WorldWideScience

Sample records for evaluating point forecasts

  1. Evaluating probability forecasts

    OpenAIRE

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

    2011-01-01

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

  2. 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

  3. Market turning points forecasting using wavelet analysis

    Science.gov (United States)

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

    2015-11-01

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

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

    Science.gov (United States)

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

    2017-04-01

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

  5. Evaluation of official tropical cyclone landfall forecast issued by India ...

    Indian Academy of Sciences (India)

    It further extended the validity period up to 72 hrs in 2009. Here an attempt is made to evaluate the TC landfall forecast issued by IMD during 2003–2013 (11 years) by calculating the landfall point forecast error (LPE) and landfall time forecast error (LTE). The average LPE is about 67, 95, and 124 km and LTE is about 4, 7, ...

  6. 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.

  7. Toke Point, Washington Tsunami Forecast Grids for MOST Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Toke Point, Washington Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

  8. Sand Point, Alaska Tsunami Forecast Grids for MOST Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Sand Point, Alaska Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST) model....

  9. Point Reyes, California Tsunami Forecast Grids for MOST Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Point Reyes, California Forecast Model Grids provides bathymetric data strictly for tsunami inundation modeling with the Method of Splitting Tsunami (MOST)...

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

    Science.gov (United States)

    Danhelka, Jan; Vlasak, Tomas

    2010-05-01

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

  11. On the Economic Evaluation of Volatility Forecasts

    DEFF Research Database (Denmark)

    Voev, Valeri

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

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

    Indian Academy of Sciences (India)

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

  13. Evaluating Extensions to Coherent Mortality Forecasting Models

    Directory of Open Access Journals (Sweden)

    Syazreen Shair

    2017-03-01

    Full Text Available Coherent models were developed recently to forecast the mortality of two or more sub-populations simultaneously and to ensure long-term non-divergent mortality forecasts of sub-populations. This paper evaluates the forecast accuracy of two recently-published coherent mortality models, the Poisson common factor and the product-ratio functional models. These models are compared to each other and the corresponding independent models, as well as the original Lee–Carter model. All models are applied to age-gender-specific mortality data for Australia and Malaysia and age-gender-ethnicity-specific data for Malaysia. The out-of-sample forecast error of log death rates, male-to-female death rate ratios and life expectancy at birth from each model are compared and examined across groups. The results show that, in terms of overall accuracy, the forecasts of both coherent models are consistently more accurate than those of the independent models for Australia and for Malaysia, but the relative performance differs by forecast horizon. Although the product-ratio functional model outperforms the Poisson common factor model for Australia, the Poisson common factor is more accurate for Malaysia. For the ethnic groups application, ethnic-coherence gives better results than gender-coherence. The results provide evidence that coherent models are preferable to independent models for forecasting sub-populations’ mortality.

  14. Evaluation of official tropical cyclone landfall forecast issued by India ...

    Indian Academy of Sciences (India)

    Evaluation of official tropical cyclone landfall forecast issued by India Meteorological Department ... Here an attempt is made to evaluate the TC landfall forecast issued by IMD during. 2003–2013 (11 years) by calculating the ..... products also helped forecasters to minimize the sub- jectivity and improve the TC forecasting ...

  15. FORECASTING OF PERFORMANCE EVALUATION OF NEW VEHICLES

    Directory of Open Access Journals (Sweden)

    O. S. Krasheninin

    2016-12-01

    Full Text Available Purpose. The research work focuses on forecasting of performance evaluation of the tractive and non-tractive vehicles that will satisfy and meet the needs and requirements of the railway industry, which is constantly evolving. Methodology. Analysis of the technical condition of the existing fleet of rolling stock (tractive and non-tractive of Ukrainian Railways shows a substantial reduction that occurs in connection with its moral and physical wear and tear, as well as insufficient and limited purchase of new units of the tractive and non-tractive rolling stock in the desired quantity. In this situation there is a necessity of search of the methods for determination of rolling stock technical characteristics. One of such urgent and effective measures is to conduct forecasting of the defining characteristics of the vehicles based on the processes of their reproduction in conditions of limited resources using a continuous exponential function. The function of the growth rate of the projected figure degree for the vehicle determines the logistic characteristic that with unlimited resources has the form of an exponent, and with low ones – that of a line. Findings. The data obtained according to the proposed method allowed determining the expected (future value, that is the ratio of load to volume of the body for non-tractive rolling stock (gondola cars and weight-to-power for tractive rolling stock, the degree of forecast reliability and the standard forecast error, which show high prediction accuracy for the completed procedure. As a result, this will allow estimating the required characteristics of vehicles in the forecast year with high accuracy. Originality. The concept of forecasting the characteristics of the vehicles for decision-making on the evaluation of their prospects was proposed. Practical value. The forecasting methodology will reliably determine the technical parameters of tractive and non-tractive rolling stock, which will meet

  16. ECMWF SSW forecast evaluation using infrasound

    NARCIS (Netherlands)

    Smets, P.S.M.; Assink, J. D.; le Pichon, A; Evers, L.G.

    2016-01-01

    Accurate prediction of Sudden Stratospheric Warming (SSW) events is important for the performance of numerical weather prediction due to significant stratosphere-Troposphere coupling. In this study, for the first time middle atmospheric numerical weather forecasts are evaluated using infrasound.

  17. Evaluation of the performance of DIAS ionospheric forecasting models

    Directory of Open Access Journals (Sweden)

    Tsagouri Ioanna

    2011-08-01

    Full Text Available Nowcasting and forecasting ionospheric products and services for the European region are regularly provided since August 2006 through the European Digital upper Atmosphere Server (DIAS, http://dias.space.noa.gr. Currently, DIAS ionospheric forecasts are based on the online implementation of two models: (i the solar wind driven autoregression model for ionospheric short-term forecast (SWIF, which combines historical and real-time ionospheric observations with solar-wind parameters obtained in real time at the L1 point from NASA ACE spacecraft, and (ii the geomagnetically correlated autoregression model (GCAM, which is a time series forecasting method driven by a synthetic geomagnetic index. In this paper we investigate the operational ability and the accuracy of both DIAS models carrying out a metrics-based evaluation of their performance under all possible conditions. The analysis was established on the systematic comparison between models’ predictions with actual observations obtained over almost one solar cycle (1998–2007 at four European ionospheric locations (Athens, Chilton, Juliusruh and Rome and on the comparison of the models’ performance against two simple prediction strategies, the median- and the persistence-based predictions during storm conditions. The results verify operational validity for both models and quantify their prediction accuracy under all possible conditions in support of operational applications but also of comparative studies in assessing or expanding the current ionospheric forecasting capabilities.

  18. Applications of the gambling score in evaluating earthquake predictions and forecasts

    Science.gov (United States)

    Zhuang, Jiancang; Zechar, Jeremy D.; Jiang, Changsheng; Console, Rodolfo; Murru, Maura; Falcone, Giuseppe

    2010-05-01

    This study presents a new method, namely the gambling score, for scoring the performance earthquake forecasts or predictions. Unlike most other scoring procedures that require a regular scheme of forecast and treat each earthquake equally, regardless their magnitude, this new scoring method compensates the risk that the forecaster has taken. Starting with a certain number of reputation points, once a forecaster makes a prediction or forecast, he is assumed to have betted some points of his reputation. The reference model, which plays the role of the house, determines how many reputation points the forecaster can gain if he succeeds, according to a fair rule, and also takes away the reputation points bet by the forecaster if he loses. This method is also extended to the continuous case of point process models, where the reputation points betted by the forecaster become a continuous mass on the space-time-magnitude range of interest. For discrete predictions, we apply this method to evaluate performance of Shebalin's predictions made by using the Reverse Tracing of Precursors (RTP) algorithm and of the outputs of the predictions from the Annual Consultation Meeting on Earthquake Tendency held by China Earthquake Administration. For the continuous case, we use it to compare the probability forecasts of seismicity in the Abruzzo region before and after the L'aquila earthquake based on the ETAS model and the PPE model.

  19. Spatial evaluation of volcanic ash forecasts using satellite observations

    Directory of Open Access Journals (Sweden)

    N. J. Harvey

    2016-01-01

    Full Text Available The decision to close airspace in the event of a volcanic eruption is based on hazard maps of predicted ash extent. These are produced using output from volcanic ash transport and dispersion (VATD models. In this paper the fractions skill score has been used for the first time to evaluate the spatial accuracy of VATD simulations relative to satellite retrievals of volcanic ash. This objective measure of skill provides more information than traditional point-by-point metrics, such as success index and Pearson correlation coefficient, as it takes into the account spatial scale over which skill is being assessed. The FSS determines the scale over which a simulation has skill and can differentiate between a "near miss" and a forecast that is badly misplaced. The idealized scenarios presented show that even simulations with considerable displacement errors have useful skill when evaluated over neighbourhood scales of 200–700 (km2. This method could be used to compare forecasts produced by different VATDs or using different model parameters, assess the impact of assimilating satellite-retrieved ash data and evaluate VATD forecasts over a long time period.

  20. Hydro-meteorological evaluation of downscaled global ensemble rainfall forecasts

    Science.gov (United States)

    Gaborit, Étienne; Anctil, François; Fortin, Vincent; Pelletier, Geneviève

    2013-04-01

    Ensemble rainfall forecasts are of high interest for decision making, as they provide an explicit and dynamic assessment of the uncertainty in the forecast (Ruiz et al. 2009). However, for hydrological forecasting, their low resolution currently limits their use to large watersheds (Maraun et al. 2010). In order to bridge this gap, various implementations of the statistic-stochastic multi-fractal downscaling technique presented by Perica and Foufoula-Georgiou (1996) were compared, bringing Environment Canada's global ensemble rainfall forecasts from a 100 by 70-km resolution down to 6 by 4-km, while increasing each pixel's rainfall variance and preserving its original mean. For comparison purposes, simpler methods were also implemented such as the bi-linear interpolation, which disaggregates global forecasts without modifying their variance. The downscaled meteorological products were evaluated using different scores and diagrams, from both a meteorological and a hydrological view points. The meteorological evaluation was conducted comparing the forecasted rainfall depths against nine days of observed values taken from Québec City rain gauge database. These 9 days present strong precipitation events occurring during the summer of 2009. For the hydrologic evaluation, the hydrological models SWMM5 and (a modified version of) GR4J were implemented on a small 6 km2 urban catchment located in the Québec City region. Ensemble hydrologic forecasts with a time step of 3 hours were then performed over a 3-months period of the summer of 2010 using the original and downscaled ensemble rainfall forecasts. The most important conclusions of this work are that the overall quality of the forecasts was preserved during the disaggregation procedure and that the disaggregated products using this variance-enhancing method were of similar quality than bi-linear interpolation products. However, variance and dispersion of the different members were, of course, much improved for the

  1. Evaluation of Coupled Model Forecasts of Ethiopian Highlands Summer Climate

    Directory of Open Access Journals (Sweden)

    Mark R. Jury

    2014-01-01

    Full Text Available This study evaluates seasonal forecasts of rainfall and maximum temperature across the Ethiopian highlands from coupled ensemble models in the period 1981–2006, by comparison with gridded observational products (NMA + GPCC/CRU3. Early season forecasts from the coupled forecast system (CFS are steadier than European community medium range forecast (ECMWF. CFS and ECMWF April forecasts of June–August (JJA rainfall achieve significant fit (r2=0.27, 0.25, resp., but ECMWF forecasts tend to have a narrow range with drought underpredicted. Early season forecasts of JJA maximum temperature are weak in both models; hence ability to predict water resource gains may be better than losses. One aim of seasonal climate forecasting is to ensure that crop yields keep pace with Ethiopia’s growing population. Farmers using prediction technology are better informed to avoid risk in dry years and generate surplus in wet years.

  2. Choice of Sample Split in Out-of-Sample Forecast Evaluation

    DEFF Research Database (Denmark)

    Hansen, Peter Reinhard; Timmermann, Allan

    Out-of-sample tests of forecast performance depend on how a given data set is split into estimation and evaluation periods, yet no guidance exists on how to choose the split point. Empirical forecast evaluation results can therefore be difficult to interpret, particularly when several values......, while conversely the power of forecast evaluation tests is strongest with long out-of-sample periods. To deal with size distortions, we propose a test statistic that is robust to the effect of considering multiple sample split points. Empirical applications to predictabil- ity of stock returns...... and inflation demonstrate that out-of-sample forecast evaluation results can critically depend on how the sample split is determined....

  3. Evaluation of Air Force and Navy Demand Forecasting Systems

    Science.gov (United States)

    1994-01-01

    FORECASTING SYSTEMS THESIS Presented to the Faculty of the Graduate School of Logistics and Acquisition Management of the Air Force Institute of...compute the forecasting error measurements (MAD, , vAPE & MPE) to evaluate the accuracy and the stability of the Air Force RDB Forecasting system. The RDB...Institute, March 1993. Bond, A. Craig and Marvin E. Ruth. A Conceptual Model of the Air Force Logistics Picline. MS thesis, AFIT/GLM/LSM/89S-2. School

  4. Tide forecasting method based on dynamic weight distribution for operational evaluation

    Directory of Open Access Journals (Sweden)

    Shao-wei Qiu

    2009-03-01

    Full Text Available Through analysis of operational evaluation factors for tide forecasting, the relationship between the evaluation factors and the weights of forecasters was examined. A tide forecasting method based on dynamic weight distribution for operational evaluation was developed, and multiple-forecaster synchronous forecasting was realized while avoiding the instability cased by only one forecaster. Weights were distributed to the forecasters according to each one's forecast precision. An evaluation criterion for the professional level of the forecasters was also built. The eligibility rates of forecast results demonstrate the skill of the forecasters and the stability of their forecasts. With the developed tide forecasting method, the precision and reasonableness of tide forecasting are improved. The application of the present method to tide forecasting at the Huangpu Park tidal station demonstrates the validity of the method.

  5. Ideal point error for model assessment in data-driven river flow forecasting

    Directory of Open Access Journals (Sweden)

    C. W. Dawson

    2012-08-01

    Full Text Available When analysing the performance of hydrological models in river forecasting, researchers use a number of diverse statistics. Although some statistics appear to be used more regularly in such analyses than others, there is a distinct lack of consistency in evaluation, making studies undertaken by different authors or performed at different locations difficult to compare in a meaningful manner. Moreover, even within individual reported case studies, substantial contradictions are found to occur between one measure of performance and another. In this paper we examine the ideal point error (IPE metric – a recently introduced measure of model performance that integrates a number of recognised metrics in a logical way. Having a single, integrated measure of performance is appealing as it should permit more straightforward model inter-comparisons. However, this is reliant on a transferrable standardisation of the individual metrics that are combined to form the IPE. This paper examines one potential option for standardisation: the use of naive model benchmarking.

  6. Evaluation of model-based seasonal streamflow and water allocation forecasts for the Elqui Valley, Chile

    Science.gov (United States)

    Delorit, Justin; Cristian Gonzalez Ortuya, Edmundo; Block, Paul

    2017-09-01

    In many semi-arid regions, multisectoral demands often stress available water supplies. Such is the case in the Elqui River valley of northern Chile, which draws on a limited-capacity reservoir to allocate 25 000 water rights. Delayed infrastructure investment forces water managers to address demand-based allocation strategies, particularly in dry years, which are realized through reductions in the volume associated with each water right. Skillful season-ahead streamflow forecasts have the potential to inform managers with an indication of future conditions to guide reservoir allocations. This work evaluates season-ahead statistical prediction models of October-January (growing season) streamflow at multiple lead times associated with manager and user decision points, and links predictions with a reservoir allocation tool. Skillful results (streamflow forecasts outperform climatology) are produced for short lead times (1 September: ranked probability skill score (RPSS) of 0.31, categorical hit skill score of 61 %). At longer lead times, climatological skill exceeds forecast skill due to fewer observations of precipitation. However, coupling the 1 September statistical forecast model with a sea surface temperature phase and strength statistical model allows for equally skillful categorical streamflow forecasts to be produced for a 1 May lead, triggered for 60 % of years (1950-2015), suggesting forecasts need not be strictly deterministic to be useful for water rights holders. An early (1 May) categorical indication of expected conditions is reinforced with a deterministic forecast (1 September) as more observations of local variables become available. The reservoir allocation model is skillful at the 1 September lead (categorical hit skill score of 53 %); skill improves to 79 % when categorical allocation prediction certainty exceeds 80 %. This result implies that allocation efficiency may improve when forecasts are integrated into reservoir decision frameworks. The

  7. Forecasting the weather at the TAL sites during STS-40 using the grid point forecast output from the NMC MRF model

    Science.gov (United States)

    Hafele, Gene M.

    1992-01-01

    The NOAA's Spaceflight Meteorology Group has used the point forecast output from the Global Profile Archive and Global Profile Archive since 1990, and found this product to allow forecasters to examine the MRF model in a vertical profile, and thereby determine how different model parameters behave over time. Attention is presently given to the use of these resources in the illustrative case of the STS-40 mission, over northwestern Spain.

  8. Evaluating Downscaling Methods for Seasonal Climate Forecasts over East Africa

    Science.gov (United States)

    Roberts, J. Brent; Robertson, Franklin R.; Bosilovich, Michael; Lyon, Bradfield; Funk, Chris

    2013-01-01

    The U.S. National Multi-Model Ensemble seasonal forecasting system is providing hindcast and real-time data streams to be used in assessing and improving seasonal predictive capacity. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of NMME forecasts specifically for use in impact modeling within hub regions including East Africa, the Hindu Kush-Himalayan (HKH) region and Mesoamerica. One of the participating models in NMME is the NASA Goddard Earth Observing System (GEOS5). This work will present an intercomparison of downscaling methods using the GEOS5 seasonal forecasts of temperature and precipitation over East Africa. The current seasonal forecasting system provides monthly averaged forecast anomalies. These anomalies must be spatially downscaled and temporally disaggregated for use in application modeling (e.g. hydrology, agriculture). There are several available downscaling methodologies that can be implemented to accomplish this goal. Selected methods include both a non-homogenous hidden Markov model and an analogue based approach. A particular emphasis will be placed on quantifying the ability of different methods to capture the intermittency of precipitation within both the short and long rain seasons. Further, the ability to capture spatial covariances will be assessed. Both probabilistic and deterministic skill measures will be evaluated over the hindcast period

  9. Cooperative Research to Evaluate an Incidental Catch Distribution Forecast

    Directory of Open Access Journals (Sweden)

    Sara M. Turner

    2017-05-01

    Full Text Available Concern over incidental catches in commercial fisheries has been increasing, and while simple mitigation strategies have been effective, few effective mitigation strategies have been established for more complex species interactions. Incidental catches of alewife (Alosa pseudoharengus and blueback herring (A. aestivalis in the commercial Atlantic herring (Clupea harengus fishery have received substantial attention on the Northeast U.S. continental shelf, despite an existing bycatch avoidance program. This study evaluates the utility of existing species distribution forecasts to predict river herring catches in the southern New England small mesh bottom trawl Atlantic herring fishery, with the ultimate goal of incorporating incidental catch forecasts into the bycatch avoidance program. Commercial Atlantic herring bottom trawl vessels assisted with field-based evaluation of alewife, blueback herring, and Atlantic herring species distribution forecast models. Vessels were equipped with conductivity, temperature, and depth probes, and sampling occurred throughout the fishery season (January–March. Locations of expected low and high forecasted incidental catches were sampled, as well as locations the captain expected to find low and high incidental catches. This allowed us to sample within the spatial area the fishery occurs, and to evaluate the forecasted conditions, and predictions, at the spatial scale of the fishery. Catch differences between high and low probability stations were small and variable, as were differences in modeled probability of species presence. No differences were observed between observations at model-predicted stations and captain-selected stations. The sampling provided a better understanding of the potential effectiveness of distribution forecasts for further reducing incidental catches. Existing models have limited use at the spatial scale of this fishery, but could be improved by developing models with fishery

  10. Non-parametric probabilistic forecasts of wind power: required properties and evaluation

    DEFF Research Database (Denmark)

    Pinson, Pierre; Nielsen, Henrik Aalborg; Møller, Jan Kloppenborg

    2007-01-01

    Predictions of wind power production for horizons up to 48-72 hour ahead comprise a highly valuable input to the methods for the daily management or trading of wind generation. Today, users of wind power predictions are not only provided with point predictions, which are estimates of the conditio......Predictions of wind power production for horizons up to 48-72 hour ahead comprise a highly valuable input to the methods for the daily management or trading of wind generation. Today, users of wind power predictions are not only provided with point predictions, which are estimates...... of a single or a set of quantile forecasts. The required and desirable properties of such probabilistic forecasts are defined and a framework for their evaluation is proposed. This framework is applied for evaluating the quality of two statistical methods producing full predictive distributions from point...

  11. Evaluation of probabilistic forecasts with the scoringRules package

    Science.gov (United States)

    Jordan, Alexander; Krüger, Fabian; Lerch, Sebastian

    2017-04-01

    Over the last decades probabilistic forecasts in the form of predictive distributions have become popular in many scientific disciplines. With the proliferation of probabilistic models arises the need for decision-theoretically principled tools to evaluate the appropriateness of models and forecasts in a generalized way in order to better understand sources of prediction errors and to improve the models. Proper scoring rules are functions S(F,y) which evaluate the accuracy of a forecast distribution F , given that an outcome y was observed. In coherence with decision-theoretical principles they allow to compare alternative models, a crucial ability given the variety of theories, data sources and statistical specifications that is available in many situations. This contribution presents the software package scoringRules for the statistical programming language R, which provides functions to compute popular scoring rules such as the continuous ranked probability score for a variety of distributions F that come up in applied work. For univariate variables, two main classes are parametric distributions like normal, t, or gamma distributions, and distributions that are not known analytically, but are indirectly described through a sample of simulation draws. For example, ensemble weather forecasts take this form. The scoringRules package aims to be a convenient dictionary-like reference for computing scoring rules. We offer state of the art implementations of several known (but not routinely applied) formulas, and implement closed-form expressions that were previously unavailable. Whenever more than one implementation variant exists, we offer statistically principled default choices. Recent developments include the addition of scoring rules to evaluate multivariate forecast distributions. The use of the scoringRules package is illustrated in an example on post-processing ensemble forecasts of temperature.

  12. ANALYSIS OF FORECASTING METHODS FROM THE POINT OF VIEW OF EARLY WARNING CONCEPT IN PROJECT MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Florin POPESCU

    2017-12-01

    Full Text Available Early warning system (EWS based on a reliable forecasting process has become a critical component of the management of large complex industrial projects in the globalized transnational environment. The purpose of this research is to critically analyze the forecasting methods from the point of view of early warning, choosing those useful for the construction of EWS. This research addresses complementary techniques, using Bayesian Networks, which addresses both uncertainties and causality in project planning and execution, with the goal of generating early warning signals for project managers. Even though Bayesian networks have been widely used in a range of decision-support applications, their application as early warning systems for project management is still new.

  13. Forecasting DNI and GHI based on the WRF model. An evaluation study in Andalusia (Southern Spain)

    Energy Technology Data Exchange (ETDEWEB)

    Lara Fanego, Vicente; Ruiz Arias, Jose Antonio; Pozo Vazquez, Antonio David; Santos Alamillos, Francisco Javier; Tovar Pescador, Joaquin [Jaen Univ. (Spain). Dept. of Physics; Quesada Ruiz, Samuel [Jaen Univ. (Spain). Dept. of Computer Engineering

    2011-07-01

    In this work, we evaluate the reliability of GHI and DNI forecast based on the WRF mesoscale atmospheric model in Andalusia (Southern Spain). Particularly, the role of the spatial resolution of the model set up and the use of a spatial-averaging post-processing step was analyzed. To this end, a set of two-days-ahead one-year-length integrations, with different spatial resolutions (1, 3, 9 and 27 km) were evaluated. Results showed, firstly, that an increment in the spatial resolution does not enhance the reliability of the model forecasts, except under clear sky conditions. Secondly, that, in general, an spatial averaging of the solar forecasts corresponding to the grid points surrounding the location of interest provides a notable improvement in the forecasting skills. The most significant improvement is found when forecasts corresponding to an area of about 100 by 100 km are averaged. The role of the WRF model cloud representation in the former results is discussed. (orig.)

  14. nowCOAST's Map Service for Geo-Referenced Hyperlinks to Forecasts for Geographic Areas or Points

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Map Information: This nowCOAST geolinks map service provides maps depicting the locations of geographic zones and points where NWS forecasts are available along with...

  15. nowCOAST's Map Service for Geo-Referenced Hyperlinks to Forecast Guidance or Predictions at Point Locations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Map Information: This nowCOAST geolinks map service provides maps depicting the locations where NOAA point forecast guidance or predictions are available along with...

  16. Evaluation of short-term weather forecasts in South Africa | Banitz ...

    African Journals Online (AJOL)

    In this paper a brief overview will be given for the reasons for doing evaluations of short-term weather forecasts as well as the methodology thereof. Short-term weather forecasts are defined as a forecast valid for the current day as well as the next day. In other words up to 48 h ahead. Results are given for South African ...

  17. A performance evaluation of point pair features

    DEFF Research Database (Denmark)

    Kiforenko, Lilita; Drost, Bertram; Tombari, Federico

    2017-01-01

    of relations between two points). Our comparison is made on 7 publicly available datasets, showing variations on a number of parameters, e.g. acquisition technique, the number of objects/scenes and the amount of occlusion and clutter. We evaluate feature performance both at a point-wise object...... datasets. However, to the best of our knowledge, no comprehensive evaluation of these features has been made. In this work, we evaluate PPFs on a large set of 3D scenes. We not only compare PPFs to local point cloud descriptors, but also investigate the internal variations of PPFs (different types...

  18. THE ACCURACY AND BIAS EVALUATION OF THE USA UNEMPLOYMENT RATE FORECASTS. METHODS TO IMPROVE THE FORECASTS ACCURACY

    Directory of Open Access Journals (Sweden)

    MIHAELA BRATU (SIMIONESCU

    2012-12-01

    Full Text Available In this study some alternative forecasts for the unemployment rate of USA made by four institutions (International Monetary Fund (IMF, Organization for Economic Co-operation and Development (OECD, Congressional Budget Office (CBO and Blue Chips (BC are evaluated regarding the accuracy and the biasness. The most accurate predictions on the forecasting horizon 201-2011 were provided by IMF, followed by OECD, CBO and BC.. These results were gotten using U1 Theil’s statistic and a new method that has not been used before in literature in this context. The multi-criteria ranking was applied to make a hierarchy of the institutions regarding the accuracy and five important accuracy measures were taken into account at the same time: mean errors, mean squared error, root mean squared error, U1 and U2 statistics of Theil. The IMF, OECD and CBO predictions are unbiased. The combined forecasts of institutions’ predictions are a suitable strategy to improve the forecasts accuracy of IMF and OECD forecasts when all combination schemes are used, but INV one is the best. The filtered and smoothed original predictions based on Hodrick-Prescott filter, respectively Holt-Winters technique are a good strategy of improving only the BC expectations. The proposed strategies to improve the accuracy do not solve the problem of biasness. The assessment and improvement of forecasts accuracy have an important contribution in growing the quality of decisional process.

