prospects for specific stock markets. The

  16. 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

  17. Flood forecasting and uncertainty of precipitation forecasts

    International Nuclear Information System (INIS)

    Kobold, Mira; Suselj, Kay

    2004-01-01

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

  18. Forecasting Performance of Asymmetric GARCH Stock Market Volatility Models

    Directory of Open Access Journals (Sweden)

    Hojin Lee

    2009-12-01

    Full Text Available We investigate the asymmetry between positive and negative returns in their effect on conditional variance of the stock market index and incorporate the characteristics to form an out-of-sample volatility forecast. Contrary to prior evidence, however, the results in this paper suggest that no asymmetric GARCH model is superior to basic GARCH(1,1 model. It is our prior knowledge that, for equity returns, it is unlikely that positive and negative shocks have the same impact on the volatility. In order to reflect this intuition, we implement three diagnostic tests for volatility models: the Sign Bias Test, the Negative Size Bias Test, and the Positive Size Bias Test and the tests against the alternatives of QGARCH and GJR-GARCH. The asymmetry test results indicate that the sign and the size of the unexpected return shock do not influence current volatility differently which contradicts our presumption that there are asymmetric effects in the stock market volatility. This result is in line with various diagnostic tests which are designed to determine whether the GARCH(1,1 volatility estimates adequately represent the data. The diagnostic tests in section 2 indicate that the GARCH(1,1 model for weekly KOSPI returns is robust to the misspecification test. We also investigate two representative asymmetric GARCH models, QGARCH and GJR-GARCH model, for our out-of-sample forecasting performance. The out-of-sample forecasting ability test reveals that no single model is clearly outperforming. It is seen that the GJR-GARCH and QGARCH model give mixed results in forecasting ability on all four criteria across all forecast horizons considered. Also, the predictive accuracy test of Diebold and Mariano based on both absolute and squared prediction errors suggest that the forecasts from the linear and asymmetric GARCH models need not be significantly different from each other.

  19. Analysis of the indices of thermal comfort for the conditions of the Mexican Republic; Analisis de los indices de confort termico para las condiciones de la republica mexicana

    Energy Technology Data Exchange (ETDEWEB)

    Fuentes Freixanet, Victor; Rodriguez Viqueira, Manuel [Universidad Autonoma Metropolitana - Unidad Azcapotzalco (Mexico)

    2009-07-15

    The objective of this article is to analyze different indices of thermal comfort for the Mexican Republic. Among them the Fanger (PMV and PPD) physiological methods of comfort and the new effective temperature index are included. The standard effective temperature (SET), as well as the adaptive methods of Humphreys and Nicol, Auliciems, De Dear and Brager. A comparative analysis is done of the different indices through thematic maps determined by interpolation, using a climatic data base of 700 cities obtained from the observatories and stations of the National Meteorological Service. This article pretends to establish general criteria of the thermal comfort to later define design strategies for each one of the climatic regions of the Mexican Republic. [Spanish] El objetivo de este articulo es analizar distintos indices de confort termico para la Republica Mexicana. Entre ellos se incluyen los metodos fisiologicos de confort de Fanger (PMV y PPD), el indice de nueva temperatura efectiva. La temperatura efectiva estandar (SET), asi como los metodos adaptativos de Humphreys y Nicol, Auliciems, De Dear y Brager. Se hace un analisis comparativo de los distintos indices a traves de mapas tematicos determinados por interpolacion, usando una base de datos climaticos de 700 ciudades obtenidos de los observatorios y estaciones del Servicio Meteorologico Nacional. Este articulo presenta establecer criterios generales del confort termico para posteriormente definir estrategias de diseno para cada una de las regiones climaticas de la Republica Mexicana.

  20. Entropy Econometrics for combining regional economic forecasts: A Data-Weighted Prior Estimator

    Science.gov (United States)

    Fernández-Vázquez, Esteban; Moreno, Blanca

    2017-10-01

    Forecast combination has been studied in econometrics for a long time, and the literature has shown the superior performance of forecast combination over individual predictions. However, there is still controversy on which is the best procedure to specify the forecast weights. This paper explores the possibility of using a procedure based on Entropy Econometrics, which allows setting the weights for the individual forecasts as a mixture of different alternatives. In particular, we examine the ability of the Data-Weighted Prior Estimator proposed by Golan (J Econom 101(1):165-193, 2001) to combine forecasting models in a context of small sample sizes, a relative common scenario when dealing with time series for regional economies. We test the validity of the proposed approach using a simulation exercise and a real-world example that aims at predicting gross regional product growth rates for a regional economy. The forecasting performance of the Data-Weighted Prior Estimator proposed is compared with other combining methods. The simulation results indicate that in scenarios of heavily ill-conditioned datasets the approach suggested dominates other forecast combination strategies. The empirical results are consistent with the conclusions found in the numerical experiment.

  1. Development of visibility forecasting modeling framework for the Lower Fraser Valley of British Columbia using Canada's Regional Air Quality Deterministic Prediction System.