  19. CNR-ISAC 2 m temperature monthly forecasts: a first probabilistic evaluation

    Science.gov (United States)

    Mastrangelo, Daniele; Malguzzi, Piero

    2017-04-01

    The 2 m temperature probabilistic forecasts collected, on a weekly basis, in about one year of CNR-ISAC monthly forecasting activity are evaluated in this work. RPSS and reliability diagrams are computed on a tercile classification of forecast and observed temperatures. The RPSS, averaged over all the available cases, shows that the system has a residual predictive skill beyond week 2 on some peculiar regions. Reliability diagrams show that, in general, the probability forecasts of above-normal observed temperature are more reliable than below-normal temperature. Although the results are based on a limited period, they can represent a reference for similar works based on other subseasonal forecasting systems.

  20. Evaluating winds and vertical wind shear from Weather Research and Forecasting model forecasts using seven planetary boundary layer schemes

    DEFF Research Database (Denmark)

    Draxl, Caroline; Hahmann, Andrea N.; Pena Diaz, Alfredo

    2014-01-01

    The existence of vertical wind shear in the atmosphere close to the ground requires that wind resource assessment and prediction with numerical weather prediction (NWP) models use wind forecasts at levels within the full rotor span of modern large wind turbines. The performance of NWP models...... regarding wind energy at these levels partly depends on the formulation and implementation of planetary boundary layer (PBL) parameterizations in these models. This study evaluates wind speeds and vertical wind shears simulated by theWeather Research and Forecasting model using seven sets of simulations...... with different PBL parameterizations at one coastal site over western Denmark. The evaluation focuses on determining which PBL parameterization performs best for wind energy forecasting, and presenting a validation methodology that takes into account wind speed at different heights. Winds speeds at heights...

  1. Prospective and retrospective evaluation of five-year earthquake forecast models for California

    Science.gov (United States)

    Strader, Anne; Schneider, Max; Schorlemmer, Danijel

    2017-10-01

    The Collaboratory for the Study of Earthquake Predictability was developed to prospectively test earthquake forecasts through reproducible and transparent experiments within a controlled environment. From January 2006 to December 2010, the Regional Earthquake Likelihood Models (RELM) Working Group developed and evaluated thirteen time-invariant prospective earthquake mainshock forecasts. The number, spatial and magnitude components of the forecasts were compared to the observed seismicity distribution using a set of likelihood-based consistency tests. In this RELM experiment update, we assess the long-term forecasting potential of the RELM forecasts. Additionally, we evaluate RELM forecast performance against the Uniform California Earthquake Rupture Forecast (UCERF2) and the National Seismic Hazard Mapping Project (NSHMP) forecasts, which are used for seismic hazard analysis for California. To test each forecast's long-term stability, we also evaluate each forecast from January 2006 to December 2015, which contains both five-year testing periods, and the 40-year period from January 1967 to December 2006. Multiple RELM forecasts, which passed the N-test during the retrospective (January 2006 to December 2010) period, overestimate the number of events from January 2011 to December 2015, although their forecasted spatial distributions are consistent with observed earthquakes. Both the UCERF2 and NSHMP forecasts pass all consistency tests for the two five-year periods; however, they tend to underestimate the number of observed earthquakes over the 40-year testing period. The smoothed seismicity model Helmstetter-et-al.Mainshock outperforms both United States Geological Survey (USGS) models during the second five-year experiment, and contains higher forecasted seismicity rates than the USGS models at multiple observed earthquake locations.

  2. A performance evaluation of point pair features

    DEFF Research Database (Denmark)

    Kiforenko, Lilita; Drost, Bertram; Tombari, Federico

    2018-01-01

    of relations between two points). Our comparison is made on 7 publicly available datasets, showing variations on a number of parameters, e.g. acquisition technique, the number of objects/scenes and the amount of occlusion and clutter. We evaluate feature performance both at a point-wise object...... datasets. However, to the best of our knowledge, no comprehensive evaluation of these features has been made. In this work, we evaluate PPFs on a large set of 3D scenes. We not only compare PPFs to local point cloud descriptors, but also investigate the internal variations of PPFs (different types......-scene correspondence level and for overall object detection and pose estimation in a RANSAC pipeline. Additionally, we also present object detection and pose estimation results for the original, voting based, PPF algorithm. Our results show that in general PPF is the top performer, however, there are datasets, which...

  3. Transport project evaluation: feasibility risk assessment and scenario forecasting

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Leleur, Steen

    2017-01-01

    distribution functions. The latter have been placed and ultimately simulated on the inaccuracies of determining demand forecasts, i.e. leading to travel time savings and ticket revenues of the project. Finally, RSF makes use of scenario forecasting where trend scenarios such as economic growth and level...

  4. Evaluating National Weather Service Seasonal Forecast Products in Reservoir Operation Case Studies

    Science.gov (United States)

    Nielson, A.; Guihan, R.; Polebistki, A.; Palmer, R. N.; Werner, K.; Wood, A. W.

    2014-12-01

    Forecasts of future weather and streamflow can provide valuable information for reservoir operations and water management. A challenge confronting reservoir operators today is how to incorporate both climate and streamflow products into their operations and which of these forecast products are most informative and useful for optimized water management. This study incorporates several reforecast products provided by the Colorado Basin River Forecast Center (CBRFC) which allows a complete retrospective analysis of climate forecasts, resulting in an evaluation of each product's skill in the context of water resources management. The accuracy and value of forecasts generated from the Climate Forecast System version 2 (CFSv2) are compared to the accuracy and value of using an Ensemble Streamflow Predictions (ESP) approach. Using the CFSv2 may offer more insight when responding to climate driven extremes than the ESP approach because the CFSv2 incorporates a fully coupled climate model into its forecasts rather than using all of the historic climate record as being equally probable. The role of forecast updating frequency will also be explored. Decision support systems (DSS) for both Salt Lake City Parley's System and the Snohomish County Public Utility Department's (SnoPUD) Jackson project will be used to illustrate the utility of forecasts. Both DSS include a coupled simulation and optimization model that will incorporate system constraints, operating policies, and environmental flow requirements. To determine the value of the reforecast products, performance metrics meaningful to the managers of each system are to be identified and quantified. Without such metrics and awareness of seasonal operational nuances, it is difficult to identify forecast improvements in meaningful ways. These metrics of system performance are compared using the different forecast products to evaluate the potential benefits of using CFSv2 seasonal forecasts in systems decision making.

  5. Ex-post evaluations of demand forecast accuracy

    DEFF Research Database (Denmark)

    Nicolaisen, Morten Skou; Driscoll, Patrick Arthur

    2014-01-01

    of the largest ex-post studies of demand forecast accuracy for transport infrastructure projects. The focus is twofold; to provide an overview of observed levels of demand forecast inaccuracy and to explore the primary explanations offered for the observed inaccuracy. Inaccuracy in the form of both bias......Travel demand forecasts play a crucial role in the preparation of decision support to policy makers in the field of transport planning. The results feed directly into impact appraisals such as cost benefit analyses and environmental impact assessments, which are mandatory for large public works...

  6. Results of the Clarus demonstrations : evaluation of enhanced road weather forecasting enabled by Clarus.

    Science.gov (United States)

    2011-06-14

    This document is the final report of an evaluation of Clarus-enabled enhanced road weather forecasting used in the Clarus Demonstrations. : This report examines the use of Clarus data to enhance four types of weather models and forecasts: The Local A...

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

    National Research Council Canada - National Science Library

    Passner, Jeffrey E

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    T. Hashino

    2007-01-01

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

  9. Existing bridge evaluation using deficiency point method

    Directory of Open Access Journals (Sweden)

    Vičan Josef

    2016-01-01

    Full Text Available In the transforming EU countries, transportation infrastructure has a prominent position in advancing industry and society. Recent developments show, that attention should be moved from the design of new structures towards the repair and reconstruction of existing ones to ensure and increase their satisfactory structural reliability and durability. The problem is very urgent because many construction projects, especially transport infrastructure, in most European countries are more than 50-60 years old and require rehabilitations based on objective evaluations. Therefore, the paper presents methodology of existing bridge evaluation based on reliability concept using Deficiency Point Method. The methodology was prepared from the viewpoint to determine the priority order for existing bridge rehabilitation.

  10. Empirical evaluation of a forecasting model for successful facilitation ...

    African Journals Online (AJOL)

    The forecasting model identified 8 key attributes for facilitation success based on performance measures from the 1999 Facilitator Customer Service Survey. During 2000 the annual ... Ultimately, the students deserve the best education possible to contribute to the maximisation of the country's human capital. South African ...

  11. Diagnostic Evaluation of Nmme Precipitation and Temperature Forecasts for the Continental United States

    Science.gov (United States)

    Karlovits, G. S.; Villarini, G.; Bradley, A.; Vecchi, G. A.

    2014-12-01

    Forecasts of seasonal precipitation and temperature can provide information in advance of potentially costly disruptions caused by flood and drought conditions. The consequences of these adverse hydrometeorological conditions may be mitigated through informed planning and response, given useful and skillful forecasts of these conditions. However, the potential value and applicability of these forecasts is unavoidably linked to their forecast quality. In this work we evaluate the skill of four global circulation models (GCMs) part of the North American Multi-Model Ensemble (NMME) project in forecasting seasonal precipitation and temperature over the continental United States. The GCMs we consider are the Geophysical Fluid Dynamics Laboratory (GFDL)-CM2.1, NASA Global Modeling and Assimilation Office (NASA-GMAO)-GEOS-5, The Center for Ocean-Land-Atmosphere Studies - Rosenstiel School of Marine & Atmospheric Science (COLA-RSMAS)-CCSM3, Canadian Centre for Climate Modeling and Analysis (CCCma) - CanCM4. These models are available at a resolution of 1-degree and monthly, with a minimum forecast lead time of nine months, up to one year. These model ensembles are compared against gridded monthly temperature and precipitation data created by the PRISM Climate Group, which represent the reference observation dataset in this work. Aspects of forecast quality are quantified using a diagnostic skill score decomposition that allows the evaluation of the potential skill and conditional and unconditional biases associated with these forecasts. The evaluation of the decomposed GCM forecast skill over the continental United States, by season and by lead time allows for a better understanding of the utility of these models for flood and drought predictions. Moreover, it also represents a diagnostic tool that could provide model developers feedback about strengths and weaknesses of their models.

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

    Directory of Open Access Journals (Sweden)

    Zhen Yao Wong

    2016-09-01

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

  13. Development and evaluation of an operational SDS forecasting system for East Asia: CUACE/DUST

    Science.gov (United States)

    Zhou, C. H.; Gong, S. L.; Zhang, X. Y.; Wang, Y. Q.; Niu, T.; Liu, H. L.; Zhao, T. L.; Yang, Y. Q.; Hou, Q.

    2007-06-01

    CUACE/Dust, an operational sand and dust storm (SDS) forecasting system for East Asia, was developed at CMA (China Meteorological Administration) by integrating a meso-scale dust aerosol model with a 3DVar data assimilation system that uses both surface network observation data and dust intensity data retrieved from the Chinese Geostationary Satellite FY-2C. For spring 2006, CUACE/Dust successfully forecasted most of the 31 SDS episodes in East Asia. A detailed comparison of the modeling predictions for the 8-12 March episode with surface network observations and lidar measurements revealed a robust forecasting ability of the system. The time series of the forecasted dust concentrations for a number of representative stations for the whole spring 2006 were also evaluated against surface PM10 monitoring data, showing a very good agreement in terms of the SDS timing and magnitudes near source regions where dust aerosols dominate. For the entire domain forecasts in spring 2006 (1 March-31 May), a TS (thread score) system evaluated the performance of the system against all available observations and rendered an averaged TS value of 0.31 for 24 h forecasts, 0.23 for 48 h and 0.21 for 72 h forecasts.

  14. Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service.

    Science.gov (United States)

    Bastl, Katharina; Berger, Uwe; Kmenta, Maximilian

    2017-05-08

    Pollen forecasts are highly valuable for allergen avoidance and thus raising the quality of life of persons concerned by pollen allergies. They are considered as valuable free services for the public. Careful scientific evaluation of pollen forecasts in terms of accurateness and reliability has not been available till date. The aim of this study was to analyze 9 mobile apps, which deliver pollen information and pollen forecasts, with a focus on their accurateness regarding the prediction of the pollen load in the grass pollen season 2016 to assess their usefulness for pollen allergy sufferers. The following number of apps was evaluated for each location: 3 apps for Vienna (Austria), 4 apps for Berlin (Germany), and 1 app each for Basel (Switzerland) and London (United Kingdom). All mobile apps were freely available. Today's grass pollen forecast was compared throughout the defined grass pollen season at each respective location with measured grass pollen concentrations. Hit rates were calculated for the exact performance and for a tolerance in a range of ±2 and ±4 pollen per cubic meter. In general, for most apps, hit rates score around 50% (6 apps). It was found that 1 app showed better results, whereas 3 apps performed less well. Hit rates increased when calculated with tolerances for most apps. In contrast, the forecast for the "readiness to flower" for grasses was performed at a sufficiently accurate level, although only two apps provided such a forecast. The last of those forecasts coincided with the first moderate grass pollen load on the predicted day or 3 days after and performed even from about a month before well within the range of 3 days. Advertisement was present in 3 of the 9 analyzed apps, whereas an imprint mentioning institutions with experience in pollen forecasting was present in only three other apps. The quality of pollen forecasts is in need of improvement, and quality control for pollen forecasts is recommended to avoid potential harm to

  15. Serving Real-Time Point Observation Data in netCDF using Climate and Forecasting Discrete Sampling Geometry Conventions

    Science.gov (United States)

    Ward-Garrison, C.; May, R.; Davis, E.; Arms, S. C.

    2016-12-01

    NetCDF is a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. The Climate and Forecasting (CF) metadata conventions for netCDF foster the ability to work with netCDF files in general and useful ways. These conventions include metadata attributes for physical units, standard names, and spatial coordinate systems. While these conventions have been successful in easing the use of working with netCDF-formatted output from climate and forecast models, their use for point-based observation data has been less so. Unidata has prototyped using the discrete sampling geometry (DSG) CF conventions to serve, using the THREDDS Data Server, the real-time point observation data flowing across the Internet Data Distribution (IDD). These data originate in text format reports for individual stations (e.g. METAR surface data or TEMP upper air data) and are converted and stored in netCDF files in real-time. This work discusses the experiences and challenges of using the current CF DSG conventions for storing such real-time data. We also test how parts of netCDF's extended data model can address these challenges, in order to inform decisions for a future version of CF (CF 2.0) that would take advantage of features of the netCDF enhanced data model.

  16. Statistical evaluation of CFS seasonal precipitation forecasts for large-scale droughts in Africa and India

    Science.gov (United States)

    Siegmund, Jonatan; Bliefernicht, Jan; Laux, Patrick; Kunstmann, Harald

    2013-04-01

    Monthly and seasonal meteorological forecasts are routinely produced by several international weather services using global coupled ocean-atmosphere general circulation models. This kind of information can be used as source of information in operational hydrological monitoring and forecasting systems to improve early drought warnings. In March 2011, a new version of the global coupled model of the National Centre for Environmental Prediction, the Climate Forecast System (CFS) Version 2, became operational providing real-time ensemble forecasts up to nine months. However, a comprehensive analysis of the CFS forecast for the prediction of droughts in water stress regions has not yet been performed. In this study we evaluate the CFS precipitation forecasts for large-scale droughts that occurred during the rainy season in West Africa, East Africa and India. The target areas are large-scale river-basins like Volta (West Africa), Ganges (India) and the administrative area of Kenya. The forecasts are compared to monthly precipitation observations provided on a regular grid by the Global Precipitation Climatology Centre. In addition, the CFS performance is evaluated using areal monthly precipitation amount of the river basin of interest as an indicator for dry months. The verification is done for the period 1982-2009 using all ensemble members of the retrospective CFS archive. The outcomes of this study illustrate, that the CFS in some cases can simulate general features of the monthly precipitation regime for the respective river basins. However, an evaluation using the entire retrospective CFS forecasts demonstrates a low accuracy. Furthermore, the seasonal forecasts of monthly precipitation are characterized by a large over- and underestimation during the rainy season depending on the target region. In this presentation, the following issues are highlighted: (i) The performance of the CFS precipitation forecast for individual events such as the severe India drought in

  17. Evaluating NMME Seasonal Forecast Skill for use in NASA SERVIR Hub Regions

    Science.gov (United States)

    Roberts, J. Brent; Roberts, Franklin R.

    2013-01-01

    The U.S. National Multi-Model Ensemble seasonal forecasting system is providing hindcast and real-time data streams to be used in assessing and improving seasonal predictive capacity. The coupled forecasts have numerous potential applications, both national and international in scope. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of NMME forecasts specifically for use in driving applications models in hub regions including East Africa, the Hindu Kush- Himalayan (HKH) region and Mesoamerica. A prerequisite for seasonal forecast use in application modeling (e.g. hydrology, agriculture) is bias correction and skill assessment. Efforts to address systematic biases and multi-model combination in support of NASA SERVIR impact modeling requirements will be highlighted. Specifically, quantilequantile mapping for bias correction has been implemented for all archived NMME hindcasts. Both deterministic and probabilistic skill estimates for raw, bias-corrected, and multi-model ensemble forecasts as a function of forecast lead will be presented for temperature and precipitation. Complementing this statistical assessment will be case studies of significant events, for example, the ability of the NMME forecasts suite to anticipate the 2010/2011 drought in the Horn of Africa and its relationship to evolving SST patterns.

  18. Evaluation of forecasts by accuracy and spread in the MiKlip decadal climate prediction system

    Directory of Open Access Journals (Sweden)

    Christopher Kadow

    2016-12-01

    Full Text Available We present the evaluation of temperature and precipitation forecasts obtained with the MiKlip decadal climate prediction system. These decadal hindcast experiments are verified with respect to the accuracy of the ensemble mean and the ensemble spread as a representative for the forecast uncertainty. The skill assessment follows the verification framework already used by the decadal prediction community, but enhanced with additional evaluation techniques like the logarithmic ensemble spread score. The core of the MiKlip system is the coupled Max Planck Institute Earth System Model. An ensemble of 10 members is initialized annually with ocean and atmosphere reanalyses of the European Centre for Medium-Range Weather Forecasts. For assessing the effect of the initialization, we compare these predictions to uninitialized climate projections with the same model system. Initialization improves the accuracy of temperature and precipitation forecasts in year 1, particularly in the Pacific region. The ensemble spread well represents the forecast uncertainty in lead year 1, except in the tropics. This estimate of prediction skill creates confidence in the respective 2014 forecasts, which depict less precipitation in the tropics and a warming almost everywhere. However, large cooling patterns appear in the Northern Hemisphere, the Pacific South America and the Southern Ocean. Forecasts for 2015 to 2022 show even warmer temperatures than for 2014, especially over the continents. The evaluation of lead years 2 to 9 for temperature shows skill globally with the exception of the eastern Pacific. The ensemble spread can again be used as an estimate of the forecast uncertainty in many regions: It improves over the tropics compared to lead year 1. Due to a reduction of the conditional bias, the decadal predictions of the initialized system gain skill in the accuracy compared to the uninitialized simulations in the lead years 2 to 9. Furthermore, we show that

  19. Evaluation of Particulate Matter Source Apportionment Forecasts during the MAPS-Seoul Field Campaign

    Science.gov (United States)

    Bae, C.; Kim, S.; Kim, H. C.; Kim, B. U.

    2015-12-01

    We report forecasting model performance analysis results of Comprehensive Air quality Model with extensions (CAMx) simulation evaluated with flight measurements during Megacity Air Pollution Studies-Seoul (MAPS-Seoul) field campaign. The primary focus of this study is two-fold: (1) the air quality forecasting model performance for O3, PM10/2.5 and their precursors over the Yellow Sea to measure the model's ability to account for the transport process and (2) the utilization of modeled source-receptor relationship to understand the root of systematic model under-prediction for PM10 and PM2.5 forecasts. MAPS-Seoul, conducted in the Seoul Metropolitan Area (SMA) in the summer of 2015, was an integrated research program covering ground monitoring and aloft measurement with aircrafts. To support this field campaign, air quality forecasting was performed with Weather Research and Forecasting (WRF) - Sparse Matrix Operator Kernel Emissions (SMOKE) - CAMx modeling framework. WRF model simulations initialized with National Centers for Environmental Prediction Global Forecasting System (NOAA/NCEP-GFS) were prepared for daily meteorological forecasts. Emission inventories used in this study are Model Inter-Comparison Study-Asia (MICS-Asia) 2010 for Asia and Clean Air Policy Support System (CAPSS) 2010 for South Korea. Simulated PM10 concentrations were evaluated with observed PM10 concentrations at ground monitoring sites of the AirKorea network in SMA. During the campaign period, average simulated PM10 concentrations showed significant underprediction, over 30% (~35 ㎍/㎥) lower than those observed at sites. To examine source-receptor relationship as a way to identify the cause of underprediction, we ran CAMx with Particulate matter Source Apportionment Technology (PSAT). The air quality forecasting model is based on the with 27-km horizontal grid resolution over Northeast Asia.

  20. Evaluation of a wildfire smoke forecasting system as a tool for public health protection.

    Science.gov (United States)

    Yao, Jiayun; Brauer, Michael; Henderson, Sarah B

    2013-10-01

    Exposure to wildfire smoke has been associated with cardiopulmonary health impacts. Climate change will increase the severity and frequency of smoke events, suggesting a need for enhanced public health protection. Forecasts of smoke exposure can facilitate public health responses. We evaluated the utility of a wildfire smoke forecasting system (BlueSky) for public health protection by comparing its forecasts with observations and assessing their associations with population-level indicators of respiratory health in British Columbia, Canada. We compared BlueSky PM2.5 forecasts with PM2.5 measurements from air quality monitors, and BlueSky smoke plume forecasts with plume tracings from National Oceanic and Atmospheric Administration Hazard Mapping System remote sensing data. Daily counts of the asthma drug salbutamol sulfate dispensations and asthma-related physician visits were aggregated for each geographic local health area (LHA). Daily continuous measures of PM2.5 and binary measures of smoke plume presence, either forecasted or observed, were assigned to each LHA. Poisson regression was used to estimate the association between exposure measures and health indicators. We found modest agreement between forecasts and observations, which was improved during intense fire periods. A 30-μg/m3 increase in BlueSky PM2.5 was associated with an 8% increase in salbutamol dispensations and a 5% increase in asthma-related physician visits. BlueSky plume coverage was associated with 5% and 6% increases in the two health indicators, respectively. The effects were similar for observed smoke, and generally stronger in very smoky areas. BlueSky forecasts showed modest agreement with retrospective measures of smoke and were predictive of respiratory health indicators, suggesting they can provide useful information for public health protection.

  1. Forecasting and evaluating patterns of energy development in southwestern Wyoming

    Science.gov (United States)

    Garman, Steven L.

    2015-01-01

    The effects of future oil and natural gas development in southwestern Wyoming on wildlife populations are topical to conservation of the sagebrush steppe ecosystem. To aid in understanding these potential effects, the U.S. Geological Survey developed an Energy Footprint simulation model that forecasts the amount and pattern of energy development under different assumptions of development rates and well-drilling methods. The simulated disturbance patterns produced by the footprint model are used to assess the potential effects on wildlife habitat and populations. A goal of this modeling effort is to use measures of energy production (number of simulated wells), well-pad and road-surface disturbance, and potential effects on wildlife to identify build-out designs that minimize the physical and ecological footprint of energy development for different levels of energy production and development costs.

  2. Evaluation of NCEP TIGGE short-range forecast for Indian summer monsoon intraseasonal oscillation

    Science.gov (United States)

    Tirkey, Snehlata; Mukhopadhyay, P.

    2017-08-01

    This study focuses on the short-range prediction of Monsoon Intraseasonal Oscillations (MISOs) using the National Centers for Environmental Prediction(NCEP) Ensemble Prediction System (EPS) data from The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) archive. The Indian Summer Monsoon Rainfall (ISMR), which plays an important role in the socio-economic growth of the country, is highly variable and is mostly governed by the MISOs. In addition to this, deterministic forecasts of ISMR are not very reliable. Hence, a probabilistic approach at daily scale is required. Keeping this in mind, the present analysis is done by using daily forecast data for up to 7-day lead time and compared with observations. The analysis shows that the ensemble forecast well captures the variability as compared to observations even up to 7 days. The spatial characteristics and the northward propagation of MISO are observed thoroughly in the EPS. The evolution of dynamical and thermodynamical parameters such as specific humidity, moist static energy, moisture divergence, and vorticity is also captured well but show deviation from the observation from 96 h lead time onwards. The tropospheric temperature forecast captures the observed gradient but with certain bias in magnitude whereas the wind shear is simulated quite well both in pattern and magnitude. These analyses bring out the biases in TIGGE EPS forecast and also point out the possible moist processes which needs to be improved.

  3. Evaluation of weather forecast systems for storm surge modeling in the Chesapeake Bay

    Science.gov (United States)

    Garzon, Juan L.; Ferreira, Celso M.; Padilla-Hernandez, Roberto

    2018-01-01

    Accurate forecast of sea-level heights in coastal areas depends, among other factors, upon a reliable coupling of a meteorological forecast system to a hydrodynamic and wave system. This study evaluates the predictive skills of the coupled circulation and wind-wave model system (ADCIRC+SWAN) for simulating storm tides in the Chesapeake Bay, forced by six different products: (1) Global Forecast System (GFS), (2) Climate Forecast System (CFS) version 2, (3) North American Mesoscale Forecast System (NAM), (4) Rapid Refresh (RAP), (5) European Center for Medium-Range Weather Forecasts (ECMWF), and (6) the Atlantic hurricane database (HURDAT2). This evaluation is based on the hindcasting of four events: Irene (2011), Sandy (2012), Joaquin (2015), and Jonas (2016). By comparing the simulated water levels to observations at 13 monitoring stations, we have found that the ADCIR+SWAN System forced by the following: (1) the HURDAT2-based system exhibited the weakest statistical skills owing to a noteworthy overprediction of the simulated wind speed; (2) the ECMWF, RAP, and NAM products captured the moment of the peak and moderately its magnitude during all storms, with a correlation coefficient ranging between 0.98 and 0.77; (3) the CFS system exhibited the worst averaged root-mean-square difference (excepting HURDAT2); (4) the GFS system (the lowest horizontal resolution product tested) resulted in a clear underprediction of the maximum water elevation. Overall, the simulations forced by NAM and ECMWF systems induced the most accurate results best accuracy to support water level forecasting in the Chesapeake Bay during both tropical and extra-tropical storms.