    Science.gov (United States)

    So, Rita; Teakles, Andrew; Baik, Jonathan; Vingarzan, Roxanne; Jones, Keith

    2018-05-01

    Visibility degradation, one of the most noticeable indicators of poor air quality, can occur despite relatively low levels of particulate matter when the risk to human health is low. The availability of timely and reliable visibility forecasts can provide a more comprehensive understanding of the anticipated air quality conditions to better inform local jurisdictions and the public. This paper describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada's operational Regional Air Quality Deterministic Prediction System (RAQDPS) for the Lower Fraser Valley of British Columbia. A baseline model (GM-IMPROVE) was constructed using the revised IMPROVE algorithm based on unprocessed forecasts from the RAQDPS. Three additional prototypes (UMOS-HYB, GM-MLR, GM-RF) were also developed and assessed for forecast performance of up to 48 hr lead time during various air quality and meteorological conditions. Forecast performance was assessed by examining their ability to provide both numerical and categorical forecasts in the form of 1-hr total extinction and Visual Air Quality Ratings (VAQR), respectively. While GM-IMPROVE generally overestimated extinction more than twofold, it had skill in forecasting the relative species contribution to visibility impairment, including ammonium sulfate and ammonium nitrate. Both statistical prototypes, GM-MLR and GM-RF, performed well in forecasting 1-hr extinction during daylight hours, with correlation coefficients (R) ranging from 0.59 to 0.77. UMOS-HYB, a prototype based on postprocessed air quality forecasts without additional statistical modeling, provided reasonable forecasts during most daylight hours. In terms of categorical forecasts, the best prototype was approximately 75 to 87% correct, when forecasting for a condensed three-category VAQR. A case study, focusing on a poor visual air quality yet low Air Quality Health Index episode

  2. A convection-allowing ensemble forecast based on the breeding growth mode and associated optimization of precipitation forecast

    Science.gov (United States)

    Li, Xiang; He, Hongrang; Chen, Chaohui; Miao, Ziqing; Bai, Shigang

    2017-10-01

    A convection-allowing ensemble forecast experiment on a squall line was conducted based on the breeding growth mode (BGM). Meanwhile, the probability matched mean (PMM) and neighborhood ensemble probability (NEP) methods were used to optimize the associated precipitation forecast. The ensemble forecast predicted the precipitation tendency accurately, which was closer to the observation than in the control forecast. For heavy rainfall, the precipitation center produced by the ensemble forecast was also better. The Fractions Skill Score (FSS) results indicated that the ensemble mean was skillful in light rainfall, while the PMM produced better probability distribution of precipitation for heavy rainfall. Preliminary results demonstrated that convection-allowing ensemble forecast could improve precipitation forecast skill through providing valuable probability forecasts. It is necessary to employ new methods, such as the PMM and NEP, to generate precipitation probability forecasts. Nonetheless, the lack of spread and the overprediction of precipitation by the ensemble members are still problems that need to be solved.

  3. Relationship between the pre- and postpartum body condition scores and periparturient indices and fertility in high-yielding dairy cows

    Directory of Open Access Journals (Sweden)

    Stefańska Barbara

    2016-03-01

    Full Text Available Introduction: The aim of this study was to investigate the relationship between body condition score (BCS determined on the dry-off day, calving day, and in the first month of lactation, its changes during the dry period and early lactation, and periparturient indices and fertility in high-producing dairy cows. Material and Methods: The experiment was conducted in two herds: A and B, located in Western Poland. The studies were conducted on 116 and 108 Polish Holstein-Friesian dairy cows respectively, with an average milk yield of >10 000 kg/305-day lactation. The experiment included the dry period (-56 d to the calving day, the calving day, and early lactation (from +1 to +56 d. The experimental factor was BCS (0 to 5-point scale. The BCS was performed by one person on day -56, on parturition day (in the first 12 h after calving and on day 30 of lactation. Results: A decrease in BCS (≥-0.25 in herd A during the dry period accelerated the planned calving period by 7.3 d. In the group of cows with BCS 3.50 in the first month of lactation (30 d resulted in the extension of uterine involution period (56 d. Improvement of BCS during the dry period shortened the anoestrus (60 d in herd A and the period of insemination service (60 d in herd B. However, in this group (IM BCS ≥ 0.25 of cows the day of the highest artificial insemination index (2.50 in herd B was analysed. Conclusion: The body condition on the dry-off day and at calving, as well as its deterioration in the first month of lactation, have a considerable effect on fertility indices in dairy cows, thus confirming the advisability of its regular monitoring during routine operations connected with the management of a dairy cattle herd.

  4. Uncertainty in dispersion forecasts using meteorological ensembles

    International Nuclear Information System (INIS)

    Chin, H N; Leach, M J

    1999-01-01

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

  5. ORIBATID MITES POPULATION’S STRUCTURE IN TECHNOGENIC AND NATURAL LANDSCAPES AS AN INDICATOR OF ECOSYSTEMS’ CONDITION

    Directory of Open Access Journals (Sweden)

    Shtirts A. D.

    2013-12-01

    Full Text Available Species composition and specific ecological structure of oribatid mites community in industrial site and buffer zone of «Artyomovsk nonferrous metal plant» and botanical nature sanctuary «Steppe Otradovskaya» were established. The ecological structure of «Artyomovsk nonferrous metal plant» area is perturbed, and typical for the anthropogenically-transformed ecosystems, and has low rates of average population density, wealth rate, ecological diversity indexes; it also has changed in dominance structure and life forms distribution. The oribatid community structure in the botanical nature sanctuary «Steppe Otradovskaya» during the spring period is typical for Donbass steppe conservations. In summer it resembles structurally in disrupted landscapes due to adverse edaphic conditions, occurring in Donbass in August. The integral sensitivity threshold indicator for oribatid mite communities shows that an environmental state of the technogenic area («Artyomovsk nonferrous metal plant» in summer and autumn is subnormal. The ecological status of «Steppe Otradovskaya» in spring can be considered as normal, and in the thalweg of the steppe gully as relatively favorable. During summer, the environmental condition of the study area is subnormal.