  4. Evaluation of Maximum a Posteriori Estimation as Data Assimilation Method for Forecasting Infiltration-Inflow Affected Urban Runoff with Radar Rainfall Input

    Directory of Open Access Journals (Sweden)

    Jonas W. Pedersen

    2016-09-01

    Full Text Available High quality on-line flow forecasts are useful for real-time operation of urban drainage systems and wastewater treatment plants. This requires computationally efficient models, which are continuously updated with observed data to provide good initial conditions for the forecasts. This paper presents a way of updating conceptual rainfall-runoff models using Maximum a Posteriori estimation to determine the most likely parameter constellation at the current point in time. This is done by combining information from prior parameter distributions and the model goodness of fit over a predefined period of time that precedes the forecast. The method is illustrated for an urban catchment, where flow forecasts of 0–4 h are generated by applying a lumped linear reservoir model with three cascading reservoirs. Radar rainfall observations are used as input to the model. The effects of different prior standard deviations and lengths of the auto-calibration period on the resulting flow forecast performance are evaluated. We were able to demonstrate that, if properly tuned, the method leads to a significant increase in forecasting performance compared to a model without continuous auto-calibration. Delayed responses and erratic behaviour in the parameter variations are, however, observed and the choice of prior distributions and length of auto-calibration period is not straightforward.

  5. Power plant asset market evaluations: Forecasting the costs of power production

    Energy Technology Data Exchange (ETDEWEB)

    Lefton, S.A.; Grunsrud, G.P. [Aptech Engineering Services, Inc., Sunnyvale, CA (United States)

    1998-12-31

    This presentation discusses the process of evaluating and valuing power plants for sale. It describes a method to forecast the future costs at a power plant using a portion of the past fixed costs, variable energy costs, and most importantly the variable cycling-related wear-and-tear costs. The presentation then discusses how to best determine market share, expected revenues, and then to forecast plant future costs based on future expected unit cycling operations. The presentation concludes with a section on recommendations to power plant buyers or sellers on how to manage the power plant asset and how to increase its market value. (orig.) 4 refs.

  6. THE FORECAST OF VALUES FOR EVALUATION IN COORDINATIVE CAPACITY AT ALPINE SKIERS BEGINNERS

    Directory of Open Access Journals (Sweden)

    Elena Rată

    2009-06-01

    Full Text Available The paper proposes itself to present some methods of forecasting the values of coordinative capacities,evaluated through equilibrium and motor memory tests, during training programs of alpine skiers in the beginner class. These studies have lead to new methods and techniques of mathematical approximation of data usingpolynomial functions of result apportionment for the analyzed groups.

  7. The SPoRT-WRF: Evaluating the Impact of NASA Datasets on Convective Forecasts

    Science.gov (United States)

    Zavodsky, Bradley; Kozlowski, Danielle; Case, Jonathan; Molthan, Andrew

    2012-01-01

    Short-term Prediction Research and Transition (SPoRT) seeks to improve short-term, regional weather forecasts using unique NASA products and capabilities SPoRT has developed a unique, real-time configuration of the NASA Unified Weather Research and Forecasting (WRF)WRF (ARW) that integrates all SPoRT modeling research data: (1) 2-km SPoRT Sea Surface Temperature (SST) Composite, (2) 3-km LIS with 1-km Greenness Vegetation Fraction (GVFs) (3) 45-km AIRS retrieved profiles. Transitioned this real-time forecast to NOAA's Hazardous Weather Testbed (HWT) as deterministic model at Experimental Forecast Program (EFP). Feedback from forecasters/participants and internal evaluation of SPoRT-WRF shows a cool, dry bias that appears to suppress convection likely related to methodology for assimilation of AIRS profiles Version 2 of the SPoRT-WRF will premier at the 2012 EFP and include NASA physics, cycling data assimilation methodology, better coverage of precipitation forcing, and new GVFs

  8. Evaluation of radar-based precipitation estimates for flash flood forecasting in the Three Gorges Region

    Directory of Open Access Journals (Sweden)

    Z. Li

    2015-05-01

    Full Text Available Spatial rainfall pattern plays a critical role in determining hydrological responses in mountainous areas, especially for natural disasters such as flash floods. In this study, to improve the skills of flood forecasting in the mountainous Three Gorges Region (TGR of the Yangtze River, we developed a first version of a high-resolution (1 km radar-based quantitative precipitation estimation (QPE consideration of many critical procedures, such as beam blockage analysis, ground-clutter filter, rain type identification and adaptive Z–R relations. A physically-based distributed hydrological model (GBHM was established and further applied to evaluate the performance of radar-based QPE for regional flood forecasting, relative to the gauge-driven simulations. With two sets of input data (gauge and radar collected during summer 2010, the applicability of the current radar-based QPE to rainstorm monitoring and flash flood forecasting in the TGR is quantitatively analysed and discussed.

  9. Evaluation of the CPTEC/AGCM wind forecasts during the hurricane Catarina occurrence

    Directory of Open Access Journals (Sweden)

    A. F. Santos

    2008-05-01

    Full Text Available In March 2004 occurred the first hurricane registered at South Atlantic Ocean. The system named Catarina begun as an extratropical cyclone and remained quasi-stationary some days over the South Atlantic Ocean. The system displaced westward, acquiring characteristics of a hurricane and hit the Brazilian State of Santa Catarina (SC between the 27 and the 28 March, causing destruction and deaths. The objective of this paper is to evaluate the Center for Weather Prediction and Climate Studies, Atmospheric Global Circulation Model (CPTEC/AGCM forecast performance of some synoptic patterns associated with Catarina. The surface wind and reduced Sea Level Pressure (SLP were examined. Moreover, the implementation of 10-m wind forecast (V10m was evaluated. This variable was not available in the CPTEC/AGCM during the Catarina occurrence and in this study it was compared with the wind at first sigma-level of the AGCM. The CPTEC-Eta reanalyses were used to comparisons. According to reanalyses, more intense winds were observed in northeast, south and southwest edges of the cyclone. The system was not predicted by the CPTEC/AGCM forecasts longer than 24 h, then the analyses were carried out only for 24 h forecasts. In general, the first sigma-level wind forecasts underestimated the wind magnitude and the cyclone intensity. However, the Catarina formation and its displacement southeastward between the 20 and the 21 March were well represented by the model. The CPTEC/AGCM presents deficiencies to predict the system intensity, but in short-range forecasts it was possible to predict the system formation and its atypical trajectory. The wind results from the new implementation did not exhibit better performance compared with the wind at first sigma-level. These results will be better investigated in the future.

  10. Evaluation of the CPTEC/AGCM wind forecasts during the hurricane Catarina occurrence

    Science.gov (United States)

    Santos, A. F.; Mendonça, A. M.; Bonatti, J. P.; de Mattos, J. G. Z.; Kubota, P. Y.; Freitas, S. R.; Silva Dias, M. A. F.; Ramirez, E.; Camayo, R.

    2008-05-01

    In March 2004 occurred the first hurricane registered at South Atlantic Ocean. The system named Catarina begun as an extratropical cyclone and remained quasi-stationary some days over the South Atlantic Ocean. The system displaced westward, acquiring characteristics of a hurricane and hit the Brazilian State of Santa Catarina (SC) between the 27 and the 28 March, causing destruction and deaths. The objective of this paper is to evaluate the Center for Weather Prediction and Climate Studies, Atmospheric Global Circulation Model (CPTEC/AGCM) forecast performance of some synoptic patterns associated with Catarina. The surface wind and reduced Sea Level Pressure (SLP) were examined. Moreover, the implementation of 10-m wind forecast (V10m) was evaluated. This variable was not available in the CPTEC/AGCM during the Catarina occurrence and in this study it was compared with the wind at first sigma-level of the AGCM. The CPTEC-Eta reanalyses were used to comparisons. According to reanalyses, more intense winds were observed in northeast, south and southwest edges of the cyclone. The system was not predicted by the CPTEC/AGCM forecasts longer than 24 h, then the analyses were carried out only for 24 h forecasts. In general, the first sigma-level wind forecasts underestimated the wind magnitude and the cyclone intensity. However, the Catarina formation and its displacement southeastward between the 20 and the 21 March were well represented by the model. The CPTEC/AGCM presents deficiencies to predict the system intensity, but in short-range forecasts it was possible to predict the system formation and its atypical trajectory. The wind results from the new implementation did not exhibit better performance compared with the wind at first sigma-level. These results will be better investigated in the future.

  11. Evaluation of Nonparametric Probabilistic Forecasts of Wind Power

    DEFF Research Database (Denmark)

    Pinson, Pierre; Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg, orlov 31.07.2008

    Predictions of wind power production for horizons up to 48-72 hour ahead comprise a highly valuable input to the methods for the daily management or trading of wind generation. Today, users of wind power predictions are not only provided with point predictions, which are estimates of the most...

  12. Evaluation of a conceptual rainfall forecasting model from observed and simulated rain events

    Directory of Open Access Journals (Sweden)

    L. Dolciné

    1998-01-01

    Full Text Available Very short-term rainfall forecasting models designed for runoff analysis of catchments, particularly those subject to flash-floods, typically include one or more variables deduced from weather radars. Useful variables for defining the state and evolution of a rain system include rainfall rate, vertically integrated rainwater content and advection velocity. The forecast model proposed in this work complements recent dynamical formulations by focusing on a formulation incorporating these variables using volumetric radar data to define the model state variables, determining the rainfall source term directly from multi-scan radar data, explicitly accounting for orographic enhancement, and explicitly incorporating the dynamical model components in an advection-diffusion scheme. An evaluation of this model is presented for four rain events collected in the South of France and in the North-East of Italy. Model forecasts are compared with two simple methods: persistence and extrapolation. An additional analysis is performed using an existing mono-dimensional microphysical meteorological model to produce simulated rain events and provide initialization data. Forecasted rainfall produced by the proposed model and the extrapolation method are compared to the simulated events. The results show that the forecast model performance is influenced by rainfall temporal variability and performance is better for less variable rain events. The comparison with the extrapolation method shows that the proposed model performs better than extrapolation in the initial period of the forecast lead-time. It is shown that the performance of the proposed model over the extrapolation method depends essentially on the additional vertical information available from voluminal radar.

  13. Evaluation of climatic forecasts of rainfall for the Tlaxcala State (Mexico): 1998-2002

    Energy Technology Data Exchange (ETDEWEB)

    Gay Garcia, C. [Centro de Ciencias de la Atmosfera, Universidad Nacional Autonoma de Mexico (UNAM), Mexico, D.F. (Mexico); Hernandez Vazquez, M.; Jimenez Lopez, J. [Centro de Investigaciones en Ciencias Biologicas, Universidad Autonoma de Tlaxcala, Tlaxcala (Mexico); Lezama Gutierrez, J. [Departamento de Agrobiologia, Universidad Autonoma de Tlaxcala, Tlaxcala (Mexico); Magana Rueda, V.O.; Morales Acoltzi, T. [Centro de Ciencias de la Atmosfera, Universidad Nacional Autonoma de Mexico, UNAM, Mexico, D.F. (Mexico); Orozco Flores, S. [Centro de Investigaciones en Ciencias Biologicas, Universidad Autonoma de Tlaxcala, Tlaxcala (Mexico)

    2004-07-01

    During the second semester of 1997 the Project Utilizacion de pronosticos climaticos para actividades agricolas de Tlaxcala was instrumented with the purpose of aiding decision making in agricultural activities in the estate of Tlaxcala, Mexico. The main objective of the project was to characterize extreme values of precipitation associated with El Nino/La Nina events, to produce useful forecasts for decision making. This was achieved through close contacts with the farmers whose specific needs were taken into account to the extent possible. In a sense such forecasts became forecasts watched over by producers. The method of ensemble of analogs was applied to historical data. The evaluation of annual and monthly forecasts is presented here. The results show that knowledge about the regional climate has been gained as it is reflected by the skill of the method to forecast. The forecast for the region, for the year 2003 is analyzed in terms of the precipitation anomalies. [Spanish] En el segundo semestre de 1997, se implemento el proyecto de investigacion Utilizacion de pronosticos climaticos para actividades agricolas en el estado de Tlaxcala. El objetivo principal del proyecto original fue el de caracterizar valores extremos de precipitacion asociados a los eventos El Nino/La Nina, producir pronosticos mensuales de precipitacion que fueran practicos en la toma de decisiones para los cultivos de temporal. Esto ultimo fue discutido con los productores cuyas necesidades y sugerencias fueron tomadas en cuenta, considerando un pronostico lo mas extendido posible. De esta manera los pronosticos se tornaron Pronosticos vigilados por los productores. El metodo de ensamble de analogos observados fue aplicado para generar los pronosticos de 1998-2002. La evaluacion de los pronosticos anuales y mensuales se presenta aqui. Los resultados muestran que se ha ganado conocimiento acerca del clima regional, como se refleja en la habilidad del metodo para pronosticar. Por ultimo, se

  14. A real-time evaluation and demonstration of strategies for 'Over-The-Loop' ensemble streamflow forecasting in US watersheds

    Science.gov (United States)

    Wood, Andy; Clark, Elizabeth; Mendoza, Pablo; Nijssen, Bart; Newman, Andy; Clark, Martyn; Nowak, Kenneth; Arnold, Jeffrey

    2017-04-01

    Many if not most national operational streamflow prediction systems rely on a forecaster-in-the-loop approach that require the hands-on-effort of an experienced human forecaster. This approach evolved from the need to correct for long-standing deficiencies in the models and datasets used in forecasting, and the practice often leads to skillful flow predictions despite the use of relatively simple, conceptual models. Yet the 'in-the-loop' forecast process is not reproducible, which limits opportunities to assess and incorporate new techniques systematically, and the effort required to make forecasts in this way is an obstacle to expanding forecast services - e.g., though adding new forecast locations or more frequent forecast updates, running more complex models, or producing forecast and hindcasts that can support verification. In the last decade, the hydrologic forecasting community has begun develop more centralized, 'over-the-loop' systems. The quality of these new forecast products will depend on their ability to leverage research in areas including earth system modeling, parameter estimation, data assimilation, statistical post-processing, weather and climate prediction, verification, and uncertainty estimation through the use of ensembles. Currently, many national operational streamflow forecasting and water management communities have little experience with the strengths and weaknesses of over-the-loop approaches, even as such systems are beginning to be deployed operationally in centers such as ECMWF. There is thus a need both to evaluate these forecasting advances and to demonstrate their potential in a public arena, raising awareness in forecast user communities and development programs alike. To address this need, the US National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the US Army Corps of Engineers, using the NCAR 'System for Hydromet Analysis Research and Prediction Applications

  15. Evaluating uncertainty estimates in hydrologic models: borrowing measures from the forecast verification community

    Directory of Open Access Journals (Sweden)

    K. J. Franz

    2011-11-01

    Full Text Available The hydrologic community is generally moving towards the use of probabilistic estimates of streamflow, primarily through the implementation of Ensemble Streamflow Prediction (ESP systems, ensemble data assimilation methods, or multi-modeling platforms. However, evaluation of probabilistic outputs has not necessarily kept pace with ensemble generation. Much of the modeling community is still performing model evaluation using standard deterministic measures, such as error, correlation, or bias, typically applied to the ensemble mean or median. Probabilistic forecast verification methods have been well developed, particularly in the atmospheric sciences, yet few have been adopted for evaluating uncertainty estimates in hydrologic model simulations. In the current paper, we overview existing probabilistic forecast verification methods and apply the methods to evaluate and compare model ensembles produced from two different parameter uncertainty estimation methods: the Generalized Uncertainty Likelihood Estimator (GLUE, and the Shuffle Complex Evolution Metropolis (SCEM. Model ensembles are generated for the National Weather Service SACramento Soil Moisture Accounting (SAC-SMA model for 12 forecast basins located in the Southeastern United States. We evaluate the model ensembles using relevant metrics in the following categories: distribution, correlation, accuracy, conditional statistics, and categorical statistics. We show that the presented probabilistic metrics are easily adapted to model simulation ensembles and provide a robust analysis of model performance associated with parameter uncertainty. Application of these methods requires no information in addition to what is already available as part of traditional model validation methodology and considers the entire ensemble or uncertainty range in the approach.

  16. Evaluating uncertainty estimates in hydrologic models: borrowing measures from the forecast verification community

    Science.gov (United States)

    Franz, K. J.; Hogue, T. S.

    2011-11-01

    The hydrologic community is generally moving towards the use of probabilistic estimates of streamflow, primarily through the implementation of Ensemble Streamflow Prediction (ESP) systems, ensemble data assimilation methods, or multi-modeling platforms. However, evaluation of probabilistic outputs has not necessarily kept pace with ensemble generation. Much of the modeling community is still performing model evaluation using standard deterministic measures, such as error, correlation, or bias, typically applied to the ensemble mean or median. Probabilistic forecast verification methods have been well developed, particularly in the atmospheric sciences, yet few have been adopted for evaluating uncertainty estimates in hydrologic model simulations. In the current paper, we overview existing probabilistic forecast verification methods and apply the methods to evaluate and compare model ensembles produced from two different parameter uncertainty estimation methods: the Generalized Uncertainty Likelihood Estimator (GLUE), and the Shuffle Complex Evolution Metropolis (SCEM). Model ensembles are generated for the National Weather Service SACramento Soil Moisture Accounting (SAC-SMA) model for 12 forecast basins located in the Southeastern United States. We evaluate the model ensembles using relevant metrics in the following categories: distribution, correlation, accuracy, conditional statistics, and categorical statistics. We show that the presented probabilistic metrics are easily adapted to model simulation ensembles and provide a robust analysis of model performance associated with parameter uncertainty. Application of these methods requires no information in addition to what is already available as part of traditional model validation methodology and considers the entire ensemble or uncertainty range in the approach.

  17. Evaluation of Optimized WRF Precipitation Forecast over a Complex Topography Region during Flood Season

    Directory of Open Access Journals (Sweden)

    Yuan Li

    2016-11-01

    Full Text Available In recent years, the Weather Research and Forecast (WRF model has been utilized to generate quantitative precipitation forecasts with higher spatial and temporal resolutions. However, factors including horizontal resolution, domain size, and the physical parameterization scheme have a strong impact on the dynamic downscaling ability of the WRF model. In this study, the influence of these factors has been analyzed in precipitation forecasting for the Xijiang Basin, southern China—a region with complex topography. The results indicate that higher horizontal resolutions always result in higher Critical Success Indexes (CSI, but higher biases as well. Meanwhile, the precipitation forecast skills are also influenced by the combination of microphysics parameterization scheme and cumulus convective parameterization scheme. On the basis of these results, an optimized configuration of the WRF model is built in which the horizontal resolution is 10 km, the microphysics parameterization is the Lin scheme, and the cumulus convective parameterization is the Betts–Miller–Janjic scheme. This configuration is then evaluated by simulating the daily weather during the 2013–2014 flood season. The high Critical Success Index scores and low biases at various thresholds and lead times confirm the high accuracy of the optimized WRF model configuration for Xijiang Basin. However, the performance of the WRF model varies from different sub-basins due to the complexity of the mesoscale convective system (MCS over this region.

  18. Evaluation of empirical attributes for credit risk forecasting from numerical data

    Directory of Open Access Journals (Sweden)

    Augustinos Dimitras

    2017-03-01

    Full Text Available In this research, the authors proposed a new method to evaluate borrowers’ credit risk and quality of financial statements information provided. They use qualitative and quantitative criteria to measure the quality and the reliability of its credit customers. Under this statement, the authors evaluate 35 features that are empirically utilized for forecasting the borrowers’ credit behavior of a Greek Bank. These features are initially selected according to universally accepted criteria. A set of historical data was collected and an extensive data analysis is performed by using non parametric models. Our analysis revealed that building simplified model by using only three out of the thirty five initially selected features one can achieve the same or slightly better forecasting accuracy when compared to the one achieved by the model uses all the initial features. Also, experimentally verified claim that universally accepted criteria can’t be globally used to achieve optimal results is discussed.

  19. Evaluating the Impact of the Summit Station, Greenland Radiosonde Program on Science and Forecast Services

    Science.gov (United States)

    Martinez, C. J.; Starkweather, S.; Cox, C. J.; Solomon, A.; Shupe, M.

    2015-12-01

    Radiosondes are balloon-borne meteorological sensors used to acquire profiles of temperature and humidity. Radiosonde data are essential inputs for numerical weather prediction models and are used for climate research, particularly in the creation of reanalysis products. However, radiosonde programs are costly to maintain, in particular in the remote regions of the Arctic (e.g., $440,000/yr at Summit, Greenland), where only 40 of approximately 1000 routine global launches are made. The climate of this data-sparse region is poorly understood and forecast data assimilation procedures are designed for global applications. Thus, observations may be rejected from the data assimilation because they are too far from the model expectations. For the most cost-efficient deployment of resources and to improve forecasting methods, analyses of the effectiveness of individual radiosonde programs are necessary. Here, we evaluate how radiosondes launched twice daily (0 and 12 UTC) from Summit Station, Greenland, (72.58⁰N, 38.48⁰W, 3210 masl) influence the European Centre for Medium Range Weather Forecasting (ECMWF) operational forecasts from June 2013 through May of 2015. A statistical analysis is conducted to determine the impact of the observations on the forecast model and the meteorological regimes that the model fails to reproduce are identified. Assimilation rates in the inversion layer are lower than any other part of the troposphere. Above the inversion, assimilation rates range from 85%-100%, 60%-98%, and > 99% for temperature, humidity, and wind, respectively. The lowest assimilation rates are found near the surface, possibly associated with biases in the representation of the temperature inversion by the ECMWF model at Summit. Consequently, assimilation rates are lower near the surface during winter when strong temperature inversions are frequently observed. Our findings benefit the scientific community who uses this information for climatological analysis of the

  20. Evaluating the Impact of the Summit Station, Greenland Radiosonde Program on Data Modelers and Forecast Services

    Science.gov (United States)

    Martinez, C. J.; Starkweather, S.; Cox, C. J.; Solomon, A.; Shupe, M.

    2015-12-01

    Radiosondes are balloon-borne meteorological sensors used to acquire profiles of temperature and humidity. Radiosonde data are essential inputs for numerical weather prediction models and are used for climate research, particularly in the creation of reanalysis products. However, radiosonde programs are costly to maintain, in particular in the remote regions of the Arctic (e.g., $440,000/yr at Summit, Greenland), where only 40 of approximately 1000 routine global launches are made. The climate of this data-sparse region is poorly understood and forecast data assimilation procedures are designed for global applications. Thus, observations may be rejected from the data assimilation because they are too far from the model expectations. For the most cost-efficient deployment of resources and to improve forecasting methods, analyses of the effectiveness of individual radiosonde programs are necessary. Here, we evaluate how radiosondes launched twice daily (0 and 12 UTC) from Summit Station, Greenland, (72.58⁰N, 38.48⁰W, 3210 masl) influence the European Centre for Medium Range Weather Forecasting (ECMWF) operational forecasts from June 2013 through May of 2015. A statistical analysis is conducted to determine the impact of the observations on the forecast model and the meteorological regimes that the model fails to reproduce are identified. Assimilation rates in the inversion layer are lower than any other part of the troposphere. Above the inversion, assimilation rates range from 85%-100%, 60%-98%, and > 99% for temperature, humidity, and wind, respectively. The lowest assimilation rates are found near the surface, possibly associated with biases in the representation of the temperature inversion by the ECMWF model at Summit. Consequently, assimilation rates are lower near the surface during winter when strong temperature inversions are frequently observed. Our findings benefit the scientific community who uses this information for climatological analysis of the

  1. Forecasting methodologies for Ganoderma spore concentration using combined statistical approaches and model evaluations.

    Science.gov (United States)

    Sadyś, Magdalena; Skjøth, Carsten Ambelas; Kennedy, Roy

    2016-04-01

    High concentration levels of Ganoderma spp. spores were observed in Worcester, UK, during 2006-2010. These basidiospores are known to cause sensitization due to the allergen content and their small dimensions. This enables them to penetrate the lower part of the respiratory tract in humans. Establishment of a link between occurring symptoms of sensitization to Ganoderma spp. and other basidiospores is challenging due to lack of information regarding spore concentration in the air. Hence, aerobiological monitoring should be conducted, and if possible extended with the construction of forecast models. Daily mean concentration of allergenic Ganoderma spp. spores in the atmosphere of Worcester was measured using 7-day volumetric spore sampler through five consecutive years. The relationships between the presence of spores in the air and the weather parameters were examined. Forecast models were constructed for Ganoderma spp. spores using advanced statistical techniques, i.e. multivariate regression trees and artificial neural networks. Dew point temperature along with maximum temperature was the most important factor influencing the presence of spores in the air of Worcester. Based on these two major factors and several others of lesser importance, thresholds for certain levels of fungal spore concentration, i.e. low (0-49 s m(-3)), moderate (50-99 s m(-3)), high (100-149 s m(-3)) and very high (150 forecasting model, which was accurate (correlation between observed and predicted values varied from r s = 0.57 to r s = 0.68).

  2. Advances in Landslide Hazard Forecasting: Evaluation of Global and Regional Modeling Approach

    Science.gov (United States)

    Kirschbaum, Dalia B.; Adler, Robert; Hone, Yang; Kumar, Sujay; Peters-Lidard, Christa; Lerner-Lam, Arthur

    2010-01-01

    A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that exhibit a high potential for landslide activity by combining a calculation of landslide susceptibility with satellite-derived rainfall estimates. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale landslide forecasting efforts, it requires several modifications before it can be fully realized as an operational tool. The evaluation finds that the landslide forecasting may be more feasible at a regional scale. This study draws upon a prior work's recommendations to develop a new approach for considering landslide susceptibility and forecasting at the regional scale. This case study uses a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America: Guatemala, Honduras, EI Salvador and Nicaragua. A regional susceptibility map is calculated from satellite and surface datasets using a statistical methodology. The susceptibility map is tested with a regional rainfall intensity-duration triggering relationship and results are compared to global algorithm framework for the Hurricane Mitch event. The statistical results suggest that this regional investigation provides one plausible way to approach some of the data and resolution issues identified in the global assessment, providing more realistic landslide forecasts for this case study. Evaluation of landslide hazards for this extreme event helps to identify several potential improvements of the algorithm framework, but also highlights several remaining challenges for the algorithm assessment, transferability and performance accuracy. Evaluation challenges include representation errors from comparing susceptibility maps of different spatial resolutions, biases in event-based landslide inventory data, and limited nonlandslide event data for more comprehensive evaluation. Additional factors that may improve

  3. Evaluation of point mutations in dystrophin gene in Iranian ...

    Indian Academy of Sciences (India)

    [Haghshenas M., Akbari M. T., Zare Karizi S., Khordadpoor Deilamani F., Nafissi S. and Salehi Z. 2016 Evaluation of point mutations in dystrophin gene in Iranian Duchenne .... PCR product (bp). Annealing temperature. Exon 44. CTTGATCCATATGCTTTTACCTGCA. 268. 59. TCCATCACCCTTCAGAACCTGACCT. Exon 50.