  6. Study of atmospheric condition during the heavy rain event in Bojonegoro using weather research and forecasting (WRF) model: case study 9 February 2017

    Science.gov (United States)

    Saragih, I. J. A.; Meygatama, A. G.; Sugihartati, F. M.; Sidauruk, M.; Mulsandi, A.

    2018-03-01

    During 2016, there are frequent heavy rains in the Bojonegoro region, one of which is rain on 9 February 2016. The occurrence of heavy rainfall can cause the floods that inundate the settlements, rice fields, roads, and public facilities. This makes it important to analyze the atmospheric conditions during the heavy rainfall events in Bojonegoro. One of the analytical methods that can be used is using WRF-Advanced Research WRF (WRF-ARW) model. This study was conducted by comparing the rain analysis from WRF-ARW model with the Himawari-8 satellite imagery. The data used are Final Analysis (FNL) data for the WRF-ARW model and infrared (IR) channel for Himawari-8 satellite imagery. The data are processed into the time-series images and then analyzed descriptively. The meteorological parameters selected to be analyzed are relative humidity, vortices, divergences, air stability index, and precipitation. These parameters are expected to indicate the existence of a convective activity in Bojonegoro during the heavy rainfall event. The Himawari-8 satellite imagery shows that there is a cluster of convective clouds in Bojonegoro during the heavy rainfall event. The lowest value of the cloud top temperature indicates that the cluster of convective clouds is a cluster of Cumulonimbus cloud (CB).

  7. Combining forecast weights: Why and how?

    Science.gov (United States)

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

    2012-09-01

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

  8. Modeling Chaotic Behavior of Chittagong Stock Indices

    Directory of Open Access Journals (Sweden)

    Shipra Banik

    2012-01-01

    Full Text Available Stock market prediction is an important area of financial forecasting, which attracts great interest to stock buyers and sellers, stock investors, policy makers, applied researchers, and many others who are involved in the capital market. In this paper, a comparative study has been conducted to predict stock index values using soft computing models and time series model. Paying attention to the applied econometric noises because our considered series are time series, we predict Chittagong stock indices for the period from January 1, 2005 to May 5, 2011. We have used well-known models such as, the genetic algorithm (GA model and the adaptive network fuzzy integrated system (ANFIS model as soft computing forecasting models. Very widely used forecasting models in applied time series econometrics, namely, the generalized autoregressive conditional heteroscedastic (GARCH model is considered as time series model. Our findings have revealed that the use of soft computing models is more successful than the considered time series model.

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

    Energy Technology Data Exchange (ETDEWEB)

    Puechl, K H

    1975-12-01

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

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

    International Nuclear Information System (INIS)

    Puechl, K.H.

    1975-01-01

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

  11. Forecasting of Currency Crises in East Asia

    Directory of Open Access Journals (Sweden)

    Chi-Young Song

    2005-06-01

    Full Text Available In this paper, we have developed a forecasting system for currency crisis in East Asia based on a signaling approach. Our system uses 15 monthly indicators of five East Asian countries including Indonesia, Korea, Malaysia, the Philippines and Thailand that were severely hit by the currency crisis in 1997. We investigate the performance of the system through deploying out-of-sample forecasting for the periods both before and after the 1997 East Asian currency crisis. Unlike the existing research based on the signaling approach, our out-of-sample forecasting does not fix the in-sample period. The out-of-sample forecasting between July 1995 and June 1997 shows that prior to breakout of the crisis, several indicators including real exchange rates and exports sent frequent warnings to all crisis-hit East Asian countries except the Philippines. This may indicate that a signaling-based early warning system for currency crisis could have been an useful method of forecasting the East Asian crisis. On the other hand, we also find that our forecasting system often generates warning signals during the out-of-sample period between July 1999 and June 2001. Since we have not observed any currency crisis in this region after 1998, these are all false alarms, indicating that our system may be seriously exposed to the type II error. We can, however, mitigate this problem if we adjust the optimal critical values of indicators depending on the preferences of forecasting system manager.

  12. Adapting National Water Model Forecast Data to Local Hyper-Resolution H&H Models During Hurricane Irma

    Science.gov (United States)

    Singhofen, P.

    2017-12-01

    The National Water Model (NWM) is a remarkable undertaking. The foundation of the NWM is a 1 square kilometer grid which is used for near real-time modeling and flood forecasting of most rivers and streams in the contiguous United States. However, the NWM falls short in highly urbanized areas with complex drainage infrastructure. To overcome these shortcomings, the presenter proposes to leverage existing local hyper-resolution H&H models and adapt the NWM forcing data to them. Gridded near real-time rainfall, short range forecasts (18-hour) and medium range forecasts (10-day) during Hurricane Irma are applied to numerous detailed H&H models in highly urbanized areas of the State of Florida. Coastal and inland models are evaluated. Comparisons of near real-time rainfall data are made with observed gaged data and the ability to predict flooding in advance based on forecast data is evaluated. Preliminary findings indicate that the near real-time rainfall data is consistently and significantly lower than observed data. The forecast data is more promising. For example, the medium range forecast data provides 2 - 3 days advanced notice of peak flood conditions to a reasonable level of accuracy in most cases relative to both timing and magnitude. Short range forecast data provides about 12 - 14 hours advanced notice. Since these are hyper-resolution models, flood forecasts can be made at the street level, providing emergency response teams with valuable information for coordinating and dispatching limited resources.