  4. Point evaluation and Hardy space : the multiscale case

    NARCIS (Netherlands)

    Alpay, Daniel; Dijksma, Aad; Volok, Dan

    2005-01-01

    We define a point evaluation for transfer operators of multiscale causal dissipative systems. We associate to such a system a de Branges Rovnyak space, which serves as the state space of a coisometric realization.

  5. AN EVALUATION OF USA UNEMPLOYMENT RATE FORECASTS IN TERMS OF ACCURACY AND BIAS. EMPIRICAL METHODS TO IMPROVE THE FORECASTS ACCURACY

    Directory of Open Access Journals (Sweden)

    BRATU (SIMIONESCU MIHAELA

    2013-02-01

    Full Text Available The most accurate forecasts for USA unemployment rate on the horizon 2001-2012, according to U1 Theil’s coefficient and to multi-criteria ranking methods, were provided by International Monetary Fund (IMF, being followed by other institutions as: Organization for Economic Co-operation and Development (OECD, Congressional Budget Office (CBO and Blue Chips (BC. The multi-criteria ranking methods were applied to solve the divergence in assessing the accuracy, differences observed by computing five chosen measures of accuracy: U1 and U2 statistics of Theil, mean error, mean squared error, root mean squared error. Some strategies of improving the accuracy of the predictions provided by the four institutions, which are biased in all cases, excepting BC, were proposed. However, these methods did not generate unbiased forecasts. The predictions made by IMF and OECD for 2001-2012 can be improved by constructing combined forecasts, the INV approach and the scheme proposed by author providing the most accurate expections. The BC forecasts can be improved by smoothing the predictions using Holt-Winters method and Hodrick - Prescott filter.

  6. Impact of single-point GPS integrated water vapor estimates on short-range WRF model forecasts over southern India

    Science.gov (United States)

    Kumar, Prashant; Gopalan, Kaushik; Shukla, Bipasha Paul; Shyam, Abhineet

    2017-11-01

    Specifying physically consistent and accurate initial conditions is one of the major challenges of numerical weather prediction (NWP) models. In this study, ground-based global positioning system (GPS) integrated water vapor (IWV) measurements available from the International Global Navigation Satellite Systems (GNSS) Service (IGS) station in Bangalore, India, are used to assess the impact of GPS data on NWP model forecasts over southern India. Two experiments are performed with and without assimilation of GPS-retrieved IWV observations during the Indian winter monsoon period (November-December, 2012) using a four-dimensional variational (4D-Var) data assimilation method. Assimilation of GPS data improved the model IWV analysis as well as the subsequent forecasts. There is a positive impact of ˜10 % over Bangalore and nearby regions. The Weather Research and Forecasting (WRF) model-predicted 24-h surface temperature forecasts have also improved when compared with observations. Small but significant improvements were found in the rainfall forecasts compared to control experiments.

  7. Evaluation and intercomparison of air quality forecasts over Korea during the KORUS-AQ campaign

    Science.gov (United States)

    Lee, Seungun; Park, Rokjin J.; Kim, Soontae; Song, Chul H.; Kim, Cheol-Hee; Woo, Jung-Hun

    2017-04-01

    We evaluate and intercompare ozone and aerosol simulations over Korea during the KORUS-AQ campaign, which was conducted in May-June 2016. Four global and regional air quality models participated in the campaign and provided daily air quality forecasts over Korea to guide aircraft flight paths for detecting air pollution events over Korean peninsula and its nearby oceans. We first evaluate the model performance by comparing simulated and observed hourly surface ozone and PM2.5 concentrations at ground sites in Korea and find that the models successfully capture intermittent air pollution events and reproduce the daily variation of ozone and PM2.5 concentrations. However, significant underestimates of peak ozone concentrations in the afternoon are also found in most models. Among chemical constituents of PM2.5, the models typically overestimate observed nitrate aerosol concentrations and underestimate organic aerosol concentrations, although the observed mass concentrations of PM2.5 are seemingly reproduced by the models. In particular, all models used the same anthropogenic emission inventory (KU-CREATE) for daily air quality forecast, but they show a considerable discrepancy for ozone and aerosols. Compared to individual model results, the ensemble mean of all models shows the best performance with correlation coefficients of 0.73 for ozone and 0.57 for PM2.5. We here investigate contributing factors to the discrepancy, which will serve as a guidance to improve the performance of the air quality forecast.

  8. Evaluation of artificial neural network techniques for flow forecasting in the River Yangtze, China

    Directory of Open Access Journals (Sweden)

    C. W. Dawson

    2002-01-01

    Full Text Available While engineers have been quantifying rainfall-runoff processes since the mid-19th century, it is only in the last decade that artificial neural network models have been applied to the same task. This paper evaluates two neural networks in this context: the popular multilayer perceptron (MLP, and the radial basis function network (RBF. Using six-hourly rainfall-runoff data for the River Yangtze at Yichang (upstream of the Three Gorges Dam for the period 1991 to 1993, it is shown that both neural network types can simulate river flows beyond the range of the training set. In addition, an evaluation of alternative RBF transfer functions demonstrates that the popular Gaussian function, often used in RBF networks, is not necessarily the ‘best’ function to use for river flow forecasting. Comparisons are also made between these neural networks and conventional statistical techniques; stepwise multiple linear regression, auto regressive moving average models and a zero order forecasting approach. Keywords: Artificial neural network, multilayer perception, radial basis function, flood forecasting

  9. Research on quality evaluation and forecast control in assembly process for complex products

    Science.gov (United States)

    Pang, Jihong; Xue, Xiaobo; Jin, Yini; Li, Yongchao

    2017-05-01

    Assembly quality affects complex product’s performance in high degree because the assembly is the end of manufacture process. In this paper, a comprehensive evaluation and forecast control of various factors affecting assembly failure is presented based on theory of gray system. Firstly, the absolute correlation degree and relative degree of correlation are calculated by using data from assembly process of complex products. Then, the comprehensive correlation degree and rank analysis are obtained with the gray method. Finally, the gray system theory is used in quality analysis and forecast control of a valve manufacturer. The final result indicates that excess amount of leakage is the main factor affecting product quality in accord with the actual situation.

  10. Multiple "buy buttons" in the brain: Forecasting chocolate sales at point-of-sale based on functional brain activation using fMRI.

    Science.gov (United States)

    Kühn, Simone; Strelow, Enrique; Gallinat, Jürgen

    2016-08-01

    We set out to forecast consumer behaviour in a supermarket based on functional magnetic resonance imaging (fMRI). Data was collected while participants viewed six chocolate bar communications and product pictures before and after each communication. Then self-reports liking judgement were collected. fMRI data was extracted from a priori selected brain regions: nucleus accumbens, medial orbitofrontal cortex, amygdala, hippocampus, inferior frontal gyrus, dorsomedial prefrontal cortex assumed to contribute positively and dorsolateral prefrontal cortex and insula were hypothesized to contribute negatively to sales. The resulting values were rank ordered. After our fMRI-based forecast an instore test was conducted in a supermarket on n=63.617 shoppers. Changes in sales were best forecasted by fMRI signal during communication viewing, second best by a comparison of brain signal during product viewing before and after communication and least by explicit liking judgements. The results demonstrate the feasibility of applying neuroimaging methods in a relatively small sample to correctly forecast sales changes at point-of-sale. Copyright © 2016. Published by Elsevier Inc.

  11. Evaluation of effect of initial condition on seasonal interannual streamflow forecasting system in Rangitata and Waitaiki river basins (New Zealand)

    Science.gov (United States)

    Zammit, C.; Singh, S.; Hreinsson, E.; Woods, R. A.; Clark, M. P.; Hamlet, A. F.

    2012-12-01

    New Zealand currently does not have a centralized, comprehensive, and state-of-the-art system in place for providing operational seasonal to interannual streamflow forecasts to guide water resources management decisions. As a pilot effort, we implement and evaluate an experimental ensemble streamflow forecasting system for the Waitaki and Rangitata River basins on New Zealand's South Island using a hydrologic simulation model (TopNet) and the familiar ensemble streamflow prediction (ESP) paradigm for estimating forecast uncertainty. To provide a comprehensive database for evaluation of the forecasting system, first a set of retrospective model states simulated by the hydrologic model on the first day of each month were archived from 1972-2009. Then, using the hydrologic simulation model, each of these historical model states was paired with the retrospective temperature and precipitation time series from each historical water year to create a database of retrospective hindcasts. Using the resulting database, the relative importance of initial state variables (such as soil moisture and snowpack) as fundamental drivers of uncertainties in forecasts were evaluated for different seasons and lead times. The analysis indicates that the sensitivity of seasonal flow forecast to intial condition uncertainty is limited. As a result seasonal hydrological forecast based on ESP technique may be plausible in South island New Zealand catchment

  12. Evaluation of terrestrial photogrammetric point clouds derived from thermal imagery

    Science.gov (United States)

    Metcalf, Jeremy P.; Olsen, Richard C.

    2016-05-01

    Computer vision and photogrammetric techniques have been widely applied to digital imagery producing high density 3D point clouds. Using thermal imagery as input, the same techniques can be applied to infrared data to produce point clouds in 3D space, providing surface temperature information. The work presented here is an evaluation of the accuracy of 3D reconstruction of point clouds produced using thermal imagery. An urban scene was imaged over an area at the Naval Postgraduate School, Monterey, CA, viewing from above as with an airborne system. Terrestrial thermal and RGB imagery were collected from a rooftop overlooking the site using a FLIR SC8200 MWIR camera and a Canon T1i DSLR. In order to spatially align each dataset, ground control points were placed throughout the study area using Trimble R10 GNSS receivers operating in RTK mode. Each image dataset is processed to produce a dense point cloud for 3D evaluation.

  13. Developing a heatwave early warning system for Sweden: evaluating sensitivity of different epidemiological modelling approaches to forecast temperatures.

    Science.gov (United States)

    Åström, Christofer; Ebi, Kristie L; Langner, Joakim; Forsberg, Bertil

    2014-12-23

    Over the last two decades a number of heatwaves have brought the need for heatwave early warning systems (HEWS) to the attention of many European governments. The HEWS in Europe are operating under the assumption that there is a high correlation between observed and forecasted temperatures. We investigated the sensitivity of different temperature mortality relationships when using forecast temperatures. We modelled mortality in Stockholm using observed temperatures and made predictions using forecast temperatures from the European Centre for Medium-range Weather Forecasts to assess the sensitivity. We found that the forecast will alter the expected future risk differently for different temperature mortality relationships. The more complex models seemed more sensitive to inaccurate forecasts. Despite the difference between models, there was a high agreement between models when identifying risk-days. We find that considerations of the accuracy in temperature forecasts should be part of the design of a HEWS. Currently operating HEWS do evaluate their predictive performance; this information should also be part of the evaluation of the epidemiological models that are the foundation in the HEWS. The most accurate description of the relationship between high temperature and mortality might not be the most suitable or practical when incorporated into a HEWS.

  14. Oil-points - Designers means to evaluate sustainability of concepts

    DEFF Research Database (Denmark)

    Bey, Niki; Lenau, Torben Anker

    1998-01-01

    Designers have an essential influence on product design and are therefore one target group for environmental evaluation methods. This implies, that such evaluation methods have to meet designers requirements. Evaluation of sustainability of products is often done using formal Life Cycle Assessment....... This is investigated by means of three case studies where environmental impact is estimated using the EDIP method, the Eco-indicator 95 method, and the Oil Point method proposed by the authors. It is found that the results obtained using Oil Points are in acceptable conformity with the results obtained with more...

  15. Evaluation of Radiation Belt Space Weather Forecasts for Internal Charging Analyses

    Science.gov (United States)

    Minow, Joseph I.; Coffey, Victoria N.; Jun, Insoo; Garrett, Henry B.

    2007-01-01

    A variety of static electron radiation belt models, space weather prediction tools, and energetic electron datasets are used by spacecraft designers and operations support personnel as internal charging code inputs to evaluate electrostatic discharge risks in space systems due to exposure to relativistic electron environments. Evaluating the environment inputs is often accomplished by comparing whether the data set or forecast tool reliability predicts measured electron flux (or fluence over a given period) for some chosen period. While this technique is useful as a model metric, it does not provide the information necessary to evaluate whether short term deviances of the predicted flux is important in the charging evaluations. In this paper, we use a 1-D internal charging model to compute electric fields generated in insulating materials as a function of time when exposed to relativistic electrons in the Earth's magnetosphere. The resulting fields are assumed to represent the "true" electric fields and are compared with electric field values computed from relativistic electron environments derived from a variety of space environment and forecast tools. Deviances in predicted fields compared to the "true" fields which depend on insulator charging time constants will be evaluated as a potential metric for determining the importance of predicted and measured relativistic electron flux deviations over a range of time scales.

  16. Ensemble hydromoeteorological forecasting in Denmark

    DEFF Research Database (Denmark)

    Lucatero Villasenor, Diana

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

  17. Evaluation of Wind Power Forecasts from the Vermont Weather Analytics Center and Identification of Improvements

    Energy Technology Data Exchange (ETDEWEB)

    Optis, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Scott, George N. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Draxl, Caroline [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2018-02-02

    The goal of this analysis was to assess the wind power forecast accuracy of the Vermont Weather Analytics Center (VTWAC) forecast system and to identify potential improvements to the forecasts. Based on the analysis at Georgia Mountain, the following recommendations for improving forecast performance were made: 1. Resolve the significant negative forecast bias in February-March 2017 (50% underprediction on average) 2. Improve the ability of the forecast model to capture the strong diurnal cycle of wind power 3. Add ability for forecast model to assess internal wake loss, particularly at sites where strong diurnal shifts in wind direction are present. Data availability and quality limited the robustness of this forecast assessment. A more thorough analysis would be possible given a longer period of record for the data (at least one full year), detailed supervisory control and data acquisition data for each wind plant, and more detailed information on the forecast system input data and methodologies.

  18. A review on the numerical simulation of equatorial plasma bubbles toward scintillation evaluation and forecasting

    Science.gov (United States)

    Yokoyama, Tatsuhiro

    2017-12-01

    Equatorial plasma bubbles (EPBs) have been a longstanding and increasingly important subject because they cause severe scintillations in radio waves from Global Navigation Satellite System satellites. The phenomenon was found in the 1930s as irregular ionosonde observations and was termed equatorial spread F (ESF). ESF is interpreted as plasma density irregularities associated with EPBs that have nonlinearly evolved into the topside ionosphere. Numerical simulations have been powerful tools to study the fully nonlinear evolution of EPBs, which cannot be wholly understood from theoretical predictions. In this paper, historical achievements in the numerical simulation of EPBs are reviewed, and future directions toward scintillation evaluation and forecast are discussed. [Figure not available: see fulltext.

  19. Forecasting methodologies for Ganoderma spore concentration using combined statistical approaches and model evaluations

    Science.gov (United States)

    Sadyś, Magdalena; Skjøth, Carsten Ambelas; Kennedy, Roy

    2016-04-01

    High concentration levels of Ganoderma spp. spores were observed in Worcester, UK, during 2006-2010. These basidiospores are known to cause sensitization due to the allergen content and their small dimensions. This enables them to penetrate the lower part of the respiratory tract in humans. Establishment of a link between occurring symptoms of sensitization to Ganoderma spp. and other basidiospores is challenging due to lack of information regarding spore concentration in the air. Hence, aerobiological monitoring should be conducted, and if possible extended with the construction of forecast models. Daily mean concentration of allergenic Ganoderma spp. spores in the atmosphere of Worcester was measured using 7-day volumetric spore sampler through five consecutive years. The relationships between the presence of spores in the air and the weather parameters were examined. Forecast models were constructed for Ganoderma spp. spores using advanced statistical techniques, i.e. multivariate regression trees and artificial neural networks. Dew point temperature along with maximum temperature was the most important factor influencing the presence of spores in the air of Worcester. Based on these two major factors and several others of lesser importance, thresholds for certain levels of fungal spore concentration, i.e. low (0-49 s m-3), moderate (50-99 s m-3), high (100-149 s m-3) and very high (150 < n s m-3), could be designated. Despite some deviation in results obtained by artificial neural networks, authors have achieved a forecasting model, which was accurate (correlation between observed and predicted values varied from r s = 0.57 to r s = 0.68).

  20. Evaluating Acupuncture Point and Nonacupuncture Point Stimulation with EEG: A High-Frequency Power Spectrum Analysis

    Directory of Open Access Journals (Sweden)

    Kwang-Ho Choi

    2016-01-01

    Full Text Available To identify physical and sensory responses to acupuncture point stimulation (APS, nonacupuncture point stimulation (NAPS and no stimulation (NS, changes in the high-frequency power spectrum before and after stimulation were evaluated with electroencephalography (EEG. A total of 37 healthy subjects received APS at the LI4 point, NAPS, or NS with their eyes closed. Background brain waves were measured before, during, and after stimulation using 8 channels. Changes in the power spectra of gamma waves and high beta waves before, during, and after stimulation were comparatively analyzed. After NAPS, absolute high beta power (AHBP, relative high beta power (RHBP, absolute gamma power (AGP, and relative gamma power (RGP tended to increase in all channels. But no consistent notable changes were found for APS and NS. NAPS is believed to cause temporary reactions to stress, tension, and sensory responses of the human body, while APS responds stably compared to stimulation of other parts of the body.

  1. Evaluation of Potential Influence of Lacking the Consideration of Aerosol Perturbations on NCEP GFS Precipitation Forecast

    Science.gov (United States)

    Jiang, Mengjiao; Feng, Jinqin; Sun, Ruiyu; Li, Zhanqing; Wan, Bingcheng; Cribb, Maureen

    2017-04-01

    Cloud-Aerosol-Precipitation-Interactions have been widely recognized as affecting precipitation very much in the water and energy cycles, however, are not considered in the operational NCEP GFS model. We evaluated the NCEP operational precipitation forecast from the aspect of lacking consideration of aerosol effects, using multiple datasets from ground-based and satellite observations and model reanalysis. CPC unified gauge-based precipitation analysis, and MERRA-2 aerosol reanalysis were used to evaluate the forecast in three countries in the year 2015. The phenomena of overestimation of light rain (47.84%) and underestimation of heavier rain (31.83%, 52.94%, and 65.74% for moderate rain, heavy rain, and very heavy rain, respectively) of the model are consistent with the scenario that no aerosol effects are considered. The standard deviation of forecast bias are significantly positive correlated with AOD with coefficient of 0.5602, 0.6522, and 0.5182 for Australia, US, and China, respectively. The ETS score in the U.S. decreases with AOD increasing. In addition, long-term forecast with a focus in Fujian, China were evaluated and analyzed using gauge-based observations of precipitation, visibility, water vapor, and convective available, and satellite datasets. The results show that model overestimates light rain and underestimates heavy rain. Long-term analysis indicated that there is a trend in heavy rain increase in summer, while a light rain decrease in other seasons. A decreasing trend of visibility is found while no obvious trend is found of water vapor or a little increase trend in summer CAPE. The results also show that more aerosols decrease cloud effective radii for liquid water path greater than 80 g/m2 situation. The increase of cloud top temperature with AOD for liquid clouds, and the decrease of that for warm mixed phase clouds, suggest that aerosols inhibit the development of shallow liquid clouds, and invigorate warm base mixed-phase clouds

  2. An evaluation of market penetration forecasting methodologies for new residential and commercial energy technologies

    Energy Technology Data Exchange (ETDEWEB)

    Raju, P.S.; Teotia, A.P.S.

    1985-05-01

    Forecasting market penetration is an essential step in the development and assessment of new technologies. This report reviews several methodologies that are available for market penetration forecasting. The primary objective of this report is to help entrepreneurs understand these methodologies and aid in the selection of one or more of them for application to a particular new technology. This report also illustrates the application of these methodologies, using examples of new technologies, such as the heat pump, drawn from the residential and commercial sector. The report concludes with a brief discussion of some considerations in selecting a forecasting methodology for a particular situation. It must be emphasized that the objective of this report is not to construct a specific market penetration model for new technologies but only to provide a comparative evaluation of methodologies that would be useful to an entrepreneur who is unfamiliar with the range of techniques available. The specific methodologies considered in this report are as follows: subjective estimation methods, market surveys, historical analogy models, time series models, econometric models, diffusion models, economic cost models, and discrete choice models. In addition to these individual methodologies, which range from the very simple to the very complex, two combination approaches are also briefly discussed: (1) the economic cost model combined with the diffusion model and (2) the discrete choice model combined with the diffusion model. This discussion of combination methodologies is not meant to be exhaustive. Rather, it is intended merely to show that many methodologies often can complement each other. A combination of two or more different approaches may be better than a single methodology alone.

  3. 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

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

    Science.gov (United States)

    Bell, Victoria A.; Davies, Helen N.; Kay, Alison L.; Brookshaw, Anca; Scaife, Adam A.

    2017-09-01

    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 % of the forecast

  5. Oil Points - Life Cycle Evaluations without the Data Problem

    DEFF Research Database (Denmark)

    Bey, Niki; Lenau, Torben Anker; Larsen, Michael Holm

    1999-01-01

    Environmental aspects of products in their whole life cycle are of increasing importance in industry [1]. Therefore, several methods and tools for environmental life cycle evaluation have been developed during the last years. Formal Life Cycle Assessment (LCA), the state-of-the-art in environmental...... indicator-based evaluation is dependent on the existence and availability of such indicators.In order to avoid this, the Oil Point Method (OPM) has been developed. Its application only requires limited resources while still providing a valuable evaluation. The OPM is based on primary energy considerations...

  6. Evaluation of the product ratio coherent model in forecasting mortality rates and life expectancy at births by States

    Science.gov (United States)

    Shair, Syazreen Niza; Yusof, Aida Yuzi; Asmuni, Nurin Haniah

    2017-05-01

    Coherent mortality forecasting models have recently received increasing attention particularly in their application to sub-populations. The advantage of coherent models over independent models is the ability to forecast a non-divergent mortality for two or more sub-populations. One of the coherent models was recently developed by [1] known as the product-ratio model. This model is an extension version of the functional independent model from [2]. The product-ratio model has been applied in a developed country, Australia [1] and has been extended in a developing nation, Malaysia [3]. While [3] accounted for coherency of mortality rates between gender and ethnic group, the coherency between states in Malaysia has never been explored. This paper will forecast the mortality rates of Malaysian sub-populations according to states using the product ratio coherent model and its independent version— the functional independent model. The forecast accuracies of two different models are evaluated using the out-of-sample error measurements— the mean absolute forecast error (MAFE) for age-specific death rates and the mean forecast error (MFE) for the life expectancy at birth. We employ Malaysian mortality time series data from 1991 to 2014, segregated by age, gender and states.

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

    Science.gov (United States)

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

    2017-11-01

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

  8. Noise Control for a Moving Evaluation Point Using Neural Networks

    Science.gov (United States)

    Maeda, Toshiki; Shiraishi, Toshihiko

    2016-09-01

    This paper describes the noise control for a moving evaluation point using neural networks by making the best use of its learning ability. Noise control is a technology which is effective on low-frequency noise. Based on the principle of superposition, a primary sound wave can be cancelled at an evaluation point by emitting a secondary opposite sound wave. To obtain good control performance, it is important to precisely identify the characteristics of all the sound paths. One of the most popular algorithms of noise control is filtered-x LMS algorithm. This algorithm can deliver a good result while all the sound paths do not change. However, the control system becomes uncontrollable while the evaluation point is moving. To solve the problem, the characteristics of all the paths are must be identified at all time. In this paper, we applied neural networks with the learning ability to the noise control system to follow the time-varying paths and verified its control performance by numerical simulations. Then, dropout technique for the networks is also applied. Dropout is a technique that prevent the network from overfitting and enables better control performance. By applying dropout for noise control, it prevents the system from diverging.

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

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2016-01-01

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

  10. Process-oriented statistical-dynamical evaluation of LM precipitation forecasts

    Directory of Open Access Journals (Sweden)

    A. Claußnitzer

    2008-04-01

    Full Text Available The objective of this study is the scale dependent evaluation of precipitation forecasts of the Lokal-Modell (LM from the German Weather Service in relation to dynamical and cloud parameters. For this purpose the newly designed Dynamic State Index (DSI is correlated with clouds and precipitation. The DSI quantitatively describes the deviation and relative distance from a stationary and adiabatic solution of the primitive equations. A case study and statistical analysis of clouds and precipitation demonstrates the availability of the DSI as a dynamical threshold parameter. This confirms the importance of imbalances of the atmospheric flow field, which dynamically induce the generation of rainfall.

  11. Accounting for the inaccuracies in demand forecasts and construction cost estimations in transport project evaluation

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Leleur, Steen

    2014-01-01

    For decades researchers have claimedthat particularly demand forecasts and construction cost estimations are assigned with/affected by a large degree of uncertainty. Massively, articles,research documents and reports agree that there exists a tendencytowards underestimating the costs...... in demand and cost estimations and hence the evaluation of transport infrastructure projects. Currently, research within this area is scarce and scattered with no commonagreement on how to embed and operationalise the huge amount of empiricaldata that exist within the frame of Optimism Bias. Therefore...... convertingdeterministic benefit-cost ratios (BCRs) into stochasticinterval results. A new data collection (2009–2013) forms the empirical basis for any risk simulation embeddedwithin the so-calledUP database (UNITE project database),revealing the inaccuracy of both construction costs and demandforecasts. Accordingly...

  12. Assessing DRAGON Measurements for Evaluation and Assimilation in the GEOS-5 Aerosol Forecasting System

    Science.gov (United States)

    da Silva, A.; Colarco, P. R.; Darmenov, A.; Holben, B. N.