  13. Inflation Forecast Contracts

    OpenAIRE

    Gersbach, Hans; Hahn, Volker

    2012-01-01

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

  14. The potential predictability of fire danger provided by ECMWF forecast

    Science.gov (United States)

    Di Giuseppe, Francesca

    2017-04-01

    The European Forest Fire Information System (EFFIS), is currently being developed in the framework of the Copernicus Emergency Management Services to monitor and forecast fire danger in Europe. The system provides timely information to civil protection authorities in 38 nations across Europe and mostly concentrates on flagging regions which might be at high danger of spontaneous ignition due to persistent drought. The daily predictions of fire danger conditions are based on the US Forest Service National Fire Danger Rating System (NFDRS), the Canadian forest service Fire Weather Index Rating System (FWI) and the Australian McArthur (MARK-5) rating systems. Weather forcings are provided in real time by the European Centre for Medium range Weather Forecasts (ECMWF) forecasting system. The global system's potential predictability is assessed using re-analysis fields as weather forcings. The Global Fire Emissions Database (GFED4) provides 11 years of observed burned areas from satellite measurements and is used as a validation dataset. The fire indices implemented are good predictors to highlight dangerous conditions. High values are correlated with observed fire and low values correspond to non observed events. A more quantitative skill evaluation was performed using the Extremal Dependency Index which is a skill score specifically designed for rare events. It revealed that the three indices were more skilful on a global scale than the random forecast to detect large fires. The performance peaks in the boreal forests, in the Mediterranean, the Amazon rain-forests and southeast Asia. The skill-scores were then aggregated at country level to reveal which nations could potentiallty benefit from the system information in aid of decision making and fire control support. Overall we found that fire danger modelling based on weather forecasts, can provide reasonable predictability over large parts of the global landmass.

  15. Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

    Science.gov (United States)

    Seibert, Mathias; Merz, Bruno; Apel, Heiko

    2017-03-01

    The Limpopo Basin in southern Africa is prone to droughts which affect the livelihood of millions of people in South Africa, Botswana, Zimbabwe and Mozambique. Seasonal drought early warning is thus vital for the whole region. In this study, the predictability of hydrological droughts during the main runoff period from December to May is assessed using statistical approaches. Three methods (multiple linear models, artificial neural networks, random forest regression trees) are compared in terms of their ability to forecast streamflow with up to 12 months of lead time. The following four main findings result from the study. 1. There are stations in the basin at which standardised streamflow is predictable with lead times up to 12 months. The results show high inter-station differences of forecast skill but reach a coefficient of determination as high as 0.73 (cross validated). 2. A large range of potential predictors is considered in this study, comprising well-established climate indices, customised teleconnection indices derived from sea surface temperatures and antecedent streamflow as a proxy of catchment conditions. El Niño and customised indices, representing sea surface temperature in the Atlantic and Indian oceans, prove to be important teleconnection predictors for the region. Antecedent streamflow is a strong predictor in small catchments (with median 42 % explained variance), whereas teleconnections exert a stronger influence in large catchments. 3. Multiple linear models show the best forecast skill in this study and the greatest robustness compared to artificial neural networks and random forest regression trees, despite their capabilities to represent nonlinear relationships. 4. Employed in early warning, the models can be used to forecast a specific drought level. Even if the coefficient of determination is low, the forecast models have a skill better than a climatological forecast, which is shown by analysis of receiver operating characteristics

  16. Verification of Space Weather Forecasts using Terrestrial Weather Approaches

    Science.gov (United States)

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

    2015-12-01

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

  17. Positive autoantibodies to ZnT8 indicate elevated risk for additional autoimmune conditions in patients with Addison's disease.

    Science.gov (United States)

    Fichna, Marta; Rogowicz-Frontczak, Anita; Żurawek, Magdalena; Fichna, Piotr; Gryczyńska, Maria; Zozulińska-Ziółkiewicz, Dorota; Ruchała, Marek