    2013-12-01

    GEOS-5 is the latest version of the NASA Global Modeling and Assimilation Office (GMAO) earth system model. GEOS-5 contains components for atmospheric circulation and composition (including data assimilation), ocean circulation and biogeochemistry, and land surface processes. In addition to traditional meteorological parameters, GEOS-5 includes modules representing the atmospheric composition, most notably aerosols and tropospheric/stratospheric chemical constituents, taking explicit account of the impact of these constituents on the radiative processes of the atmosphere. The assimilation of Aerosol Optical Depth (AOD) in GEOS-5 involves very careful cloud screening and homogenization of the observing system by means of a Neural Net scheme that translates MODIS radiances into AERONET calibrated AOD. These measurements are further quality controlled using an adaptive buddy check scheme, and assimilated using the Local Displacement Ensemble (LDE) methodology. The near real-time GEOS-5 aerosol forecasting system runs at a nominal 25km horizontal resolution with 72 vertical layers (top at ~85km). GEOS-5 is driven by daily biomass burning emissions derived from MODIS fire radiative power retrievals. In this talk we will utilize aerosol measurements from the Distributed Regional Aerosol Gridded Observation Networks (DRAGON) to evaluate the temporal and spatial distribution of aerosols in GEOS-5. While NRT assimilation of MODIS optical depth observations constrains the GEOS-5 aerosol distributions during satellite overpasses, the diurnal cycle, mixing state and optical properties are internally determined by the model parameterizations and require careful validation. By combining DRAGON with other in-situ and remotely sensed measurements from the DISCOVER-AQ and SEAC4RS field campaigns we will present a comprehensive evaluation of the GEOS-5 aerosol state, and examine the impact of assimilating the DRAGON measurements on the quality of the GEOS-5 analysis and forecasts

  13. Consideration Points on Evaluation of Biomass Use from Lifecycle View

    Science.gov (United States)

    Yuyama, Yoshito; Yamaoka, Masaru; Nakamura, Masato; Shimizu, Natsuki

    Biomass use system is consisted of 1) production or generation, collection, transportation and storage of feedstock biomass, 2) conversion of the feedstock biomass to demand-oriented material and energy (renewal resources), 3) storage, transportation and use of the renewal resources, and 4) adequate disposal at above respective stage. This paper arranged the discussion points on evaluation methods of new biomass use scenarios in terms of lifecycle cost and lifecycle fossil energy consumption. An evaluation format was proposed. The evaluation clarifies the structure of cost and energy for a planned biomass use scenario. The results will provide an suitable project cycle management by cost saving and mitigation of global warming. The analysis from lifecycle view is important to ensure the sustainability of biomass use system.

  14. An evaluation of the Canadian global meteorological ensemble prediction system for short-term hydrological forecasting

    Directory of Open Access Journals (Sweden)

    F. Anctil

    2009-11-01

    Full Text Available Hydrological forecasting consists in the assessment of future streamflow. Current deterministic forecasts do not give any information concerning the uncertainty, which might be limiting in a decision-making process. Ensemble forecasts are expected to fill this gap.

    In July 2007, the Meteorological Service of Canada has improved its ensemble prediction system, which has been operational since 1998. It uses the GEM model to generate a 20-member ensemble on a 100 km grid, at mid-latitudes. This improved system is used for the first time for hydrological ensemble predictions. Five watersheds in Quebec (Canada are studied: Chaudière, Châteauguay, Du Nord, Kénogami and Du Lièvre. An interesting 17-day rainfall event has been selected in October 2007. Forecasts are produced in a 3 h time step for a 3-day forecast horizon. The deterministic forecast is also available and it is compared with the ensemble ones. In order to correct the bias of the ensemble, an updating procedure has been applied to the output data. Results showed that ensemble forecasts are more skilful than the deterministic ones, as measured by the Continuous Ranked Probability Score (CRPS, especially for 72 h forecasts. However, the hydrological ensemble forecasts are under dispersed: a situation that improves with the increasing length of the prediction horizons. We conjecture that this is due in part to the fact that uncertainty in the initial conditions of the hydrological model is not taken into account.

  15. Coupling meteorological and hydrological models to evaluate the uncertainty in runoff forecasting: the case study of Maggiore Lake basin

    Science.gov (United States)

    Ceppi, A.; Ravazzani, G.; Rabuffetti, D.; Mancini, M.

    2009-04-01

    observed data to run the control simulations were supplied by ARPA-Piemonte. The study is focused on Maggiore Lake basin, an alpine basin between North-West of Italy and Southern Switzerland; results and statistical testing of the re-analyses shown in this presentation, are subdivided for each of three smaller sub-basins: Toce, Ticino and Maggia, in order to demonstrate the research progress on coupling meteorological and hydrological models in particular orographic features. It is presented how the meteorological forecasts are efficient into hydrological forecasting system, how the ensemble predictions are powerful to evaluate the uncertainty of the QPF which affects the QDF and the whole hydro-meteorological alert system for a mountain catchment. Further, in order to control the quality of the hydrological predictions in the short and medium term, statistical methods are used to calculate how the skill scores can be applied for hydrological applications and how the ensemble forecasts can help the users for decision making in management situations. Two significant events are analysed in order to compare the behaviour of the model driven by different weather scenarios: one convective in June that has yielded a high peak flow and one light stratiform in November that has been studied for the snow melt temperature which has affected the liquid precipitation and therefore the forecasted runoff. It is shown how the entire rainfall, the liquid precipitation and the runoff change in function of an areal the sub-basin scale, in order to understand where the errors are more frequently encountered.

  16. Two Different Points of View through Artificial Intelligence and Vector Autoregressive Models for Ex Post and Ex Ante Forecasting

    Science.gov (United States)

    Aydin, Alev Dilek; Caliskan Cavdar, Seyma

    2015-01-01

    The ANN method has been applied by means of multilayered feedforward neural networks (MLFNs) by using different macroeconomic variables such as the exchange rate of USD/TRY, gold prices, and the Borsa Istanbul (BIST) 100 index based on monthly data over the period of January 2000 and September 2014 for Turkey. Vector autoregressive (VAR) method has also been applied with the same variables for the same period of time. In this study, different from other studies conducted up to the present, ENCOG machine learning framework has been used along with JAVA programming language in order to constitute the ANN. The training of network has been done by resilient propagation method. The ex post and ex ante estimates obtained by the ANN method have been compared with the results obtained by the econometric forecasting method of VAR. Strikingly, our findings based on the ANN method reveal that there is a possibility of financial distress or a financial crisis in Turkey starting from October 2017. The results which were obtained with the method of VAR also support the results of ANN method. Additionally, our results indicate that the ANN approach has more superior prediction performance than the VAR method. PMID:26550010

  17. The Effect of Hydrologic Model Calibration on Seasonal Streamflow Forecasts for the Western U.S.

    Science.gov (United States)

    Shi, X.; Wood, A. W.; Lettenmaier, D. P.

    2007-12-01

    Forecasts of seasonal streamflow, particularly for the spring and summer period which are dominated by snowmelt runoff, are central to the management of the water resources infrastructure of the western U.S. Operational approaches to seasonal streamflow forecasting, like the Ensemble Streamflow Prediction (ESP) method used by the U.S. National Weather Service, rely heavily on manpower and/or computationally intensive calibration of conceptual streamflow models. We suggest an alternative approach, in which a priori (e.g., based on regional information) model parameters are used for streamflow forecasting, and a post processing bias correction is applied using a percentile mapping approach which utilizes the past history of model errors associated with the uncalibrated model. We evaluate intensively the impact of calibration on ESP forecasts at eight forecast points carefully selected to span a range of basin sizes and hydroclimatic conditions across the western U.S. At each of these sites, we apply the ESP approach, and evaluate forecast errors for a range of forecast dates and lead times. We use both the root mean squared error (RMSE) and coefficient of prediction Cp (which essentially is a measure of the fraction of variance explained by the forecast) to evaluate the effects of model calibration on seasonal streamflow forecast accuracy. We find that while the bias correction approach captures most of the accuracy achievable by model calibration, for most forecast points, forecast dates, and lead times there remains a modest increase in forecast accuracy that can only be captured by model calibration.

  18. Evaluation of the wheel-point and step-point methods of veld ...

    African Journals Online (AJOL)

    The step-point method yielded results on percentage veld composition and on veld composition score which did not differ in precision or in absolute amount from those obtained using the wheel-point apparatus. Adoption of the step point method in preference to the wheel-point method saves in equipment and manpower, ...

  19. Forecasting the State of Health of Electric Vehicle Batteries to Evaluate the Viability of Car Sharing Practices

    Directory of Open Access Journals (Sweden)

    Ivana Semanjski

    2016-12-01

    Full Text Available Car-sharing practices are introducing electric vehicles (EVs into their fleet. However, the literature suggests that at this point shared EV systems are failing to reach satisfactory commercial viability. A potential reason for this is the effect of higher vehicle usage, which is characteristic of car sharing, and the implications on the battery’s state of health (SoH. In this paper, we forecast the SoH of two identical EVs being used in different car-sharing practices. For this purpose, we use real life transaction data from charging stations and different EV sensors. The results indicate that insight into users’ driving and charging behavior can provide a valuable point of reference for car-sharing system designers. In particular, the forecasting results show that the moment when an EV battery reaches its theoretical end of life can differ in as much as a quarter of the time when vehicles are shared under different conditions.

  20. Evaluation for Long Term PM10 Concentration Forecasting using Multi Linear Regression (MLR and Principal Component Regression (PCR Models

    Directory of Open Access Journals (Sweden)

    Samsuri Abdullah

    2016-07-01

    Full Text Available Air pollution in Peninsular Malaysia is dominated by particulate matter which is demonstrated by having the highest Air Pollution Index (API value compared to the other pollutants at most part of the country. Particulate Matter (PM10 forecasting models development is crucial because it allows the authority and citizens of a community to take necessary actions to limit their exposure to harmful levels of particulates pollution and implement protection measures to significantly improve air quality on designated locations. This study aims in improving the ability of MLR using PCs inputs for PM10 concentrations forecasting. Daily observations for PM10 in Kuala Terengganu, Malaysia from January 2003 till December 2011 were utilized to forecast PM10 concentration levels. MLR and PCR (using PCs input models were developed and the performance was evaluated using RMSE, NAE and IA. Results revealed that PCR performed better than MLR due to the implementation of PCA which reduce intricacy and eliminate data multi-collinearity.

  1. Improving Precipitation Forecast for Canadian Catchments

    Science.gov (United States)

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

    2016-12-01

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

  2. Forecasting the State of Health of Electric Vehicle Batteries to Evaluate the Viability of Car Sharing Practices

    OpenAIRE

    Ivana Semanjski; Sidharta Gautama

    2016-01-01

    Car sharing practices are introducing electric vehicles into their fleet. However, literature suggests that at this point shared electric vehicle systems are failing to reach satisfactory commercial viability. Potential reason for this is the effect of higher vehicle usage which is characteristic for car sharing, and the implication on the battery state of health. In this paper, we forecast state of health for two identical electric vehicles shared by two different car sharing practices. For ...

  3. Performance evaluation of ionospheric time delay forecasting models using GPS observations at a low-latitude station

    Science.gov (United States)

    Sivavaraprasad, G.; Venkata Ratnam, D.

    2017-07-01

    Ionospheric delay is one of the major atmospheric effects on the performance of satellite-based radio navigation systems. It limits the accuracy and availability of Global Positioning System (GPS) measurements, related to critical societal and safety applications. The temporal and spatial gradients of ionospheric total electron content (TEC) are driven by several unknown priori geophysical conditions and solar-terrestrial phenomena. Thereby, the prediction of ionospheric delay is challenging especially over Indian sub-continent. Therefore, an appropriate short/long-term ionospheric delay forecasting model is necessary. Hence, the intent of this paper is to forecast ionospheric delays by considering day to day, monthly and seasonal ionospheric TEC variations. GPS-TEC data (January 2013-December 2013) is extracted from a multi frequency GPS receiver established at K L University, Vaddeswaram, Guntur station (geographic: 16.37°N, 80.37°E; geomagnetic: 7.44°N, 153.75°E), India. An evaluation, in terms of forecasting capabilities, of three ionospheric time delay models - an Auto Regressive Moving Average (ARMA) model, Auto Regressive Integrated Moving Average (ARIMA) model, and a Holt-Winter's model is presented. The performances of these models are evaluated through error measurement analysis during both geomagnetic quiet and disturbed days. It is found that, ARMA model is effectively forecasting the ionospheric delay with an accuracy of 82-94%, which is 10% more superior to ARIMA and Holt-Winter's models. Moreover, the modeled VTEC derived from International Reference Ionosphere, IRI (IRI-2012) model and new global TEC model, Neustrelitz TEC Model (NTCM-GL) have compared with forecasted VTEC values of ARMA, ARIMA and Holt-Winter's models during geomagnetic quiet days. The forecast results are indicating that ARMA model would be useful to set up an early warning system for ionospheric disturbances at low latitude regions.

  4. Trade Balances of the Asian Countries under Crisis: Forecast and Evaluation

    Directory of Open Access Journals (Sweden)

    Ingyo Cheong

    1998-06-01

    Full Text Available To overcome the financial crisis, we need to do some reform, such as to change the governmental and non-governmental structure, make sure the policy to be transparent, and remove restrictions, etc. All these measures can restore the confidence of foreign investors towards Korea. But to make balance of the trade surplus and keep foreign exchange reserve at a reasonable level, ensure foreign exchange and the security of financial department is one of the most urgent topics. Since the deep relationship of economy among countries in North-East Asia, financial crisis is not only the problem in Korea. It is already expended to the whole North-East Asia. This thesis shows the idea that we can forecast surplus in the trade balance scale, enlarge the trade balance of South Korea and activate export. It also shows that instead of the increase of export, the surplus is caused by the decrease of import. At this point of view, the number of surplus is not true. If the investment keeps decreasing like this, the foundation of Korean Economy will collapse.

  5. Evaluating the Contribution of NASA Remotely-Sensed Data Sets on a Convection-Allowing Forecast Model

    Science.gov (United States)

    Zavodsky, Bradley T.; Case, Jonathan L.; Molthan, Andrew L.

    2012-01-01

    The Short-term Prediction Research and Transition (SPoRT) Center is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service forecast offices. SPoRT provides real-time NASA products and capabilities to help its partners address specific operational forecast challenges. One challenge that forecasters face is using guidance from local and regional deterministic numerical models configured at convection-allowing resolution to help assess a variety of mesoscale/convective-scale phenomena such as sea-breezes, local wind circulations, and mesoscale convective weather potential on a given day. While guidance from convection-allowing models has proven valuable in many circumstances, the potential exists for model improvements by incorporating more representative land-water surface datasets, and by assimilating retrieved temperature and moisture profiles from hyper-spectral sounders. In order to help increase the accuracy of deterministic convection-allowing models, SPoRT produces real-time, 4-km CONUS forecasts using a configuration of the Weather Research and Forecasting (WRF) model (hereafter SPoRT-WRF) that includes unique NASA products and capabilities including 4-km resolution soil initialization data from the Land Information System (LIS), 2-km resolution SPoRT SST composites over oceans and large water bodies, high-resolution real-time Green Vegetation Fraction (GVF) composites derived from the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and retrieved temperature and moisture profiles from the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI). NCAR's Model Evaluation Tools (MET) verification package is used to generate statistics of model performance compared to in situ observations and rainfall analyses for three months during the summer of 2012 (June-August). Detailed analyses of specific severe weather outbreaks during the summer

  6. Multi-model data fusion for river flow forecasting: an evaluation of six alternative methods based on two contrasting catchments

    Directory of Open Access Journals (Sweden)

    R. J. Abrahart

    2002-01-01

    Full Text Available This paper evaluates six published data fusion strategies for hydrological forecasting based on two contrasting catchments: the River Ouse and the Upper River Wye. The input level and discharge estimates for each river comprised a mixed set of single model forecasts. Data fusion was performed using: arithmetic-averaging, a probabilistic method in which the best model from the last time step is used to generate the current forecast, two different neural network operations and two different soft computing methodologies. The results from this investigation are compared and contrasted using statistical and graphical evaluation. Each location demonstrated several options and potential advantages for using data fusion tools to construct superior estimates of hydrological forecast. Fusion operations were better in overall terms in comparison to their individual modelling counterparts and two clear winners emerged. Indeed, the six different mechanisms on test revealed unequal aptitudes for fixing different categories of problematic catchment behaviour and, in such cases, the best method(s were a good deal better than their closest rival(s. Neural network fusion of differenced data provided the best solution for a stable regime (with neural network fusion of original data being somewhat similar — whereas a fuzzified probabilistic mechanism produced a superior output in a more volatile environment. The need for a data fusion research agenda within the hydrological sciences is discussed and some initial suggestions are presented. Keywords: data fusion, fuzzy logic, neural network, hydrological modelling

  7. Forecasting Temporal and Spatial Climatological Influence for Land Suitability Evaluation in Bentota Sri Lanka

    Directory of Open Access Journals (Sweden)

    Gayani Ranasinghe

    2017-01-01

    Full Text Available Climate change has raised much concern regarding its impacts on future land use planning, varying by region, time, and socio-economic development path. The principle purpose of land suitability evaluation is to predict the potential and limitation of the land for crop production and other land uses. This study was carried out to predict the temperature and rainfall trends as one of the major factor for evaluating land suitability. Climatic data such as monthly mean temperature, total monthly rainfall, maximum daily rainfall and total annual rainfall during last 30 years of all weather stations located in Bentota River basin was collected and analyzed applying time series analysis, correlation analysis and Manna Kendall trend test methods. Spatial distribution of forecast rainfall values was illustrated applying Arc GIS software. The findings revealed that monthly mean temperature and maximum daily rainfall had a general increasing trend whereas, total monthly rainfall and total annual rainfall showed a general decreasing trend in  Bentota area. It was indicated relatively high rainfall situations during May and October while low rainfall situations during January and February by occurring flood situation in once per five year. During Yala season the area will be received comparatively more rainfall (331mm than Maha season (300mm in future. Community and the farmers in this area can be aware about the anticipated spatial distribution of total monthly rainfall during two major seasons and flood occurrence periods. Decision makers should evaluate land suitability of Bentota area by considering above climatological influences and its spatial distribution pattern that identified as major outcome of this research. The approach and the methodology adopted in this study will be useful for other researchers, agriculturalist and planners to identify the future climatological influences and its spatial distribution pattern for land suitability evaluations

  8. Development of speed models for improving travel forecasting and highway performance evaluation : [technical summary].

    Science.gov (United States)

    2013-12-01

    Travel forecasting models predict travel demand based on the present transportation system and its use. Transportation modelers must develop, validate, and calibrate models to ensure that predicted travel demand is as close to reality as possible. Mo...

  9. Evaluation of energy fluxes in the NCEP climate forecast system version 2.0 (CFSv2)

    Science.gov (United States)

    Rai, Archana; Saha, Subodh Kumar

    2018-01-01

    The energy fluxes at the surface and top of the atmosphere (TOA) from a long free run by the NCEP climate forecast system version 2.0 (CFSv2) are validated against several observation and reanalysis datasets. This study focuses on the annual mean energy fluxes and tries to link it with the systematic cold biases in the 2 m air temperature, particularly over the land regions. The imbalance in the long term mean global averaged energy fluxes are also evaluated. The global averaged imbalance at the surface and at the TOA is found to be 0.37 and 6.43 Wm-2, respectively. It is shown that CFSv2 overestimates the land surface albedo, particularly over the snow region, which in turn contributes to the cold biases in 2 m air temperature. On the other hand, surface albedo is highly underestimated over the coastal region around Antarctica and that may have contributed to the warm bias over that oceanic region. This study highlights the need for improvements in the parameterization of snow/sea-ice albedo scheme for a realistic simulation of surface temperature and that may have implications on the global energy imbalance in the model.

  10. Probabilistic Forecasts of Solar Irradiance by Stochastic Differential Equations

    DEFF Research Database (Denmark)

    Iversen, Jan Emil Banning; Morales González, Juan Miguel; Møller, Jan Kloppenborg

    2014-01-01

    Probabilistic forecasts of renewable energy production provide users with valuable information about the uncertainty associated with the expected generation. Current state-of-the-art forecasts for solar irradiance have focused on producing reliable point forecasts. The additional information...... included in probabilistic forecasts may be paramount for decision makers to efficiently make use of this uncertain and variable generation. In this paper, a stochastic differential equation framework for modeling the uncertainty associated with the solar irradiance point forecast is proposed. This modeling...... approach allows for characterizing both the interdependence structure of prediction errors of short-term solar irradiance and their predictive distribution. Three different stochastic differential equation models are first fitted to a training data set and subsequently evaluated on a one-year test set...

  11. Evaluating the Impact of Atmospheric Infrared Sounder (AIRS) Data On Convective Forecasts

    Science.gov (United States)

    Kozlowski, Danielle; Zavodsky, Bradley

    2011-01-01

    The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service (NWS) offices. SPoRT provides real-time NASA products and capabilities to its partners to address specific operational forecast challenges. The mission of SPoRT is to transition observations and research capabilities into operations to help improve short-term weather forecasts on a regional scale. Two areas of focus are data assimilation and modeling, which can to help accomplish SPoRT's programmatic goals of transitioning NASA data to operational users. Forecasting convective weather is one challenge that faces operational forecasters. Current numerical weather prediction (NWP) models that operational forecasters use struggle to properly forecast location, timing, intensity and/or mode of convection. Given the proper atmospheric conditions, convection can lead to severe weather. SPoRT's partners in the National Oceanic and Atmospheric Administration (NOAA) have a mission to protect the life and property of American citizens. This mission has been tested as recently as this 2011 severe weather season, which has seen more than 300 fatalities and injuries and total damages exceeding $10 billion. In fact, during the three day period from 25-27 April, 1,265 storms reports (362 tornado reports) were collected making this three day period one of most active in American history. To address the forecast challenge of convective weather, SPoRT produces a real-time NWP model called the SPoRT Weather Research and Forecasting (SPoRT-WRF), which incorporates unique NASA data sets. One of the NASA assets used in this unique model configuration is retrieved profiles from the Atmospheric Infrared Sounder (AIRS).The goal of this project is to determine the impact that these AIRS profiles have on the SPoRT-WRF forecasts by comparing to a current operational model and a control SPoRT-WRF model

  12. How to evaluate an Early Warning System? Towards a United Statistical Framework for Assessing Financial Crises Forecasting Methods

    OpenAIRE

    Candelon, B.; Dumitrescu, E-I.; Hurlin, C.

    2010-01-01

    This paper proposes a new statistical framework originating from the traditional credit-scoring literature, to evaluate currency crises Early Warning Systems (EWS). Based on an assessment of the predictive power of panel logit and Markov frameworks, the panel logit model is outperforming the Markov switching specitcations. Furthermore, the introduction of forward-looking variables clearly improves the forecasting properties of the EWS. This improvement confirms the adequacy of the second gene...

  13. The strategy of professional forecasting

    DEFF Research Database (Denmark)

    Ottaviani, Marco; Sørensen, Peter Norman

    2006-01-01

    We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters endeavor to convince the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts and the ......We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters endeavor to convince the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts...

  14. Evaluating the performance of real-time streamflow forecasting using multi-satellite precipitation products in the Upper Zambezi, Africa

    Science.gov (United States)

    Demaria, E. M.; Valdes, J. B.; Wi, S.; Serrat-Capdevila, A.; Valdés-Pineda, R.; Durcik, M.

    2016-12-01

    In under-instrumented basins around the world, accurate and timely forecasts of river streamflows have the potential of assisting water and natural resource managers in their management decisions. The Upper Zambezi river basin is the largest basin in southern Africa and its water resources are critical to sustainable economic growth and poverty reduction in eight riparian countries. We present a real-time streamflow forecast for the basin using a multi-model-multi-satellite approach that allows accounting for model and input uncertainties. Three distributed hydrologic models with different levels of complexity: VIC, HYMOD_DS, and HBV_DS are setup at a daily time step and a 0.25 degree spatial resolution for the basin. The hydrologic models are calibrated against daily observed streamflows at the Katima-Mulilo station using a Genetic Algorithm. Three real-time satellite products: Climate Prediction Center's morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Tropical Rainfall Measuring Mission (TRMM-3B42RT) are bias-corrected with daily CHIRPS estimates. Uncertainty bounds for predicted flows are estimated with the Inverse Variance Weighting method. Because concentration times in the basin range from a few days to more than a week, we include the use of precipitation forecasts from the Global Forecasting System (GFS) to predict daily streamflows in the basin with a 10-days lead time. The skill of GFS-predicted streamflows is evaluated and the usefulness of the forecasts for short term water allocations is presented.

  15. Application of the NASA A-Train to Evaluate Clouds Simulated by the Weather Research and Forecast Model

    Science.gov (United States)

    Molthan, Andrew L.; Jedlovec, Gary J.; Lapenta, William M.

    2008-01-01

    The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.

  16. Evaluation of NMME temperature and precipitation bias and forecast skill for South Asia

    Science.gov (United States)

    Cash, Benjamin A.; Manganello, Julia V.; Kinter, James L.

    2017-08-01

    Systematic error and forecast skill for temperature and precipitation in two regions of Southern Asia are investigated using hindcasts initialized May 1 from the North American Multi-Model Ensemble. We focus on two contiguous but geographically and dynamically diverse regions: the Extended Indian Monsoon Rainfall (70-100E, 10-30 N) and the nearby mountainous area of Pakistan and Afghanistan (60-75E, 23-39 N). Forecast skill is assessed using the Sign test framework, a rigorous statistical method that can be applied to non-Gaussian variables such as precipitation and to different ensemble sizes without introducing bias. We find that models show significant systematic error in both precipitation and temperature for both regions. The multi-model ensemble mean (MMEM) consistently yields the lowest systematic error and the highest forecast skill for both regions and variables. However, we also find that the MMEM consistently provides a statistically significant increase in skill over climatology only in the first month of the forecast. While the MMEM tends to provide higher overall skill than climatology later in the forecast, the differences are not significant at the 95% level. We also find that MMEMs constructed with a relatively small number of ensemble members per model can equal or outperform MMEMs constructed with more members in skill. This suggests some ensemble members either provide no contribution to overall skill or even detract from it.