    2016-07-01

    Autoimmune Addison's disease (AAD) associates with exceptional susceptibility to develop other autoimmune conditions, including type 1 diabetes (T1D), marked by positive serum autoantibodies to insulin (IAA), glutamic acid decarboxylase (GADA) and insulinoma-associated protein 2 (IA-2A). Zinc transporter 8 (ZnT8) is a new T1D autoantigen, encoded by the SLC30A8 gene. Its polymorphic variant rs13266634C/T seems associated with the occurrence of serum ZnT8 antibodies (ZnT8A). This study was designed to determine the prevalence of serum ZnT8A and their clinical implication in 140 AAD patients. Other beta cell and thyroid-specific autoantibodies were also investigated, and ZnT8A results were confronted with the rs13266634 genotype. ZnT8A were detectable in 8.5 %, GADA in 20.7 %, IA-2A in 5.7 %, IAA in 1.6 % and various anti-thyroid antibodies in 7.1-67.8 % individuals. Type 1 diabetes was found in 10 % AAD patients. ZnT8A were positive in 57.1 % of T1D patients and 3.4 % non-diabetic AAD. Analysis of ZnT8A enabled to identify autoimmunity in two (14.3 %) T1D individuals previously classified as autoantibody-negative. ZnT8A-positive patients revealed significantly higher number of autoimmune conditions (p < 0.001), increased prevalence of T1D (p < 0.001) and other beta cell-specific autoantibodies. Carriers of the rs13266634 T-allele displayed increased frequency (p = 0.006) and higher titres of ZnT8A (p = 0.002). Our study demonstrates high incidence of ZnT8A in AAD patients. ZnT8A are associated with coexisting T1D and predictive of T1D in non-diabetic subjects. Moreover, positive ZnT8A in AAD indicate elevated risk for additional autoimmune conditions. Autoantibodies to beta cell antigens, comprising ZnT8, could be included in routine screening panels in AAD.

  18. Stress selection indices an acceptable tool to screen superior wheat genotypes under irrigated and rain-fed conditions

    International Nuclear Information System (INIS)

    Ullah, H.; Alam, M.

    2014-01-01

    environments (IRE and RFE). MP, TOL and STI had strong positive relationship with tillers m/sup -2/, spikelets spike-1, 1000-grain weight, biological yield and grain yield under IRE. Mean stress indices showed that the top ranking genotypes for MP and STI were B-VI(N)6, BRF-7, B-VI(N)5 and B-II(N)3, reflected their superior performance across both the conditions. (author)

  19. Psychometric properties of the Sleep Condition Indicator and Insomnia Severity Index in the evaluation of insomnia disorder.

    Science.gov (United States)

    Wong, Mark Lawrence; Lau, Kristy Nga Ting; Espie, Colin A; Luik, Annemarie I; Kyle, Simon D; Lau, Esther Yuet Ying

    2017-05-01

    The Sleep Condition Indicator (SCI) and Insomnia Severity Index (ISI) are commonly used instruments to assess insomnia. We evaluated their psychometric properties, particularly their discriminant validity against structured clinical interview (according to DSM-5 and ICSD-3), and their concurrent validity with measures of sleep and daytime functioning. A total of 158 young adults, 16% of whom were diagnosed with DSM-5 insomnia disorder and 13% with ICSD-3 Chronic Insomnia by structured interview, completed the ISI and SCI twice in 7-14 days, in addition to measures of sleep and daytime function. The Chinese version of the SCI was validated with good psychometric properties (ICC = 0.882). A cutoff of ≥8 on the ISI, ≤5 on the SCI short form, and ≤21 on the SCI achieved high discriminant validity (AUC > 0.85) in identifying individuals with insomnia based on both DSM-5 and ICSD-3 criteria. The SCI and ISI had comparable associations with subjective (0.18 sleep (0.31 disorder. Moreover, they showed good concordance with measures of daytime dysfunction, as well as subjective and objective sleep. The SCI and ISI are recommended for use in clinical and research settings. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Population ecology of the mallard: II. Breeding habitat conditions, size of the breeding populations, and production indices

    Science.gov (United States)

    Pospahala, Richard S.; Anderson, David R.; Henny, Charles J.

    1974-01-01

    This report, the second in a series on a comprehensive analysis of mallard population data, provides information on mallard breeding habitat, the size and distribution of breeding populations, and indices to production. The information in this report is primarily the result of large-scale aerial surveys conducted during May and July, 1955-73. The history of the conflict in resource utilization between agriculturalists and wildlife conservation interests in the primary waterfowl breeding grounds is reviewed. The numbers of ponds present during the breeding season and the midsummer period and the effects of precipitation and temperature on the number of ponds present are analyzed in detail. No significant cycles in precipitation were detected and it appears that precipitation is primarily influenced by substantial seasonal and random components. Annual estimates (1955-73) of the number of mallards in surveyed and unsurveyed breeding areas provided estimates of the size and geographic distribution of breeding mallards in North America. The estimated size of the mallard breeding population in North America has ranged from a high of 14.4 million in 1958 to a low of 7.1 million in 1965. Generally, the mallard breeding population began to decline after the 1958 peak until 1962, and remained below 10 million birds until 1970. The decline and subsequent low level of the mallard population between 1959 and 1969 .generally coincided with a period of poor habitat conditions on the major breeding grounds. The density of mallards was highest in the Prairie-Parkland Area with an average of nearly 19.2 birds per square mile. The proportion of the continental mallard breeding population in the Prairie-Parkland Area ranged from 30% in 1962 to a high of 600/0 in 1956. The geographic distribution of breeding mallards throughout North America was significantly related to the number of May ponds in the Prairie-Parkland Area. Estimates of midsummer habitat conditions and indices to

  1. FORECASTING NEW PRODUCT SALES

    Directory of Open Access Journals (Sweden)

    R. Siriram

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: This paper tests the accuracy of using Linear regression, Logistics regression, and Bass curves in selected new product rollouts, based on sales data. The selected new products come from the electronics and electrical engineering and information and communications technology industries. The eight selected products are: electronic switchgear, electric motors, supervisory control and data acquisition systems, programmable logic controllers, cell phones, wireless modules, routers, and antennas. We compare the Linear regression, Logistics regression and Bass curves with respect to forecasting using analysis of variance. The accuracy of these three curves is studied and conclusions are drawn. We use an expert panel to compare the different curves and provide lessons for managers to improve forecasting new product sales. In addition, comparison between the two industries is drawn, and areas for further research are indicated.