  17. Evaluation of Crop to Crop Water Demand Forecasting: Tomatoes and Bell Peppers Grown in a Commercial Greenhouse

    Directory of Open Access Journals (Sweden)

    Dean C. J. Rice

    2017-12-01

    Full Text Available Forecasting crop water demand is a critical part of any greenhouse’s day-to-day operations. This study focuses on a region located in Essex County, Ontario Canada where water demand is dominated by commercial greenhouse operations (78% of capacity. Development of complex and elaborate forecasting methods such as artificial neural networks (ANN can be costly to develop and implement, especially with the limited resources available to greenhouses. This study proposes simplified forecasting methods that would be used in conjunction with a more complex base model architecture. These simplified methods use one crop water usage as an indicator of another’s, and is titled crop-to-crop forecasting (C2C. In this study, tomatoes and peppers were evaluated, and three C2C models were developed along with an ANN base model to provide a basis for evaluation. The models were created using a dataset containing hourly watering data along with climatic and temporal data for the period between June 2015 and August 2016. The three C2C architectures used were linear regression (LR, quotient method (QM, and feed-forward neural network (FFNN, compared with the (ANN model, which is a feed-forward neural network with extra inputs (FFNN-EI. Each model was evaluated using the root mean squared error (RMSE and the normalized root mean squared error (NRMSE. The results show that all C2C methods have higher RMSE and NRMSE than that of the base model, with an average RMSE increase of 12% for peppers and 29% for tomatoes.

  18. Evaluation of Factors Affecting Freezing Point of Milk

    OpenAIRE

    Jelena Zagorska; Inga Ciprovica

    2013-01-01

    The freezing point of milk is in important indicator of the milk quality. The freezing point of milk is determined primarily to prove milk adulteration with water and to determine the amount of water in it. Chemical composition and properties of milk, thermal treatment and presence of any substance can influence freezing point of product. There are different substances, which can be added to milk with main purpose to prolong shelf-life of raw milk. There are detergent, pr...

  19. The Variance-covariance Method using IOWGA Operator for Tourism Forecast Combination

    Directory of Open Access Journals (Sweden)

    Liangping Wu

    2014-08-01

    Full Text Available Three combination methods commonly used in tourism forecasting are the simple average method, the variance-covariance method and the discounted MSFE method. These methods assign the different weights that can not change at each time point to each individual forecasting model. In this study, we introduce the IOWGA operator combination method which can overcome the defect of previous three combination methods into tourism forecasting. Moreover, we further investigate the performance of the four combination methods through the theoretical evaluation and the forecasting evaluation. The results of the theoretical evaluation show that the IOWGA operator combination method obtains extremely well performance and outperforms the other forecast combination methods. Furthermore, the IOWGA operator combination method can be of well forecast performance and performs almost the same to the variance-covariance combination method for the forecasting evaluation. The IOWGA operator combination method mainly reflects the maximization of improving forecasting accuracy and the variance-covariance combination method mainly reflects the decrease of the forecast error. For future research, it may be worthwhile introducing and examining other new combination methods that may improve forecasting accuracy or employing other techniques to control the time for updating the weights in combined forecasts.

  20. The Use of the Data Assimilation Research Testbed for Initializing and Evaluating IPCC Decadal Forecasts

    Science.gov (United States)

    Raeder, K.; Anderson, J. L.; Lauritzen, P. H.; Hoar, T. J.; Collins, N.

    2010-12-01

    DART (www.image.ucar.edu/DAReS/DART) is a general purpose, freely available, ensemble Kalman filter, data assimilation system, which is being used to generate state-of-the-art, partially coupled, ocean-atmosphere re-analyses in support of the decadal predictions planned for the next IPCC report. The resulting gridded product is directly comparable to the state variables output by POP and CAM (oceanic and atmospheric components of NCAR's Community Earth System Model climate model) because those are the assimilating models. Other models could also benefit from comparison against these reanalyses, since the ocean analyses are at the leading edge of ocean state estimation, and the atmospheric analyses are competitive with operational centers'. Such comparisons can reveal model biases and predictability characteristics, and do so in a quantitative way, since the ensemble nature of the analyses provides an objective estimate of the analysis error. The analyses will also be used as initial conditions for the decadal forecasts because they are the most realistic available. The generation of such analyses has revealed errors in model formulation for several versions of the finite volume core CAM, which has led to model improvements in each case. New models can be incorporated into DART in a matter of weeks, allowing them to be compared directly against available observations. The observations currently used in the assimilations include, for the ocean; temperature and salinity from the World Ocean Database (floats, drifters, moorings, autonomous pinipeds, and others), and for the atmosphere; temperature and winds from radiosondes, satellite drift winds, ACARS and aircraft. Observations of ocean currents and atmospheric moisture and pressure are also available. Global Positioning System profiles of atmospheric temperature and moisture are available for recent years. All that is required to add new observations to the suite is the forward operator, which generates an estimate

  1. Toward Seasonal Forecasting of Global Droughts: Evaluation over USA and Africa

    Science.gov (United States)

    Wood, Eric; Yuan, Xing; Roundy, Joshua; Sheffield, Justin; Pan, Ming

    2013-04-01

    Extreme hydrologic events in the form of droughts are significant sources of social and economic damage. In the United States according to the National Climatic Data Center, the losses from drought exceed US210 billion during 1980-2011, and account for about 24% of all losses from major weather disasters. Internationally, especially for the developing world, drought has had devastating impacts on local populations through food insecurity and famine. Providing reliable drought forecasts with sufficient early warning will help the governments to move from the management of drought crises to the management of drought risk. After working on drought monitoring and forecasting over the USA for over 10 years, the Princeton land surface hydrology group is now developing a global drought monitoring and forecasting system using a dynamical seasonal climate-hydrologic LSM-model (CHM) approach. Currently there is an active debate on the merits of the CHM-based seasonal hydrologic forecasts as compared to Ensemble Streamflow Prediction (ESP). We use NCEP's operational forecast system, the Climate Forecast System version 2 (CFSv2) and its previous version CFSv1, to investigate the value of seasonal climate model forecasts by conducting a set of 27-year seasonal hydrologic hindcasts over the USA. Through Bayesian downscaling, climate models have higher squared correlation (R2) and smaller error than ESP for monthly precipitation averaged over major river basins across the USA, and the forecasts conditional on ENSO show further improvements (out to four months) over river basins in the southern USA. All three approaches have plausible predictions of soil moisture drought frequency over central USA out to six months because of strong soil moisture memory, and seasonal climate models provide better results over central and eastern USA. The R2 of drought extent is higher for arid basins and for the forecasts initiated during dry seasons, but significant improvements from CFSv2 occur

  2. Stochastic rainfall-runoff forecasting: parameter estimation, multi-step prediction, and evaluation of overflow risk

    DEFF Research Database (Denmark)

    Löwe, Roland; Mikkelsen, Peter Steen; Madsen, Henrik

    2014-01-01

    Probabilistic runoff forecasts generated by stochastic greybox models can be notably useful for the improvement of the decision-making process in real-time control setups for urban drainage systems because the prediction risk relationships in these systems are often highly nonlinear. To date...

  3. Demand Forecasting: An Evaluation of DODs Accuracy Metric and Navys Procedures

    Science.gov (United States)

    2016-06-01

    United States Navy Wagner Correia de Souza, Captain Lieutenant, Brazilian Navy Submitted in partial fulfillment of the requirements for the...39  1.  Alternative Metric Selection .......................................................40  a.  Further Discussion on...Forecast Method ...................................................82  Figure 24.  Average MASE Results in the Selected Data

  4. [Hygienic forecasting and toxicologic evaluation of potential danger caused by new sulphenamide vulcanization accelerators].

    Science.gov (United States)

    Latyshevskaia, N I; Novikova, O N; Iudina, E V; Skakovskaia, M A

    2005-01-01

    The article covers forecasting work conditions in oncoming production of sulphenamides T and DC--vulcanization accelerators, specifies leading occupational hazards, justifies values of MAC for sulphenamide T and approximate safe levels of action for sulphenamide DC in air of workplace.

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

    Directory of Open Access Journals (Sweden)

    Katarina Bačić

    2006-12-01

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

  6. The Ethical Tipping Points of Evaluators in Conflict Zones

    Science.gov (United States)

    Duggan, Colleen; Bush, Kenneth

    2014-01-01

    What is different about the conduct of evaluations in conflict zones compared to nonconflict zones--and how do these differences affect (if at all) the ethical calculations and behavior of evaluators? When are ethical issues too risky, or too uncertain, for evaluators to accept--or to continue--an evaluation? These are the core questions guiding…

  7. Initial evaluations of a Gulf of Mexico/Caribbean ocean forecast system in the context of the Deepwater Horizon disaster

    Science.gov (United States)

    Zaron, Edward D.; Fitzpatrick, Patrick J.; Cross, Scott L.; Harding, John M.; Bub, Frank L.; Wiggert, Jerry D.; Ko, Dong S.; Lau, Yee; Woodard, Katharine; Mooers, Christopher N. K.

    2015-12-01

    In response to the Deepwater Horizon (DwH) oil spill event in 2010, the Naval Oceanographic Office deployed a nowcast-forecast system covering the Gulf of Mexico and adjacent Caribbean Sea that was designated Americas Seas, or AMSEAS, which is documented in this manuscript. The DwH disaster provided a challenge to the application of available ocean-forecast capabilities, and also generated a historically large observational dataset. AMSEAS was evaluated by four complementary efforts, each with somewhat different aims and approaches: a university research consortium within an Integrated Ocean Observing System (IOOS) testbed; a petroleum industry consortium, the Gulf of Mexico 3-D Operational Ocean Forecast System Pilot Prediction Project (GOMEX-PPP); a British Petroleum (BP) funded project at the Northern Gulf Institute in response to the oil spill; and the Navy itself. Validation metrics are presented in these different projects for water temperature and salinity profiles, sea surface wind, sea surface temperature, sea surface height, and volume transport, for different forecast time scales. The validation found certain geographic and time biases/errors, and small but systematic improvements relative to earlier regional and global modeling efforts. On the basis of these positive AMSEAS validation studies, an oil spill transport simulation was conducted using archived AMSEAS nowcasts to examine transport into the estuaries east of the Mississippi River. This effort captured the influences of Hurricane Alex and a non-tropical cyclone off the Louisiana coast, both of which pushed oil into the western Mississippi Sound, illustrating the importance of the atmospheric influence on oil spills such as DwH.

  8. Evaluation of fire weather forecasts using PM2.5 sensitivity analysis

    Science.gov (United States)

    Balachandran, Sivaraman; Baumann, Karsten; Pachon, Jorge E.; Mulholland, James A.; Russell, Armistead G.

    2017-01-01

    Fire weather forecasts are used by land and wildlife managers to determine when meteorological and fuel conditions are suitable to conduct prescribed burning. In this work, we investigate the sensitivity of ambient PM2.5 to various fire and meteorological variables in a spatial setting that is typical for the southeastern US, where prescribed fires are the single largest source of fine particulate matter. We use the method of principle components regression to estimate sensitivity of PM2.5, measured at a monitoring site in Jacksonville, NC (JVL), to fire data and observed and forecast meteorological variables. Fire data were gathered from prescribed fire activity used for ecological management at Marine Corps Base Camp Lejeune, extending 10-50 km south from the PM2.5 monitor. Principal components analysis (PCA) was run on 10 data sets that included acres of prescribed burning activity (PB) along with meteorological forecast data alone or in combination with observations. For each data set, observed PM2.5 (unitless) was regressed against PCA scores from the first seven principal components (explaining at least 80% of total variance). PM2.5 showed significant sensitivity to PB: 3.6 ± 2.2 μg m-3 per 1000 acres burned at the investigated distance scale of ∼10-50 km. Applying this sensitivity to the available activity data revealed a prescribed burning source contribution to measured PM2.5 of up to 25% on a given day. PM2.5 showed a positive sensitivity to relative humidity and temperature, and was also sensitive to wind direction, indicating the capture of more regional aerosol processing and transport effects. As expected, PM2.5 had a negative sensitivity to dispersive variables but only showed a statistically significant negative sensitivity to ventilation rate, highlighting the importance of this parameter to fire managers. A positive sensitivity to forecast precipitation was found, consistent with the practice of conducting prescribed burning on days when rain

  9. Forecasting Skill

    Science.gov (United States)

    1981-01-01

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

  10. Evaluation of Critical Control Points (CCPS) in the Production of ...

    African Journals Online (AJOL)

    Hazard analysis and critical control point (HACCP) was carried out during the production of African locust bean seeds condiment (Daddawa) in a location that specialized in it's manufacturing namely Kwanar – yandaddawa (Dawakin – Tofa Local Government Area) Kano State, Nigeria. The analyses consisted of ...

  11. Evaluating Multisystemic Efforts to Impact Disproportionality through Key Decision Points

    Science.gov (United States)

    Derezotes, Dennette; Richardson, Brad; King, Connie Bear; Kleinschmit-Rembert, Julia; Pratt, Betty

    2008-01-01

    Working in four communities, Casey Foundation/Center for the Study of Social Policy (CSSP) Alliance on Racial Equity (the Alliance) have developed a Racial Equity Scorecard for measuring disproportionality at key decision points for use in impacting disproportionality in the child welfare system. The four communities include King County,…

  12. Legibility Evaluation Using Point-of-regard Measurement

    Science.gov (United States)

    Saito, Daisuke; Saito, Keiichi; Saito, Masao

    Web site visibility has become important because of the rapid dissemination of World Wide Web, and combinations of foreground and background colors are crucial in providing high visibility. In our previous studies, the visibilities of several web-safe color combinations were examined using a psychological method. In those studies, simple stimuli were used because of experimental restriction. In this paper, legibility of sentences on web sites was examined using a psychophisiological method, point-of-regard measurement, to obtain other practical data. Ten people with normal color sensations ranging from ages 21 to 29 were recruited. The number of characters per line in each page was arranged in the same number, and the four representative achromatic web-safe colors, that is, #000000, #666666, #999999 and #CCCCCC, were examined. The reading time per character and the gaze time per line were obtained from point-of-regard measurement, and the normalized with the reading time and the gaze time of the three colors were calculated and compared. As the results, it was shown that the time of reading and gaze become long at the same ratio when the contrast decreases by point-of-regard measurement. Therefore, it was indicated that the legibility of color combinations could be estimated by point-of-regard measurement.

  13. Evaluation of the Seat Index Point Tool for Military Seats

    Science.gov (United States)

    2014-12-01

    in the seats used in the Seated Soldier Study (Figure 20) and in a range of other ! 23! military vehicle seats (Figure 21). In each case, a FARO Arm...reproducibility. Figure 19. Installing SIPT and J826 in a military seat. The FARO Arm used to record SIP and H- point locations is shown

  14. MOORE´S LAW EVALUATION AND PROPOSAL OF AN ALTERNATIVE FORECASTING MODEL BASED ON TREND EXTRAPOLATION

    Directory of Open Access Journals (Sweden)

    Marcelo D'Emidio

    2010-06-01

    Full Text Available This study´s core objective is to validate whether the model proposed by Moore (1975 - also known as Moore’s Law – adequately describes the technological evolution of microprocessors. It further poses to verify whether this model is a feasible predictive tool and, finally, present an alternative model. To this extent, the forecasting technique method, based on historical data projections, will be applied. Statistical tests employed presented strong indications that the method proposed by Moore (1975 adequately described the evolution of processor component numbers during the 70s, 80s and 90s. As to the 2000s, however, the same cannot be affirmed and consequently the present study encountered grounding for the need to adapt the model to enable its application as a predictive tool.Key-words: Moore’s Law. Forecast. Technological evolution.  

  15. Design and evaluation of pointing devices; Gestaltung und Evaluation von koordinatengebenden Interaktionsgeraeten

    Energy Technology Data Exchange (ETDEWEB)

    Krauss, L.; Zuehlke, D. [Kaiserslautern Univ. (Germany)

    2002-07-01

    Pointing devices e.g. the computer mouse are gaining considerable importance in modern human-machine-systems as a major part of the interaction interface between human beings and machines. During the dialogues with window-based operating systems the human being - the user - moves the cursor to a certain position on the screen by means of pointing devices. Microsoft products like WINDOWS have asserted themselves in the meantime in office applications and are currently conquering the market of industrial control systems as well. In office applications the mouse has become established as the most important pointing device for interaction. However, an 'office mouse' is not really suitable in a manufacturing environment. Only a few investigations exist evaluating alternatives to the mouse, which are suitable for industrial applications. At the Center of Human-Machine-Interaction (ZMMI) of the Institute of Production Automation (pak) at the University of Kaiserslautern a comparative investigation was carried out for alternative pointing devices like mouse, mousepad, mousebutton, mousestick, trackball, joystick, touchscreen, digitizing tablet and keyboard to determine their industrial suitability. This paper presents the methods of investigation and the most important results. The known Fitts' law model is mainly used in the field of HCl for office applications in order to evaluate interaction devices. This paper presents the new method DEVICE and is applied in the field of HMI for the evaluation of pointing devices. Tests with DEVICE and Fitts' method were conducted with machine operators under industrial environments to determine the suitability of thirty different pointing devices. The comparison between DEVICE and Fitts' law model shows that the results of certain partial tests correlate with each other. DEVICE can be used as substitute for Fitts' law model and offers additional parameters such as e.g. error rates and pointing deviation

  16. Learning from the Past - Evaluating Forecasts for Canadian Oil Sands Production with Data

    OpenAIRE

    Hehl, Friedrich

    2013-01-01

    Crude oil plays an important role for the global energy system. As there is ample evidence that conventional oil production will have peaked by 2020, unconventional oil has attained a stronger focus. In particular, oil derived from bitumen from Canadian oilsands has been proposed as a possible remedy to global oil depletion. This study aims to test the hypothesis that forecasts on the Canadian oil sands published between about 2000 and 2010 have been overestimating production significantly. A ...

  17. Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species

    KAUST Repository

    Fernandes, José Antonio

    2015-01-01

    The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.

  18. Wind Farm Power Forecasting

    OpenAIRE

    Haouas, Nabiha; Bertrand, Pierre R.

    2013-01-01

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

  19. Evaluation of Deep Space Ka-Band Data Transfer using Radiometeorological Forecasts and Radiometer Measurements

    Science.gov (United States)

    Montopoli, Mario; Marzano, Frank S.; Biscarini, Marianna; Milani, Luca; Cimini, Domenico; De Sanctis, Klaide; Di Fabio, Saverio

    2016-04-01

    Deep space exploration is aimed at acquiring information about the solar system. In this scenario, telecommunications links between Earth ground receiving stations and extra-terrestrial satellite platforms have to be designed in order to ensure the optimal transfer of the acquired scientific data back to the Earth. A significant communication capacity has to be planned when very large distances, as those characterising deep space links, are involved thus fostering more ambitious scientific mission requirements. At the current state of the art, two microwave channel frequencies are used to perform the deep space data transfer: X band (~ 8.4 GHz) and Ka band (~ 32 GHz) channel. Ka-band transmission can offer an advantage over X-band in terms of antenna performance with the same antenna effective area and an available data transfer bandwidth (50 times higher at Ka band than X band). However, Earth troposphere-related impairments can affects the space-to-Earth carrier signals at frequencies higher than 10 GHz by degrading its integrity and thus reducing the deep space channel temporal availability. Such atmospheric impairments, especially in terms of path attenuation, their statistic and the possibility to forecast them in the next 24H at the Earth's receiving station would allow a more accurate design of the deep space link, promoting the mitigation of the detrimental effects on the link availability. To pursue this aim, meteorological forecast models and in situ measurements need to be considered in order to characterise the troposphere in terms of signal path attenuation at current and future time. In this work, we want to show how the synergistic use of meteorological forecasts, radiative transfer simulations and in situ measurements such as microwave radiometry observations, rain gauges and radiosoundings, can aid the optimisation of a deep space link at Ka band and improve its performance with respect to usual practices. The outcomes of the study are in the

  20. Evaluation of global monitoring and forecasting systems at Mercator Océan

    Science.gov (United States)

    Lellouche, J.-M.; Le Galloudec, O.; Drévillon, M.; Régnier, C.; Greiner, E.; Garric, G.; Ferry, N.; Desportes, C.; Testut, C.-E.; Bricaud, C.; Bourdallé-Badie, R.; Tranchant, B.; Benkiran, M.; Drillet, Y.; Daudin, A.; De Nicola, C.

    2013-01-01

    Since December 2010, the MyOcean global analysis and forecasting system has consisted of the Mercator Océan NEMO global 1/4° configuration with a 1/12° nested model over the Atlantic and the Mediterranean. The open boundary data for the nested configuration come from the global 1/4° configuration at 20° S and 80° N. The data are assimilated by means of a reduced-order Kalman filter with a 3-D multivariate modal decomposition of the forecast error. It includes an adaptive-error estimate and a localization algorithm. A 3-D-Var scheme provides a correction for the slowly evolving large-scale biases in temperature and salinity. Altimeter data, satellite sea surface temperature and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions for numerical ocean forecasting. In addition to the quality control performed by data producers, the system carries out a proper quality control on temperature and salinity vertical profiles in order to minimise the risk of erroneous observed profiles being assimilated in the model. This paper describes the recent systems used by Mercator Océan and the validation procedure applied to current MyOcean systems as well as systems under development. The paper shows how refinements or adjustments to the system during the validation procedure affect its quality. Additionally, we show that quality checks (in situ, drifters) and data sources (satellite sea surface temperature) have as great an impact as the system design (model physics and assimilation parameters). The results of the scientific assessment are illustrated with diagnostics over the year 2010 mainly, assorted with time series over the 2007-2011 period. The validation procedure demonstrates the accuracy of MyOcean global products, whose quality is stable over time. All monitoring systems are close to altimetric observations with a forecast RMS difference of 7 cm. The update of the mean dynamic topography corrects local

  1. Evaluation of risk change-point for novice teenage drivers.

    Science.gov (United States)

    Li, Qing; Guo, Feng; Klauer, Sheila G; Simons-Morton, Bruce G

    2017-11-01

    The driving risk of novice teenagers is the highest during the initial period after licensure but decreases rapidly. This paper applies two recurrent-event change-point models to detect the time of change in driving risks. The models are based on a non-homogeneous Poisson process with piecewise constant intensity functions. We show that the maximum likelihood estimators of the change-points can only occur at the event times and they are consistent. A simulation study is conducted to demonstrate the model performance under different scenarios. The proposed models are applied to the Naturalistic Teenage Driving Study, which continuously recorded in situ driving behaviour of 42 novice teenage drivers for the first 18 months after licensure using sophisticated in-vehicle instrumentation. The results indicate that approximately half of the drivers have lower risk after 73.0h of independent driving after licensure while the risk for others increases. On the average the driving risk deceases after the change-point. The results provide critical information for safety education, safety countermeasure development, and Graduated Driver Licensing policy making. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Evaluation of sequential images for photogrammetrically point determination

    Science.gov (United States)

    Kowalczyk, M.

    2011-12-01

    Close range photogrammetry encounters many problems with reconstruction of objects three-dimensional shape. Relative orientation parameters of taken photos makes usually key role leading to right solution of this problem. Automation of technology process is hardly performed due to recorded scene complexity and configuration of camera positions. This configuration makes the process of joining photos into one set usually impossible automatically. Application of camcorder is the solution widely proposed in literature for support in 3D models creation. Main advantages of this tool are connected with large number of recorded images and camera positions. Exterior orientation changes barely between two neighboring frames. Those features of film sequence gives possibilities for creating models with basic algorithms, working faster and more robust, than with remotely taken photos. The first part of this paper presents results of experiments determining interior orientation parameters of some sets of frames, presenting three-dimensional test field. This section describes calibration repeatability of film frames taken from camcorder. It is important due to stability of interior camera geometric parameters. Parametric model of systematical errors was applied for correcting images. Afterwards a short film of the same test field had been taken for determination of check points group. This part has been done for controlling purposes of camera application in measurement tasks. Finally there are presented some results of experiments which compare determination of recorded object points in 3D space. In common digital photogrammetry, where separate photos are used, first levels of image pyramids are taken to connect with feature based matching. This complicated process creates a lot of emergencies, which can produce false detections of image similarities. In case of digital film camera, authors of publications avoid this dangerous step, going straightly to area based matching, aiming

  3. Use of Data Denial Experiments to Evaluate ESA Forecast Sensitivity Patterns

    Energy Technology Data Exchange (ETDEWEB)

    Zack, J; Natenberg, E J; Knowe, G V; Manobianco, J; Waight, K; Hanley, D; Kamath, C

    2011-09-13

    The overall goal of this multi-phased research project known as WindSENSE is to develop an observation system deployment strategy that would improve wind power generation forecasts. The objective of the deployment strategy is to produce the maximum benefit for 1- to 6-hour ahead forecasts of wind speed at hub-height ({approx}80 m). In this phase of the project the focus is on the Mid-Columbia Basin region which encompasses the Bonneville Power Administration (BPA) wind generation area shown in Figure 1 that includes Klondike, Stateline, and Hopkins Ridge wind plants. The Ensemble Sensitivity Analysis (ESA) approach uses data generated by a set (ensemble) of perturbed numerical weather prediction (NWP) simulations for a sample time period to statistically diagnose the sensitivity of a specified forecast variable (metric) for a target location to parameters at other locations and prior times referred to as the initial condition (IC) or state variables. The ESA approach was tested on the large-scale atmospheric prediction problem by Ancell and Hakim 2007 and Torn and Hakim 2008. ESA was adapted and applied at the mesoscale by Zack et al. (2010a, b, and c) to the Tehachapi Pass, CA (warm and cools seasons) and Mid-Colombia Basin (warm season only) wind generation regions. In order to apply the ESA approach at the resolution needed at the mesoscale, Zack et al. (2010a, b, and c) developed the Multiple Observation Optimization Algorithm (MOOA). MOOA uses a multivariate regression on a few select IC parameters at one location to determine the incremental improvement of measuring multiple variables (representative of the IC parameters) at various locations. MOOA also determines how much information from each IC parameter contributes to the change in the metric variable at the target location. The Zack et al. studies (2010a, b, and c), demonstrated that forecast sensitivity can be characterized by well-defined, localized patterns for a number of IC variables such as 80-m

  4. DEWEPS - Development and Evaluation of new Wind forecasting tools with an Ensemble Prediction System

    Energy Technology Data Exchange (ETDEWEB)

    Moehrlen, C.; Joergensen, Jess

    2012-02-15

    There is an ongoing trend of increased privatization in the handling of renewable energy. This trend is required to ensure an efficient energy system, where improvements that make economic sense are prioritised. The reason why centralized forecasting can be a challenge in that matter is that the TSOs tend to optimize on physical error rather than cost. Consequently, the market is likely to speculate against the TSO, which in turn increases the cost of balancing. A privatized pool of wind and/or solar power is more difficult to speculate against, because the optimization criteria is unpredictable due to subjective risk considerations that may be taken into account at any time. Although there is and additional level of costs for the trading of the private volume, it can be argued that competition will accelerate efficiency from an economic perspective. The amount of power put into the market will become less predictable, when the wind power spot market bid takes place on the basis of a risk consideration in addition to the forecast information itself. The scope of this project is to contribute to more efficient wind power integration targeted both to centralised and decentralised cost efficient IT solutions, which will complement each other in market based energy systems. The DEWEPS project resulted in an extension of the number of Ensemble forecasts, an incremental trade strategy for balancing unpredictable power production, and an IT platform for efficient handling of power generation units. Together, these three elements contribute to less need for reserves, more capacity in the market, and thus more competition. (LN)

  5. Evaluating the 6-point Remainder Function Near the Collinear Limit

    CERN Document Server

    Papathanasiou, Georgios

    2014-01-01

    The simplicity of maximally supersymmetric Yang-Mills theory makes it an ideal theoretical laboratory for developing computational tools, which eventually find their way to QCD applications. In this contribution, we continue the investigation of a recent proposal by Basso, Sever and Vieira, for the nonperturbative description of its planar scattering amplitudes, as an expansion around collinear kinematics. The method of arXiv:1310.5735, for computing the integrals the latter proposal predicts for the leading term in the expansion of the 6-point remainder function, is extended to one the subleading terms. In particular, we focus on the contribution of the 2-gluon bound state in the dual flux tube picture, proving its general form at any order in the coupling, and providing explicit expressions up to 6 loops. These are included in the ancillary file accompanying the version of this article on the arXiv.

  6. Evaluating the reliability of point estimates of wetland reference evaporation

    Directory of Open Access Journals (Sweden)

    H. Gavin

    2003-01-01

    Full Text Available The Penman-Monteith formulation of evaporation has been criticised for its reliance upon point estimates so that areal estimates of wetland evaporation based upon single weather stations may be misleading. Typically, wetlands comprise a complex mosaic of land cover types from each of which evaporative rates may differ. The need to account for wetland patches when monitoring hydrological fluxes has been noted. This paper presents work carried out over a wet grassland in Southern England. The significance of fetch on actual evaporation was examined using the approach adopted by Gash (1986 based upon surface roughness to estimate the fraction of evaporation sensed from a specified distance upwind of the monitoring station. This theoretical analysis (assuming near-neutral conditions reveals that the fraction of evaporation contributed by the surrounding area increases steadily to a value of 77% at a distance of 224 m and thereafter declines rapidly. Thus, point climate observations may not reflect surface conditions at greater distances. This result was tested through the deployment of four weather stations on the wetland. The resultant data suggested that homogeneous conditions prevailed so that the central weather station provided reliable areal estimates of reference evaporation during the observation period March–April 1999. This may be a result of not accounting for high wind speeds and roughness found in wetlands that lead to widespread atmospheric mixing. It should be noted this analysis was based upon data collected during the period March-April when wind direction was constant (westerly and the land surface was moist. There could be more variation at other times of the year that would lead to greater heterogeneity in actual evaporation. Keywords: evaporation, Penman-Monteith, automatic weather station, fetch, wetland

  7. Accuracy analysis of point cloud modeling for evaluating concrete specimens

    Science.gov (United States)

    D'Amico, Nicolas; Yu, Tzuyang

    2017-04-01

    Photogrammetric methods such as structure from motion (SFM) have the capability to acquire accurate information about geometric features, surface cracks, and mechanical properties of specimens and structures in civil engineering. Conventional approaches to verify the accuracy in photogrammetric models usually require the use of other optical techniques such as LiDAR. In this paper, geometric accuracy of photogrammetric modeling is investigated by studying the effects of number of photos, radius of curvature, and point cloud density (PCD) on estimated lengths, areas, volumes, and different stress states of concrete cylinders and panels. Four plain concrete cylinders and two plain mortar panels were used for the study. A commercially available mobile phone camera was used in collecting all photographs. Agisoft PhotoScan software was applied in photogrammetric modeling of all concrete specimens. From our results, it was found that the increase of number of photos does not necessarily improve the geometric accuracy of point cloud models (PCM). It was also found that the effect of radius of curvature is not significant when compared with the ones of number of photos and PCD. A PCD threshold of 15.7194 pts/cm3 is proposed to construct reliable and accurate PCM for condition assessment. At this PCD threshold, all errors for estimating lengths, areas, and volumes were less than 5%. Finally, from the study of mechanical property of a plain concrete cylinder, we have found that the increase of stress level inside the concrete cylinder can be captured by the increase of radial strain in its PCM.

  8. Evaluation of global monitoring and forecasting systems at Mercator Océan

    Directory of Open Access Journals (Sweden)

    J.-M. Lellouche

    2013-01-01

    Full Text Available Since December 2010, the MyOcean global analysis and forecasting system has consisted of the Mercator Océan NEMO global 1/4° configuration with a 1/12° nested model over the Atlantic and the Mediterranean. The open boundary data for the nested configuration come from the global 1/4° configuration at 20° S and 80° N.

    The data are assimilated by means of a reduced-order Kalman filter with a 3-D multivariate modal decomposition of the forecast error. It includes an adaptive-error estimate and a localization algorithm. A 3-D-Var scheme provides a correction for the slowly evolving large-scale biases in temperature and salinity. Altimeter data, satellite sea surface temperature and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions for numerical ocean forecasting. In addition to the quality control performed by data producers, the system carries out a proper quality control on temperature and salinity vertical profiles in order to minimise the risk of erroneous observed profiles being assimilated in the model.

    This paper describes the recent systems used by Mercator Océan and the validation procedure applied to current MyOcean systems as well as systems under development. The paper shows how refinements or adjustments to the system during the validation procedure affect its quality. Additionally, we show that quality checks (in situ, drifters and data sources (satellite sea surface temperature have as great an impact as the system design (model physics and assimilation parameters. The results of the scientific assessment are illustrated with diagnostics over the year 2010 mainly, assorted with time series over the 2007–2011 period. The validation procedure demonstrates the accuracy of MyOcean global products, whose quality is stable over time. All monitoring systems are close to altimetric observations with a forecast RMS difference of 7 cm. The update of the mean

  9. Against all odds -- Probabilistic forecasts and decision making

    Science.gov (United States)

    Liechti, Katharina; Zappa, Massimiliano

    2015-04-01

    In the city of Zurich (Switzerland) the setting is such that the damage potential due to flooding of the river Sihl is estimated to about 5 billion US dollars. The flood forecasting system that is used by the administration for decision making runs continuously since 2007. It has a time horizon of max. five days and operates at hourly time steps. The flood forecasting system includes three different model chains. Two of those are run by the deterministic NWP models COSMO-2 and COSMO-7 and one is driven by the probabilistic NWP COSMO-Leps. The model chains are consistent since February 2010, so five full years are available for the evaluation for the system. The system was evaluated continuously and is a very nice example to present the added value that lies in probabilistic forecasts. The forecasts are available on an online-platform to the decision makers. Several graphical representations of the forecasts and forecast-history are available to support decision making and to rate the current situation. The communication between forecasters and decision-makers is quite close. To put it short, an ideal situation. However, an event or better put a non-event in summer 2014 showed that the knowledge about the general superiority of probabilistic forecasts doesn't necessarily mean that the decisions taken in a specific situation will be based on that probabilistic forecast. Some years of experience allow gaining confidence in the system, both for the forecasters and for the decision-makers. Even if from the theoretical point of view the handling during crisis situation is well designed, a first event demonstrated that the dialog with the decision-makers still lacks of exercise during such situations. We argue, that a false alarm is a needed experience to consolidate real-time emergency procedures relying on ensemble predictions. A missed event would probably also fit, but, in our case, we are very happy not to report about this option.

  10. Evaluation of Enhanced High Resolution MODIS/AMSR-E SSTs and the Impact on Regional Weather Forecast

    Science.gov (United States)

    Schiferl, Luke D.; Fuell, Kevin K.; Case, Jonathan L.; Jedlovec, Gary J.

    2010-01-01

    Over the last few years, the NASA Short-term Prediction Research and Transition (SPoRT) Center has been generating a 1-km sea surface temperature (SST) composite derived from retrievals of the Moderate Resolution Imaging Spectroradiometer (MODIS) for use in operational diagnostics and regional model initialization. With the assumption that the day-to-day variation in the SST is nominal, individual MODIS passes aboard the Earth Observing System (EOS) Aqua and Terra satellites are used to create and update four composite SST products each day at 0400, 0700, 1600, and 1900 UTC, valid over the western Atlantic and Caribbean waters. A six month study from February to August 2007 over the marine areas surrounding southern Florida was conducted to compare the use of the MODIS SST composite versus the Real-Time Global SST analysis to initialize the Weather Research and Forecasting (WRF) model. Substantial changes in the forecast heat fluxes were seen at times in the marine boundary layer, but relatively little overall improvement was measured in the sensible weather elements. The limited improvement in the WRF model forecasts could be attributed to the diurnal changes in SST seen in the MODIS SST composites but not accounted for by the model. Furthermore, cloud contamination caused extended periods when individual passes of MODIS were unable to update the SSTs, leading to substantial SST latency and a cool bias during the early summer months. In order to alleviate the latency problems, the SPoRT Center recently enhanced its MODIS SST composite by incorporating information from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) instruments as well as the Operational Sea Surface Temperature and Sea Ice Analysis. These enhancements substantially decreased the latency due to cloud cover and improved the bias and correlation of the composites at available marine point observations. While these enhancements improved upon the modeled cold bias using the original MODIS SSTs

  11. Evaluating the Impact of AIRS Observations on Regional Forecasts at the SPoRT Center

    Science.gov (United States)

    Zavodsky, Bradley

    2011-01-01

    NASA Short-term Prediction Research and Transition (SPoRT) Center collaborates with operational partners of different sizes and operational goals to improve forecasts using targeted projects and data sets. Modeling and DA activities focus on demonstrating utility of NASA data sets and capabilities within operational systems. SPoRT has successfully assimilated the Atmospheric Infrared Sounder (AIRS) radiance and profile data. A collaborative project is underway with the Joint Center for Satellite Data Assimilation (JCSDA) to use AIRS profiles to better understand the impact of AIRS radiances assimilated within Gridpoint Statistical Interpolation (GSI) in hopes of engaging the operational DA community in a reassessment of assimilation methodologies to more effectively assimilate hyperspectral radiances.

  12. Evaluation of Probabilistic Precipitation Forecast of TIGGE data and Probabilistic Flood Prediction over Huaihe Basin

    Science.gov (United States)

    Zhao, L.

    2016-12-01

    Rainfall is one of the most important weather phenomena which could result in severe flood and huge economic loss. A timely and accurate quantitative precipitation forecast (QPF) is a primary goal of operational prediction and one of the most factor that affects the issuance of flood warning. In order to improve a single ensemble prediction system (EPS), multi-model prediction system (MPS) and probabilistic prediction were developed with considering the characteristics of many EPS, i.e.. The simulation of initial uncertainties. The THORPEX Interactive Grand Global Ensemble (TIGGE) program provides a very good opportunity for MPS, probabilistic precipitation, and flood with further research. Based on the precipitation and temperature data obtained from TIGGE-China Meteorological Administration (CMA) archiving center and the rain gauge data, the three-layer variable infiltration capacity (VIC-3L) land surface model was employed to carry out probabilistic hydrological forecast experiments over the upper Huaihe River catchment from 20 July to 3 August 2008. The results show that the performance of the ensemble probabilistic prediction from each ensemble prediction system (EPS) is better than that of the deterministic prediction. Especially, that 72-h prediction has been improved obviously. The ensemble spread goes widely with increasing lead time and more observed discharge is bracketed in the 5th-99th quantile. The accuracy of river discharge prediction driven by the ECMWF-Centre EPS is higher than that driven by the CMA-EPS and the NCEP-EPS, and the grand-ensemble prediction is the best for hydrological prediction using the VIC model. With regard to Wangjiaba station, all predictions made with a single EPS are close to the observation between the 25th and 75th quantile. The onset of the flood ascending and the river discharge thresholds are predicted well, and so is the second rising limb. Nevertheless, the flood recession is not well predicted.

  13. Evaluation of TRMM satellite-based precipitation indexes for flood forecasting over Riyadh City, Saudi Arabia

    Science.gov (United States)

    Tekeli, Ahmet Emre; Fouli, Hesham

    2016-10-01

    Floods are among the most common disasters harming humanity. In particular, flash floods cause hazards to life, property and any type of structures. Arid and semi-arid regions are equally prone to flash floods like regions with abundant rainfall. Despite rareness of intensive and frequent rainfall events over Kingdom of Saudi Arabia (KSA); an arid/semi-arid region, occasional flash floods occur and result in large amounts of damaging surface runoff. The flooding of 16 November, 2013 in Riyadh; the capital city of KSA, resulted in killing some people and led to much property damage. The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) Real Time (RT) data (3B42RT) are used herein for flash flood forecasting. 3B42RT detected high-intensity rainfall events matching with the distribution of observed floods over KSA. A flood early warning system based on exceedance of threshold limits on 3B42RT data is proposed for Riyadh. Three different indexes: Constant Threshold (CT), Cumulative Distribution Functions (CDF) and Riyadh Flood Precipitation Index (RFPI) are developed using 14-year 3B42RT data from 2000 to 2013. RFPI and CDF with 90% captured the three major flooding events that occurred in February 2005, May 2010 and November 2013 in Riyadh. CT with 3 mm/h intensity indicated the 2013 flooding, but missed those of 2005 and 2010. The methodology implemented herein is a first-step simple and accurate way for flash flood forecasting over Riyadh. The simplicity of the methodology enables its applicability for the TRMM follow-on missions like Global Precipitation Measurement (GPM) mission.

  14. Trends in the predictive performance of raw ensemble weather forecasts

    Science.gov (United States)

    Hemri, Stephan; Scheuerer, Michael; Pappenberger, Florian; Bogner, Konrad; Haiden, Thomas

    2015-04-01

    Over the last two decades the paradigm in weather forecasting has shifted from being deterministic to probabilistic. Accordingly, numerical weather prediction (NWP) models have been run increasingly as ensemble forecasting systems. The goal of such ensemble forecasts is to approximate the forecast probability distribution by a finite sample of scenarios. Global ensemble forecast systems, like the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble, are prone to probabilistic biases, and are therefore not reliable. They particularly tend to be underdispersive for surface weather parameters. Hence, statistical post-processing is required in order to obtain reliable and sharp forecasts. In this study we apply statistical post-processing to ensemble forecasts of near-surface temperature, 24-hour precipitation totals, and near-surface wind speed from the global ECMWF model. Our main objective is to evaluate the evolution of the difference in skill between the raw ensemble and the post-processed forecasts. The ECMWF ensemble is under continuous development, and hence its forecast skill improves over time. Parts of these improvements may be due to a reduction of probabilistic bias. Thus, we first hypothesize that the gain by post-processing decreases over time. Based on ECMWF forecasts from January 2002 to March 2014 and corresponding observations from globally distributed stations we generate post-processed forecasts by ensemble model output statistics (EMOS) for each station and variable. Parameter estimates are obtained by minimizing the Continuous Ranked Probability Score (CRPS) over rolling training periods that consist of the n days preceding the initialization dates. Given the higher average skill in terms of CRPS of the post-processed forecasts for all three variables, we analyze the evolution of the difference in skill between raw ensemble and EMOS forecasts. The fact that the gap in skill remains almost constant over time, especially for near

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

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

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  17. Forecasting Sales

    NARCIS (Netherlands)

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

    2009-01-01

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

  18. First evaluation of aerosol profiles forecasted in ECMWF C-IFS model with E-PROFILE ceilometer network

    Science.gov (United States)

    Hervo, Maxime; Haefele, Alexander

    2017-04-01

    E-PROFILE is a EUMETNET observation programme regrouping measurements of Automatic Lidars and Ceilometers (ALC). Twenty National Weather Services are funding E-PROFILE and more than 10 universities are contributing to the network. At the beginning of 2017, 68 ALCs were sending data operationally. Several hundreds of instruments are expected in the next years. ALCs have a strong potential for models evaluations and assimilation: they measure 24/7 and the high number of instruments can compensate for their limited power. ALC measurements from 8 countries were compared with ECMWF Composition Integrated Forecasting System (C-IFS) model. To our knowledge, it is the first time that this kind of comparison is realised on a continental scale. Two forward operators were used to convert aerosol concentration in simulated Lidar profile. First, the methodology used by the Copernicus Atmosphere Monitoring Service (CAMS) was used. Secondly, the experimental forward operator implemented at ECMWF was tested. On a 3-month period, the average difference between ALC measurements and CAMS forward operator was less than 50%, suggesting the good agreement between model and measurements. However, the sea-salt concentration forecasted in central Europe is clearly over-estimated. The concentration of Sulphate aerosol in the free troposphere was also clearly overestimated by the model. Similar results were found with ECMWF experimental forward operator.The comparison between measured and simulated profiles also highlights instrumental limitations like overlap artefacts. After the evaluation, assimilation tesst will be performed to integrate the E-PROFILE observations in the ECMWF assimilation procedure. Acknowledgement: This study was realised in the frame of the COST Action TOPROF (ES1303). The authors would like to acknowledge all the participants for their fruitful collaboration.

  19. Developing and Evaluating RGB Composite MODIS Imagery for Applications in National Weather Service Forecast Offices

    Science.gov (United States)

    Oswald, Hayden; Molthan, Andrew L.

    2011-01-01

    Satellite remote sensing has gained widespread use in the field of operational meteorology. Although raw satellite imagery is useful, several techniques exist which can convey multiple types of data in a more efficient way. One of these techniques is multispectral compositing. The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed two multispectral satellite imagery products which utilize data from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra and Aqua satellites, based upon products currently generated and used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The nighttime microphysics product allows users to identify clouds occurring at different altitudes, but emphasizes fog and low cloud detection. This product improves upon current spectral difference and single channel infrared techniques. Each of the current products has its own set of advantages for nocturnal fog detection, but each also has limiting drawbacks which can hamper the analysis process. The multispectral product combines each current product with a third channel difference. Since the final image is enhanced with color, it simplifies the fog identification process. Analysis has shown that the nighttime microphysics imagery product represents a substantial improvement to conventional fog detection techniques, as well as provides a preview of future satellite capabilities to forecasters.

  20. Evaluation of Dynamical Downscaling Resolution Effect on Wind Energy Forecast Value for a Wind Farm in Central Sweden

    DEFF Research Database (Denmark)

    Rosgaard, Martin Haubjerg; Hahmann, Andrea N.; Nielsen, Torben Skov

    2014-01-01

    energy. The present study aims to quantify value added to wind energy forecasts in the 12-48 hour leadtime by downscaling global numerical weather prediction (NWP) data from the National Centers for Environmental Prediction Global Forecast System (GFS) using the limited-area NWP model described......For any energy system relying on wind power, accurate forecasts of wind fluctuations are essential for efficient integration into the power grid. Increased forecast precision allows end-users to plan day-ahead operation with reduced risk of penalties which in turn supports the feasibility of wind...

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  2. Do quantitative decadal forecasts from GCMs provide decision relevant skill?

    Science.gov (United States)

    Suckling, E. B.; Smith, L. A.

    2012-04-01

    It is widely held that only physics-based simulation models can capture the dynamics required to provide decision-relevant probabilistic climate predictions. This fact in itself provides no evidence that predictions from today's GCMs are fit for purpose. Empirical (data-based) models are employed to make probability forecasts on decadal timescales, where it is argued that these 'physics free' forecasts provide a quantitative 'zero skill' target for the evaluation of forecasts based on more complicated models. It is demonstrated that these zero skill models are competitive with GCMs on decadal scales for probability forecasts evaluated over the last 50 years. Complications of statistical interpretation due to the 'hindcast' nature of this experiment, and the likely relevance of arguments that the lack of hindcast skill is irrelevant as the signal will soon 'come out of the noise' are discussed. A lack of decision relevant quantiative skill does not bring the science-based insights of anthropogenic warming into doubt, but it does call for a clear quantification of limits, as a function of lead time, for spatial and temporal scales on which decisions based on such model output are expected to prove maladaptive. Failing to do so may risk the credibility of science in support of policy in the long term. The performance amongst a collection of simulation models is evaluated, having transformed ensembles of point forecasts into probability distributions through the kernel dressing procedure [1], according to a selection of proper skill scores [2] and contrasted with purely data-based empirical models. Data-based models are unlikely to yield realistic forecasts for future climate change if the Earth system moves away from the conditions observed in the past, upon which the models are constructed; in this sense the empirical model defines zero skill. When should a decision relevant simulation model be expected to significantly outperform such empirical models? Probability

  3. 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

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

    Directory of Open Access Journals (Sweden)

    Filip Chybalski

    2017-01-01

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

  5. Fishing Forecasts

    Science.gov (United States)

    1988-01-01

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

  6. Evaluation of Dynamical Downscaling Resolution Effect on Wind Energy Forecast Value for a Wind Farm in Central Sweden

    Science.gov (United States)

    Rosgaard, Martin; Hahmann, Andrea; Skov Nielsen, Torben; Giebel, Gregor; Ejnar Sørensen, Poul; Madsen, Henrik

    2014-05-01

    For any energy system relying on wind power, accurate forecasts of wind fluctuations are essential for efficient integration into the power grid. Increased forecast precision allows end-users to plan day-ahead operation with reduced risk of penalties which in turn supports the feasibility of wind energy. This study aims to quantify value added to wind energy forecasts in the 12-48 hour leadtime by downscaling global numerical weather prediction (NWP) data using a limited-area NWP model. The accuracy of statistical wind power forecasting tools depends strongly on this NWP input. Typical performance metrics are mean absolute error or root mean square error for predicted- against observed wind power production, and these metrics are closely related to wind speed forecast bias and correlation with observations. Wind speed bias can be handled in the statistical wind power forecasting model, though it is entirely up to it's NWP input to describe the wind speed correlation correctly. The basis of comparison for forecasts is data from the Stor-Rotliden wind farm in central Sweden. The surrounding forest adds to the forecasting challenge, thus motivating the downscaling experiment as the potential for wind power forecast improvement is higher in complex terrain. The 40 Vestas V90 turbines were erected in 2009 and correspond to 78MWe installed electrical capacity. Forecasts from global and limited-area NWP models, together covering five different horizontal computational grid spacings of ~50km down to ~1km, are studied for a yearlong, continuous time period. The preliminary results shown quantify forecast strengths and weaknesses for each NWP model resolution.

  7. Strategic Forecasting

    DEFF Research Database (Denmark)

    Duus, Henrik Johannsen

    2016-01-01

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

  8. 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...

  9. DeMand: A tool for evaluating and comparing device-level demand and supply forecast models

    DEFF Research Database (Denmark)

    Neupane, Bijay; Siksnys, Laurynas; Pedersen, Torben Bach

    2016-01-01

    Fine-grained device-level predictions of both shiftable and non-shiftable energy demand and supply is vital in order to take advantage of Demand Response (DR) for efficient utilization of Renewable Energy Sources. The selection of an effective device-level load forecast model is a challenging task......, mainly due to the diversity of the models and the lack of proper tools and datasets that can be used to validate them. In this paper, we introduce the DeMand system for fine-tuning, analyzing, and validating the device-level forecast models. The system offers several built-in device-level measurement...... datasets, forecast models, features, and errors measures, thus semi-automating most of the steps of the forecast model selection and validation process. This paper presents the architecture and data model of the DeMand system; and provides a use-case example on how one particular forecast model...

  10. Point-of-care diagnostic tools : Selection, evaluation and implementation in resource-constrained settings

    NARCIS (Netherlands)

    Kosack, C.S.

    2017-01-01

    In recent year’s point-of-care diagnostic tools especially for the three main killer diseases HIV/AIDS, tuberculosis and malaria have been emerging on the market. This thesis examines the selection, evaluation and implementation of point-of-care diagnostic tools for use in resource-constrained

  11. Performance evaluation of clay-sawdust composite filter for point of ...

    African Journals Online (AJOL)

    Performance evaluation of clay-sawdust composite filter for point of use water treatment. ... Nigerian Journal of Technology ... This work explores the possibility of improving water quality and eliminating the possibility of recontamination by the use of point of use (POU) water filters made from cheap locally available materials ...

  12. 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

    2017-10-01

    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

  13. Extended performance evaluation based on DEA a multidimensional point of view

    CERN Document Server

    Neumann, Ludmila

    2017-01-01

    This book introduces new methodological developments of Data Envelopment Analysis (DEA) that satisfy the demands of business practice and provide a multidimensional point of view on the evaluation of organizational performance.

  14. Creating the data basis for environmental evaluations with the Oil Point Method

    DEFF Research Database (Denmark)

    Bey, Niki; Lenau, Torben Anker

    1999-01-01

    with rules-of-thumb. The central idea is that missing indicators can be calculated or estimated by the designers themselves.After discussing energy-related environmental evaluation and arguing for its application in evaluation of concepts, the paper focuses on the basic problem of missing data and describes...... the way in which the problem may be solved by making Oil Point evaluations. Sources of energy data are mentioned. Typical deficits to be aware of - such as the negligence of efficiency factors - are revealed and discussed. Comparative case studies which have shown encouraging results are mentioned as well.......A simple, indicator-based method for environmental evaluations, the Oil Point Method, has been developed. Oil Points are derived from energy data and refer to kilograms of oil, therefore the name. In the Oil Point Method, a certain degree of inaccuracy is explicitly accepted like it is the case...

  15. Point of Maintenance Ruggedized Operational Device Evaluation and Observation Test Report

    National Research Council Canada - National Science Library

    Gorman, Megan

    2002-01-01

    .... The Ruggedized Operational Device Evaluation and Observation (RODEO) test examined hardware packaging, software user interface, and environmental factors associated with the usability of potential Point of Maintenance (POMx) electronic tools...

  16. Evaluation of methods for rapid determination of freezing point of aviation fuels

    Science.gov (United States)

    Mathiprakasam, B.

    1982-01-01

    Methods for identification of the more promising concepts for the development of a portable instrument to rapidly determine the freezing point of aviation fuels are described. The evaluation process consisted of: (1) collection of information on techniques previously used for the determination of the freezing point, (2) screening and selection of these techniques for further evaluation of their suitability in a portable unit for rapid measurement, and (3) an extensive experimental evaluation of the selected techniques and a final selection of the most promising technique. Test apparatuses employing differential thermal analysis and the change in optical transparency during phase change were evaluated and tested. A technique similar to differential thermal analysis using no reference fuel was investigated. In this method, the freezing point was obtained by digitizing the data and locating the point of inflection. Results obtained using this technique compare well with those obtained elsewhere using different techniques. A conceptual design of a portable instrument incorporating this technique is presented.

  17. Development and Performance Evaluation of a Ceramic Filter for Point-of-Use Water Purification

    National Research Council Canada - National Science Library

    Bukola Olalekan Bolaji; Olugbenga Oluseyi Akande

    2013-01-01

    In this work, a ceramic filter for point-of-use water purification was designed, fabricated and tested to evaluate its performance in filtering water to the World Health Organisation (WHO) standards...