    AFRIKAANSE OPSOMMING: Hierdie artikel toets die akkuraatheid van die gebruik van linêere regressie, logistiese regressie en Bass-krommes by die bekendstelling van nuwe produkte gebaseer op verkoopsdata. Die geselekteerde nuwe produkte is uit die elektriese en elektroniese asook informasietegnologie- en kommunikasie bedrywe. Linêere regressie, logistiese regressie en Bass-krommes word vergelyk ten opsigte van vooruitskatting deur variansie te ontleed. Die akkuraatheid word ontleed en gevolgtrekkings gemaak. Die doel is om vooruitskatting van nuwe produkverkope te verbeter.

  2. Electricity demand forecasting techniques

    International Nuclear Information System (INIS)

    Gnanalingam, K.

    1994-01-01

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

  3. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

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

  4. Development and Validation of an HIV Risk Exposure and Indicator Conditions Questionnaire to Support Targeted HIV Screening.

    Science.gov (United States)

    Elías, María Jesús Pérez; Gómez-Ayerbe, Cristina; Elías, Pilar Pérez; Muriel, Alfonso; de Santiago, Alberto Diaz; Martinez-Colubi, María; Moreno, Ana; Santos, Cristina; Polo, Lidia; Barea, Rafa; Robledillo, Gema; Uranga, Almudena; Espín, Agustina Cano; Quereda, Carmen; Dronda, Fernando; Casado, Jose Luis; Moreno, Santiago

    2016-02-01

    The aim of our study was to develop a Spanish-structured HIV risk of exposure and indicator conditions (RE&IC) questionnaire. People attending to an emergency room or to a primary clinical care center were offered to participate in a prospective, 1 arm, open label study, in which all enrolled patients filled out our developed questionnaire and were HIV tested. Questionnaire accuracy, feasibility, and reliability were evaluated.Valid paired 5329 HIV RE&IC questionnaire and rapid HIV tests were performed, 69.3% in the primary clinical care center, 49.6% women, median age 37 years old, 74.9% Spaniards, 20.1% Latin-Americans. Confirmed hidden HIV infection was detected in 4.1%, while HIV RE&IC questionnaire was positive in 51.2%. HIV RE&IC questionnaire sensitivity was 100% to predict HIV infection, with a 100% negative predictive value. When considered separately, RE or IC items sensitivity decreases to 86.4% or 91%, and similarly their negative predictive value to 99.9% for both of them. The majority of people studied, 90.8% self-completed HIV RE&IC questionnaire. Median time to complete was 3 minutes. Overall HIV RE&IC questionnaire test-retest Kappa agreement was 0.82 (almost perfect), likewise for IC items 0.89, while for RE items was lower 0.78 (substantial).A feasible and reliable Spanish HIV RE&IC self questionnaire accurately discriminated all non-HIV-infected people without missing any HIV diagnoses, in a low prevalence HIV infection area. The best accuracy and reliability were obtained when combining HIV RE&IC items.

  5. The effect of Nitrogen on Radiation Use Efficiency and Growth indices of Maize Hybrids (Zea mays L. under Kermanshah Condition

    Directory of Open Access Journals (Sweden)

    M Ahmadi

    2018-02-01

    Full Text Available Introduction Dry matter produced by crops is a function of absorbed radiation and radiation use efficiency. Radiation use efficiency is an effective approach to quantify total dry matter accumulation. It is defined as biomass produced by plant for solar radiation absorbed during growing season. Radiation use efficiency is often calculated from the linear regression slope between total dry matter accumulation and cumulative solar radiation absorbed. It is affected by species, weather conditions, crop management, plant development stages, and the production of photosynthesis compounds. Among the factors of agronomic management, nitrogen fertilizer and crop species are the most important aspects that affect the radiation use efficiency. Therefore, by considering the fact that Kermanshah province has favorable condition in terms of more natural resources such as solar radiation, the aims of the present study were evaluation of nitrogen effect on radiation use efficiency, growth indices and yield of some current maize hybrids. Materials and Methods A split plot experiment was done based on randomized complete block design with 4 replications at 2014. Treatments were 4 levels of nitrogen fertilizer application (40%, 70%, 100% and 140% of the maize demand to nitrogen which based on the amount recommended by soil experiment equivalent to 138, 238, 350 and 483 kg.ha-1 of urea as main plots and 3 maize hybrids KSC-704, BC-678 and Simon as sub plots. Leaf area index and total dry matter yield measured during growing season. Crop growth rate and relative growth ratio calculated by differentiation from fitted equation on total dry matter yield data. In order to calculate radiation use efficiency, sunny hours for Kermanshah latitude obtained from the nearest weather station. Daily solar radiation simulated by the method cited by Goudriaan and Van Laar (1993 for growing season. The absorbed radiation in each stage obtained through the multiplication simulated

  6. Problem of short-term forecasting of near-earth space state

    International Nuclear Information System (INIS)

    Eselevich, V.G.; Ashmanets, V.I.; Startsev, S.A.

    1996-01-01

    The paper deals with actual and practically important problem of investigation and forecasting of state condition during magnetic storms. The available methods of forecasting of near-earth space state are analyzed. Forecasting of magnetic storms was conducted for control of space vehicles. Quasi-determinate method of magnetic storm forecasting is suggested. 13 refs., 3 figs

  7. Effect of Different Nitrogen Levels on Phenology, Growth Indices and Yield of two Lentil Cultivars under Rainfed Conditions in Mashhad

    Directory of Open Access Journals (Sweden)

    M Bannayan Aval

    2018-02-01

    Full Text Available Introduction Lentil (Lens Culinarris Medik. is an important pulse crop in Iran and is usually grown in rainfed areas. The average lentil yield in Iran is 1195 and 476 Kg.ha-1 in irrigated and rainfed farms, respectively. Low productivity occurs due to different factors. One of these factors is poor agronomic management practices that applied by the farmers, e.g. Limitation or inappropriate fertilizer distribution. Plant development occurs in a number of consecutive phases. These phases can be affected by temperature, moisture, photoperiod, cultivar and other factors. The amount of available nitrogen affects the distribution of assimilates between vegetative and reproductive organs and phenological stages of growth. Therefore, analysis of growth indices and its effective factors can be used as a suitable tool in evaluating the yield. The aim of this study was to evaluate the effect of different nitrogen levels on phenology and growth indices of two lentil cultivars in rainfed conditions of Mashhad. Materials and Methods The experiment was conducted as split plot layout based on randomized complete blocks design with three replications at the Agricultural Research Station, Ferdowsi University of Mashhad, during growth season 2016. Nitrogen fertilizer as urea (in three levels i.e. 0, 40 and 80 kg.ha-1 and cultivar (in two levels i.e. Birjand and Robat were in main plots and sub plots, respectively. To determine the leaf area and dry matter, sampling was done every two weeks during the growing season. Phenological stages timing for each plot were determined based on 50% of emergence, 50% of flowering, 50% of maturity. Final yield was estimated from three square meter from each plot. Data were analyzed with the SAS software; the means were compared with Duncan's multiple range tests at the 5% level of probability. The graphs were prepared by SigmaPlot software. Results and Discussion The results showed that the effect of urea fertilizer was

  8. Spatial Ensemble Postprocessing of Precipitation Forecasts Using High Resolution Analyses

    Science.gov (United States)

    Lang, Moritz N.; Schicker, Irene; Kann, Alexander; Wang, Yong

    2017-04-01

    Ensemble prediction systems are designed to account for errors or uncertainties in the initial and boundary conditions, imperfect parameterizations, etc. However, due to sampling errors and underestimation of the model errors, these ensemble forecasts tend to be underdispersive, and to lack both reliability and sharpness. To overcome such limitations, statistical postprocessing methods are commonly applied to these forecasts. In this study, a full-distributional spatial post-processing method is applied to short-range precipitation forecasts over Austria using Standardized Anomaly Model Output Statistics (SAMOS). Following Stauffer et al. (2016), observation and forecast fields are transformed into standardized anomalies by subtracting a site-specific climatological mean and dividing by the climatological standard deviation. Due to the need of fitting only a single regression model for the whole domain, the SAMOS framework provides a computationally inexpensive method to create operationally calibrated probabilistic forecasts for any arbitrary location or for all grid points in the domain simultaneously. Taking advantage of the INCA system (Integrated Nowcasting through Comprehensive Analysis), high resolution analyses are used for the computation of the observed climatology and for model training. The INCA system operationally combines station measurements and remote sensing data into real-time objective analysis fields at 1 km-horizontal resolution and 1 h-temporal resolution. The precipitation forecast used in this study is obtained from a limited area model ensemble prediction system also operated by ZAMG. The so called ALADIN-LAEF provides, by applying a multi-physics approach, a 17-member forecast at a horizontal resolution of 10.9 km and a temporal resolution of 1 hour. The performed SAMOS approach statistically combines the in-house developed high resolution analysis and ensemble prediction system. The station-based validation of 6 hour precipitation sums

  9. Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation

    Science.gov (United States)

    Zhao, T.; Cai, X.; Yang, D.

    2010-12-01

    Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover

  10. 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

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

    Science.gov (United States)

    Hathaway, David H.; Wilson, Robert M.

    2006-01-01

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

  12. An Application of the Short-Term Forecasting with Limited Data in the Healthcare Traveling Industry

    Directory of Open Access Journals (Sweden)

    Hoang-Sa Dang

    2016-10-01

    Full Text Available In real practice, forecasting under the limited data has attracted more attention in business activities, especially in the healthcare traveling industry in its current stage. However, there are only a few research studies focusing on this issue. Thus, the purposes of this paper were to determine the forecasted performance of several current forecasting methods as well as to examine their applications. Taking advantage of the small data requirement for model construction, three models including the exponential smoothing model, the Grey model GM(1,1, and the modified Lotka-Volterra model (L.V., were used to conduct forecasting analyses based on the data of foreign patients from 2001 to 2013 in six destinations. The results indicated that the L.V. model had higher prediction power than the other two models, and it obtained the best forecasting performance with an 89.7% precision rate. In conclusion, the L.V. model is the best model for estimating the market size of the healthcare traveling industry, followed by the GM(1,1 model. The contribution of this study is to offer a useful statistical tool for short-term planning, which can be applied to the healthcare traveling industry in particular, and for other business forecasting under the conditions of limited data in general.

  13. 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.

  14. Monthly forecasting of agricultural pests in Switzerland

    Science.gov (United States)

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

    2012-04-01

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

  15. 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

  16. Wave ensemble forecast in the Western Mediterranean Sea, application to an early warning system.

    Science.gov (United States)

    Pallares, Elena; Hernandez, Hector; Moré, Jordi; Espino, Manuel; Sairouni, Abdel

    2015-04-01

    The Western Mediterranean Sea is a highly heterogeneous and variable area, as is reflected on the wind field, the current field, and the waves, mainly in the first kilometers offshore. As a result of this variability, the wave forecast in these regions is quite complicated to perform, usually with some accuracy problems during energetic storm events. Moreover, is in these areas where most of the economic activities take part, including fisheries, sailing, tourism, coastal management and offshore renewal energy platforms. In order to introduce an indicator of the probability of occurrence of the different sea states and give more detailed information of the forecast to the end users, an ensemble wave forecast system is considered. The ensemble prediction systems have already been used in the last decades for the meteorological forecast; to deal with the uncertainties of the initial conditions and the different parametrizations used in the models, which may introduce some errors in the forecast, a bunch of different perturbed meteorological simulations are considered as possible future scenarios and compared with the deterministic forecast. In the present work, the SWAN wave model (v41.01) has been implemented for the Western Mediterranean sea, forced with wind fields produced by the deterministic Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS). The wind fields includes a deterministic forecast (also named control), between 11 and 21 ensemble members, and some intelligent member obtained from the ensemble, as the mean of all the members. Four buoys located in the study area, moored in coastal waters, have been used to validate the results. The outputs include all the time series, with a forecast horizon of 8 days and represented in spaghetti diagrams, the spread of the system and the probability at different thresholds. The main goal of this exercise is to be able to determine the degree of the uncertainty of the wave forecast, meaningful

  17. Inaccuracy in traffic forecasts

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  18. Can energy forecasts be improved?

    International Nuclear Information System (INIS)

    Rech, O.; Alban, P.

    2000-01-01

    Within the present day context of energy, characterized by the gap between short term trends and long term risks, forecasting takes on particular interest. We based our study on the evaluation of the results of some of these long term (2020) and very long term (2050) forecasts. This article looks at the overall demand for energy, whereas the evolution of each primary energy will be handled in a future article. We are restricting our analysis to a global level despite the inherent limitations of such a choice. Our approach mainly concentrates on the dynamics of the phenomena. Thus, we have noticed a simultaneous slowing down since the 1960's of the demography, economy and energy. The revenue and energy consumption per capita do not elude this tendency. At the same time, energy production leads a steep downward tendency. All in all, the forecasts have a tendency to conflict more or less with these changes. In the majority of the scenarios the anticipated rhythms of economic change and energy consumption would indicate a sudden and abrupt inverse of current dynamics. We have noticed that the single use of the average annual rate of change is insufficient to clearly present the long term tendencies that follow curved and not linear paths. Diagnostic errors made in past analyses are likely to affect the models for forecasting, for which the inferred dynamics have not been fully apprehended

  19. Correlation Coefficient, Path Analysis and Drought Tolerance Indices for Different Wheat Cultivars under Deficit Irrigation Conditions of Isfahan Region

    Directory of Open Access Journals (Sweden)

    H. R Salemi

    2017-06-01

    Full Text Available Introduction Water crisis as a main factor of agronomy limitation exists in all over the arid and semiarid regions such as Isfahan province which is located in the central part of the Zayandehrud River Basin. This study aimed to use path analysis and indices of drought to evaluate the correlation coefficients between main physiological parameter (grain yield with yield components and water use efficiency of winter wheat under three water conditions. Materials and Methods The experiment was carried out in Kaboutar Abad Agricultural Research Station, Isfahan in the central region of Iran (32º 31’N, 51º 51’E is located at the altitude of 1545 m above the sea level with a split plot in a randomized complete block design (RCBD with three replications in three cropping seasons on irrigated wheat cultivars. The treatments were included three levels of irrigation (60%FI, 80%FI and full irrigation as main plots and six wheat cultivars (Pishtaz, Shiraz, Sepahan, Marvdasht, Mahdavi and BC-Roshan as sub plots. Grain yield, straw and stubble, biological yield, harvest index (H.I., productivity degree (P.D., water use efficiency (WUE, plant height, grain number per spike, spike number per m2 and TGW were determined. Winter wheat cultivars were sown at the beginning of November and harvested in mid-June of the following year. The seed rate was 400 seed m-2, with a row spacing of 0.75 m. The first irrigation was by furrow method, implemented one day after seeding. Seeds emergence was observed about 5 days later. The N application was 250, 200 and 300 kgha-1 of N (urea at 46% N for each year divided into installments (10 days before planting, 30 days after planting, and every 30 days until the last irrigation. The P2O5 (phosphate ammonium and super-phosphate triple application to soil was 200, 100 and 50 kg ha-1 during the 3 years, respectively. At this stage, cultivation was done to mix the fertilizers with top soil manually. Pests and weeds were

  20. FORECASTING MODELS IN MANAGEMENT

    OpenAIRE

    Sindelar, Jiri

    2008-01-01

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