  18. A New Reference for Wind Power Forecasting

    DEFF Research Database (Denmark)

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

    1998-01-01

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

  19. Evaluation of Dynamical Downscaling Resolution Effect on Wind Energy Forecast Value for a Wind Farm in Central Sweden

    DEFF Research Database (Denmark)

    Rosgaard, Martin Haubjerg; Hahmann, Andrea N.; Nielsen, Torben Skov

    For any energy system relying on wind power, accurate forecasts of wind fluctuations are essential for efficient utilisation in the power grid. Statistical wind power prediction tools [1] use numerical weather prediction (NWP) model data along with measurements and can correct magnitude errors...... the two time series. Results on limited-area NWP model performance, with focus on the 12th to 48th forecast hour horizon relevant for Elspot auction bidding on the Nord Pool Spot market [2], are presented....

  20. Entropy Based Test Point Evaluation and Selection Method for Analog Circuit Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Yuan Gao

    2014-01-01

    Full Text Available By simplifying tolerance problem and treating faulty voltages on different test points as independent variables, integer-coded table technique is proposed to simplify the test point selection process. Usually, simplifying tolerance problem may induce a wrong solution while the independence assumption will result in over conservative result. To address these problems, the tolerance problem is thoroughly considered in this paper, and dependency relationship between different test points is considered at the same time. A heuristic graph search method is proposed to facilitate the test point selection process. First, the information theoretic concept of entropy is used to evaluate the optimality of test point. The entropy is calculated by using the ambiguous sets and faulty voltage distribution, determined by component tolerance. Second, the selected optimal test point is used to expand current graph node by using dependence relationship between the test point and graph node. Simulated results indicate that the proposed method more accurately finds the optimal set of test points than other methods; therefore, it is a good solution to minimize the size of the test point set. To simplify and clarify the proposed method, only catastrophic and some specific parametric faults are discussed in this paper.

  1. Simulations over South Asia using the Weather Research and Forecasting model with Chemistry (WRF-Chem: set-up and meteorological evaluation

    Directory of Open Access Journals (Sweden)

    R. Kumar

    2012-03-01

    Full Text Available The configuration and evaluation of the meteorology is presented for simulations over the South Asian region using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem. Temperature, water vapor, dew point temperature, zonal and meridional wind components, precipitation and tropopause pressure are evaluated against radiosonde and satellite-borne (AIRS and TRMM observations along with NCEP/NCAR reanalysis fields for the year 2008. Chemical fields, with focus on tropospheric ozone, are evaluated in a companion paper. The spatial and temporal variability in meteorological variables is well simulated by the model with temperature, dew point temperature and precipitation showing higher values during summer/monsoon and lower during winter. The index of agreement for all the parameters is estimated to be greater than 0.6 indicating that WRF-Chem is capable of simulating the variations around the observed mean. The mean bias (MB and root mean square error (RMSE in modeled temperature, water vapor and wind components show an increasing tendency with altitude. MB and RMSE values are within ±2 K and 1–4 K for temperature, 30% and 20–65% for water vapor and 1.6 m s−1 and 5.1 m s−1 for wind components. The spatio-temporal variability of precipitation is also reproduced reasonably well by the model but the model overestimates precipitation in summer and underestimates precipitation during other seasons. Such a behavior of modeled precipitation is in agreement with previous studies on South Asian monsoon. The comparison with radiosonde observations indicates a relatively better model performance for inland sites as compared to coastal and island sites. The MB and RMSE in tropopause pressure are estimated to be less than 25 hPa. Sensitivity simulations show that biases in meteorological simulations can introduce errors of ±(10–25% in simulations of tropospheric ozone, CO and NO

  2. Short-term localized weather forecasting by using different artificial neural network algorithm in tropical climate

    OpenAIRE

    Mohd-Safar, Noor Zuraidin; Ndzi, David Lorater; Kagalidis, Ioannis; Yang, Yanyan; Zakaria, Ammar

    2016-01-01

    This paper evaluates the performance of localized weather forecasting model using Artificial Neural Network (ANN) with different ANN algorithms in a tropical climate. Three ANN algorithms namely, Levenberg-Marquardt, Bayesian Regularization and Scaled Conjugate Gradient are used in the short-term weather forecasting model. The study focuses on the data from North-West Malaysia (Chuping). Meteorological data such as atmospheric pressure, temperature, dew point, humidity and wind speed are used...

  3. Bayesian flood forecasting methods: A review

    Science.gov (United States)

    Han, Shasha; Coulibaly, Paulin

    2017-08-01

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

  4. Introducing Government Contracts to Technology Forecasting

    OpenAIRE

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

    2015-01-01

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

  5. Conducting and Evaluating Stakeholder Workshops to Facilitate Updates to a Storm Surge Forecasting Model for Coastal Louisiana

    Science.gov (United States)

    DeLorme, D.; Lea, K.; Hagen, S. C.

    2016-12-01

    As coastal Louisiana evolves morphologically, ecologically, and from engineering advancements, there is a crucial need to continually adjust real-time forecasting and coastal restoration planning models. This presentation discusses planning, conducting, and evaluating stakeholder workshops to support such an endeavor. The workshops are part of an ongoing Louisiana Sea Grant-sponsored project. The project involves updating an ADCIRC (Advanced Circulation) mesh representation of topography including levees and other flood control structures by applying previously-collected elevation data and new data acquired during the project. The workshops are designed to educate, solicit input, and ensure incorporation of topographic features into the framework is accomplished in the best interest of stakeholders. During this project's first year, three one-day workshops directed to levee managers and other local officials were convened at agricultural extension facilities in Hammond, Houma, and Lake Charles, Louisiana. The objectives were to provide a forum for participants to learn about the ADCIRC framework, understand the importance of accurate elevations for a robust surge model, discuss and identify additional data sources, and become familiar with the CERA (Coastal Emergency Risks Assessment) visualization tool. The workshop structure consisted of several scientific presentations with questions/answer time (ADCIRC simulation inputs and outputs; ADCIRC framework elevation component; description and examples of topographic features such as levees, roadways, railroads, etc. currently utilized in the mesh; ADCIRC model validation demonstration through historic event simulations; CERA demonstration), a breakout activity for participant groups to identify and discuss raised features not currently in the mesh and document them on provided worksheets, and a closing session for debriefing and discussion of future model improvements. Evaluation involved developing, and analyzing a

  6. IEA Wind Task 36 Forecasting

    Science.gov (United States)

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

    2017-04-01

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

  7. Reasonable Forecasts

    Science.gov (United States)

    Taylor, Kelley R.

    2010-01-01

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

  8. ERROR DISTRIBUTION EVALUATION OF THE THIRD VANISHING POINT BASED ON RANDOM STATISTICAL SIMULATION

    Directory of Open Access Journals (Sweden)

    C. Li

    2012-07-01

    Full Text Available POS, integrated by GPS / INS (Inertial Navigation Systems, has allowed rapid and accurate determination of position and attitude of remote sensing equipment for MMS (Mobile Mapping Systems. However, not only does INS have system error, but also it is very expensive. Therefore, in this paper error distributions of vanishing points are studied and tested in order to substitute INS for MMS in some special land-based scene, such as ground façade where usually only two vanishing points can be detected. Thus, the traditional calibration approach based on three orthogonal vanishing points is being challenged. In this article, firstly, the line clusters, which parallel to each others in object space and correspond to the vanishing points, are detected based on RANSAC (Random Sample Consensus and parallelism geometric constraint. Secondly, condition adjustment with parameters is utilized to estimate nonlinear error equations of two vanishing points (VX, VY. How to set initial weights for the adjustment solution of single image vanishing points is presented. Solving vanishing points and estimating their error distributions base on iteration method with variable weights, co-factor matrix and error ellipse theory. Thirdly, under the condition of known error ellipses of two vanishing points (VX, VY and on the basis of the triangle geometric relationship of three vanishing points, the error distribution of the third vanishing point (VZ is calculated and evaluated by random statistical simulation with ignoring camera distortion. Moreover, Monte Carlo methods utilized for random statistical estimation are presented. Finally, experimental results of vanishing points coordinate and their error distributions are shown and analyzed.

  9. Probabilistic forecasting of the solar irradiance with recursive ARMA and GARCH models

    DEFF Research Database (Denmark)

    David, M.; Ramahatana, F.; Trombe, Pierre-Julien

    2016-01-01

    sky index show some similarities with that of financial time series. The aim of this paper is to assess the performances of a commonly used combination of two linear models (ARMA and GARCH) in econometrics in order to provide probabilistic forecasts of solar irradiance. In addition, a recursive...... of the grid-connected storage systems. If numerous methods for forecasting the mean of the solar irradiance were recently developed, there are only few works dedicated to the evaluation of prediction intervals associated to these point forecasts. Time series of solar irradiance and more specifically of clear...

  10. Eight attention points when evaluating large-scale public sector reforms

    DEFF Research Database (Denmark)

    Hansen, Morten Balle; Breidahl, Karen Nielsen; Hjørdis Halvorsen, Anne

    2017-01-01

    of the central, regional and local government and a social policy reform. Meta-evaluations assess the usefulness of one or more evaluations and should not be confused with meta-analyses. The purpose of this meta-evaluation was to identify general principles for organizing the evaluations of large-scale public......This chapter analyses the challenges related to evaluations of large-scale public sector reforms. It is based on a meta-evaluation of the evaluation of the reform of the Norwegian Labour Market and Welfare Administration (the NAV-reform) in Norway, which entailed both a significant reorganization...... sector reforms. Based on the analysis, eight crucial points of attention when evaluating large-scale public sector reforms are elaborated. We discuss their reasons and argue that other countries will face the same challenges and thus can learn from the experiences of Norway....

  11. Evaluation of high-resolution forecasts with the non-hydrostaticnumerical weather prediction model Lokalmodell for urban air pollutionepisodes in Helsinki, Oslo and Valencia

    Directory of Open Access Journals (Sweden)

    B. Fay

    2006-01-01

    Full Text Available The operational numerical weather prediction model Lokalmodell LM with 7,km horizontal resolution was evaluated for forecasting meteorological conditions during observed urban air pollution episodes. The resolution was increased to experimental 2.8 km and 1.1 km resolution by one-way interactive nesting without introducing urbanisation of physiographic parameters or parameterisations. The episodes examined are two severe winter inversion-induced episodes in Helsinki in December 1995 and Oslo in January 2003, three suspended dust episodes in spring and autumn in Helsinki and Oslo, and a late-summer photochemical episode in the Valencia area. The evaluation was basically performed against observations and radiosoundings and focused on the LM skill at forecasting the key meteorological parameters characteristic for the specific episodes. These included temperature inversions, atmospheric stability and low wind speeds for the Scandinavian episodes and the development of mesoscale recirculations in the Valencia area. LM forecasts often improved due to higher model resolution especially in mountainous areas like Oslo and Valencia where features depending on topography like temperature, wind fields and mesoscale valley circulations were better described. At coastal stations especially in Helsinki, forecast gains were due to the improved physiographic parameters (land fraction, soil type, or roughness length. The Helsinki and Oslo winter inversions with extreme nocturnal inversion strengths of 18°C were not sufficiently predicted with all LM resolutions. In Helsinki, overprediction of surface temperatures and low-level wind speeds basically led to underpredicted inversion strength. In the Oslo episode, the situation was more complex involving erroneous temperature advection and mountain-induced effects for the higher resolutions. Possible explanations include the influence of the LM treatment of snow cover, sea ice and stability-dependence of transfer

  12. Advancing Data assimilation for Baltic Monitoring and Forecasting Center: implementation and evaluation of HBP-PDAF system

    Science.gov (United States)

    Korabel, Vasily; She, Jun; Huess, Vibeke; Woge Nielsen, Jacob; Murawsky, Jens; Nerger, Lars

    2017-04-01

    The potential of an efficient data assimilation (DA) scheme to improve model forecast skill was successfully demonstrated by many operational centres around the world. The Baltic-North Sea region is one of the most heavily monitored seas. Ferryboxes, buoys, ADCP moorings, shallow water Argo floats, and research vessels are providing more and more near-real time observations. Coastal altimetry has now providing increasing amount of high resolution sea level observations, which will be significantly expanded by the launch of SWOT satellite in next years. This will turn operational DA into a valuable tool for improving forecast quality in the region. This motivated us to focus on advancing DA for the Baltic Monitoring and Forecasting Centre (BAL MFC) in order to create a common framework for operational data assimilation in the Baltic Sea. We have implemented HBM-PDAF system based on the Parallel Data Assimilation Framework (PDAF), a highly versatile and optimised parallel suit with a choice of sequential schemes originally developed at AWI, and a hydrodynamic HIROMB-BOOS Model (HBM). At initial phase, only the satellite Sea Surface Temperature (SST) Level 3 data has been assimilated. Several related aspects are discussed, including improvements of the forecast quality for both surface and subsurface fields, the estimation of ensemble-based forecast error covariance, as well as possibilities of assimilating new types of observations, such as in-situ salinity and temperature profiles, coastal altimetry, and ice concentration.

  13. Forecast model for the evaluation of economic resources employed in the health care of patients with HIV infection

    Directory of Open Access Journals (Sweden)

    Sacchi P

    2012-05-01

    Full Text Available Paolo Sacchi1, Savino FA Patruno1, Raffaele Bruno1, Serena Maria Benedetta Cima1, Pietro Previtali2, Alessia Franchini2, Luca Nicolini3, Carla Rognoni4, Lucia Sacchi5, Riccardo Bellazzi4, Gaetano Filice11Divisione di Malattie Infettive e Tropicali - Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; 2Università degli Studi di Pavia – Facoltà di Economia, Pavia, Italy; 3Controllo di Gestione Fondazione IRCCS Policlinico San Matteo di Pavia, Pavia, Italy; 4Dipartimento di Informatica e Sistemistica, Universita' degli Studi di Pavia, Pavia, Italy; 5Department of Information Systems and Computing, Brunel University, London, UKBackground and aims: The total health care cost for human immunodeficiency virus (HIV patients has constantly grown in recent years. To date, there is no information about how this trend will behave over the next few years. The aim of the present study is to define a pharmacoeconomic model for the forecast of the costs of a group of chronically treated patients followed over the period 2004–2009.Methods: A pharmacoeconomics model was built to describe the probability of transition among different health states and to modify the therapy over time. A Markov model was applied to evaluate the temporal evolution of the average cost. The health care resources exploited during hospitalization were analyzed by using an “activity-based costing” method.Results: The Markov model showed that the mean total cost, after an initial increase, tended to remain stable. A total of 20 clinical records were examined. The average daily cost for each patient was EUR 484.42, with a cost for admission of EUR 6781.88.Conclusion: The treatment of HIV infection in compliance with the guidelines is also effective from the payer perspective, as it allows a good health condition to be maintained and reduces the need and the costs of hospitalizations.Keywords: health care cost, HIV, Markov model, activity-based costing

  14. Short-Term Wind Power Interval Forecasting Based on an EEMD-RT-RVM Model

    OpenAIRE

    Haixiang Zang; Lei Fan; Mian Guo; Zhinong Wei; Guoqiang Sun; Li Zhang

    2016-01-01

    Accurate short-term wind power forecasting is important for improving the security and economic success of power grids. Existing wind power forecasting methods are mostly types of deterministic point forecasting. Deterministic point forecasting is vulnerable to forecasting errors and cannot effectively deal with the random nature of wind power. In order to solve the above problems, we propose a short-term wind power interval forecasting model based on ensemble empirical mode decomposition (EE...

  15. Evaluating 5 and 8 pH-point titrations for measuring VFA in full-scale ...

    African Journals Online (AJOL)

    2012-02-24

    Feb 24, 2012 ... An evaluation of 5 and 8 pH-point titrimetric methods for determining volatile fatty acids (VFAs) was conducted, and the results were compared for tap water and primary treated wastewater at the laboratory scale. These techniques were then applied to full-scale primary sludge hydrolysate, and the results ...

  16. Discrete Model Predictive Control-Based Maximum Power Point Tracking for PV Systems: Overview and Evaluation

    DEFF Research Database (Denmark)

    Lashab, Abderezak; Sera, Dezso; Guerrero, Josep M.

    2018-01-01

    The main objective of this work is to provide an overview and evaluation of discrete model predictive controlbased maximum power point tracking (MPPT) for PV systems. A large number of MPC based MPPT methods have been recently introduced in the literature with very promising performance, however...

  17. Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE)

    DEFF Research Database (Denmark)

    Vestbo, J; Anderson, W; Coxson, H O

    2008-01-01

    . Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE) is a 3-yr longitudinal study with four specific aims: 1) definition of clinically relevant COPD subtypes; 2) identification of parameters that predict disease progression in these subtypes; 3) examination of biomarkers...

  18. Forecasting Brassica rapa: Merging climate models with genotype specific process models for evaluation whole species response to climate change.

    Science.gov (United States)

    Pleban, J. R.; Mackay, D. S.; Ewers, B. E.; Weinig, C.; Guadagno, C. L.

    2016-12-01

    Human society has modified agriculture management practices and utilized a variety of breeding approaches to adapt to changing environments. Presently a dual pronged challenge has emerged as environmental change is occurring more rapidly while the demand of population growth on food supply is rising. Knowledge of how current agricultural practices will respond to these challenges can be informed through crafted prognostic modeling approaches. Amongst the uncertainties associated with forecasting agricultural production in a changing environment is evaluation of the responses across the existing genotypic diversity of crop species. Mechanistic models of plant productivity provide a means of genotype level parameterization allowing for a prognostic evaluation of varietal performance under changing climate. Brassica rapa represents an excellent species for this type of investigation because of its wide cultivation as well as large morphological and physiological diversity. We incorporated genotypic parameterization of B. rapa genotypes based on unique CO2 assimilation strategies, vulnerabilities to cavitation, and root to leaf area relationships into the TREES model. Three climate drivers, following the "business-as-usual" greenhouse gas emissions scenario (RCP 8.5) from Coupled Model Intercomparison Project, Phase 5 (CMIP5) were considered: temperature (T) along with associated changes in vapor pressure deficit (VPD), increasing CO2, as well as alternatives in irrigation regime across a temporal scale of present day to 2100. Genotypic responses to these drivers were evaluated using net primary productivity (NPP) and percent loss hydraulic conductance (PLC) as a measure of tolerance for a particular watering regime. Genotypic responses to T were witnessed as water demand driven by increases in VPD at 2050 and 2100 drove some genotypes to greater PLC and in a subset of these saw periodic decreases in NPP during a growing season. Genotypes able to withstand the greater

  19. Seasonal Streamflow Forecasts for African Basins

    Science.gov (United States)

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

    2015-12-01

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

  20. Gambling scores for earthquake predictions and forecasts

    Science.gov (United States)

    Zhuang, Jiancang

    2010-04-01

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

  1. Evaluation of the possibility of forecasting the displacements of the Solina Dam based on observation of the feeler gauges

    Directory of Open Access Journals (Sweden)

    Bąk Aleksandra

    2016-01-01

    Full Text Available These studies are the continuation of previously conducted researches based on displacements of the Solina Dam. To support the monitoring of the dam, the EDF model were used. This model determines the dependence between displacements observed on the elements of the dam and the level of the upper water, cyclicality of temperatures and the impact of time. The use of model, in both the imaging of displacements of the Solina Dam and forecasts made for the benchmarks located on the crest of the dam, gave satisfactory results, therefore further analysis were undertaken. Displacement forecasting was made based on data from feeler gauges located at the pillars, retaining walls and four galleries. Analysis based on 4 different forecasting periods enabled for the conclusion that to obtain reliable forecasts, measurement data based on 10 years of operation with frequency of 1 per month is required. The use of such a comprehensive database allowed for the achievement of full compliance between modelled values and observed displacements within the established confidence intervals.

  2. Evaluating weather research and forecasting (WRF) model predictions of turbulent flow parameters in a dry convective boundary layer

    NARCIS (Netherlands)

    Gibbs, J.A.; Fedorovich, E.; Eijk, A.M.J. van

    2011-01-01

    Weather Research and Forecasting (WRF) model predictions using different boundary layer schemes and horizontal grid spacings were compared with observational and numerical large-eddy simulation data for conditions corresponding to a dry atmospheric convective boundary layer (CBL) over the southern

  3. Evaluating Physical Processes during the Freeze-Up Season using a Coupled Sea Ice-Ocean-Atmosphere Forecast Model

    Science.gov (United States)

    Solomon, Amy; Intrieri, Janet; Persson, Ola; Cox, Christopher; Hughes, Mimi; Grachev, Andrey; Capotondi, Antonietta; de Boer, Gijs

    2017-04-01

    Improved sea ice forecasting must be based on improved model representation of coupled system processes that impact the sea ice thermodynamic and dynamic state. Pertinent coupled system processes remain uncertain and include surface energy fluxes, clouds, precipitation, boundary layer structure, momentum transfer and sea-ice dynamics, interactions between large-scale circulation and local processes, and others. In this presentation, we use a fully-coupled ocean-sea ice-atmosphere forecast system as a testbed for investigating biases in 0-10 day forecasts, with a focus on processes that determine fluxes at the ocean-ice-air interface. Model results and validation examples from an experimental, weather-scale, coupled ice-ocean-atmosphere model for 2015 and 2016 fall, sea ice freeze-up season will be presented. The model, a limited-area, fully-coupled atmosphere-ice-ocean model (named, RASM-ESRL), was developed from the larger-scale Regional Arctic System Model (RASM) architecture. RASM-ESRL includes the Weather Research and Forecasting (WRF) atmospheric model, Parallel Ocean Program (POP2) model, Community Ice Model (CICE5) and the NCAR Community Land Model. The domain is limited to the Arctic and all components are run with 10 km horizontal resolution. Components are coupled using a regionalized version of the CESM flux coupler (CPL7), which includes modifications important for resolving the sea ice pack's inertial response to transient (i.e. weather) events. The model is initialized with a GFS atmosphere, satellite-derived sea ice analyses using AMSR-2, and forced by 3-hourly GFS forecasts at the lateral boundaries. Experimental forecasts were run daily from late-July through mid-November in 2015 and 2016. These daily forecasts have been compared with observations of surface fluxes and vertical atmospheric profiles at the International Arctic Systems for Observing the Atmosphere (IASOA) stations, and with atmospheric and oceanic observations obtained within the sea

  4. A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets

    Energy Technology Data Exchange (ETDEWEB)

    Castillo, Richard [Department of Imaging Physics, University of Texas M. D. Anderson Cancer Center, Houston, TX (United States); Castillo, Edward [Department of Mathematics, University of California, Irvine, CA (United States); Guerra, Rudy [Department of Statistics, Rice University, Houston, TX (United States); Johnson, Valen E [Department of Biostatistics and Applied Mathematics, University of Texas M. D. Anderson Cancer Center, Houston, TX (United States); McPhail, Travis [Department of Computer Science, Rice University, Houston, TX (United States); Garg, Amit K; Guerrero, Thomas [Department of Radiation Oncology, University of Texas M. D. Anderson Cancer Center, Houston, TX (United States)], E-mail: tguerrero@mdanderson.org

    2009-04-07

    Expert landmark correspondences are widely reported for evaluating deformable image registration (DIR) spatial accuracy. In this report, we present a framework for objective evaluation of DIR spatial accuracy using large sets of expert-determined landmark point pairs. Large samples (>1100) of pulmonary landmark point pairs were manually generated for five cases. Estimates of inter- and intra-observer variation were determined from repeated registration. Comparative evaluation of DIR spatial accuracy was performed for two algorithms, a gradient-based optical flow algorithm and a landmark-based moving least-squares algorithm. The uncertainty of spatial error estimates was found to be inversely proportional to the square root of the number of landmark point pairs and directly proportional to the standard deviation of the spatial errors. Using the statistical properties of this data, we performed sample size calculations to estimate the average spatial accuracy of each algorithm with 95% confidence intervals within a 0.5 mm range. For the optical flow and moving least-squares algorithms, the required sample sizes were 1050 and 36, respectively. Comparative evaluation based on fewer than the required validation landmarks results in misrepresentation of the relative spatial accuracy. This study demonstrates that landmark pairs can be used to assess DIR spatial accuracy within a narrow uncertainty range.

  5. Evaluation of the performance of a meso-scale NWP model to forecast solar irradiance on Reunion Island for photovoltaic power applications

    Science.gov (United States)

    Kalecinski, Natacha; Haeffelin, Martial; Badosa, Jordi; Periard, Christophe

    2013-04-01

    Solar photovoltaic power is a predominant source of electrical power on Reunion Island, regularly providing near 30% of electrical power demand for a few hours per day. However solar power on Reunion Island is strongly modulated by clouds in small temporal and spatial scales. Today regional regulations require that new solar photovoltaic plants be combined with storage systems to reduce electrical power fluctuations on the grid. Hence cloud and solar irradiance forecasting becomes an important tool to help optimize the operation of new solar photovoltaic plants on Reunion Island. Reunion Island, located in the South West of the Indian Ocean, is exposed to persistent trade winds, most of all in winter. In summer, the southward motion of the ITCZ brings atmospheric instabilities on the island and weakens trade winds. This context together with the complex topography of Reunion Island, which is about 60 km wide, with two high summits (3070 and 2512 m) connected by a 1500 m plateau, makes cloudiness very heterogeneous. High cloudiness variability is found between mountain and coastal areas and between the windward, leeward and lateral regions defined with respect to the synoptic wind direction. A detailed study of local dynamics variability is necessary to better understand cloud life cycles around the island. In the presented work, our approach to explore the short-term solar irradiance forecast at local scales is to use the deterministic output from a meso-scale numerical weather prediction (NWP) model, AROME, developed by Meteo France. To start we evaluate the performance of the deterministic forecast from AROME by using meteorological measurements from 21 meteorological ground stations widely spread around the island (and with altitudes from 8 to 2245 m). Ground measurements include solar irradiation, wind speed and direction, relative humidity, air temperature, precipitation and pressure. Secondly we study in the model the local dynamics and thermodynamics that

  6. Evaluation of maximum power point tracking in hydrokinetic energy conversion systems

    Directory of Open Access Journals (Sweden)

    Jahangir Khan

    2015-11-01

    Full Text Available Maximum power point tracking is a mature control issue for wind, solar and other systems. On the other hand, being a relatively new technology, detailed discussion on power tracking of hydrokinetic energy conversion systems are generally not available. Prior to developing sophisticated control schemes for use in hydrokinetic systems, existing know-how in wind or solar technologies can be explored. In this study, a comparative evaluation of three generic classes of maximum power point scheme is carried out. These schemes are (a tip speed ratio control, (b power signal feedback control, and (c hill climbing search control. In addition, a novel concept for maximum power point tracking: namely, extremum seeking control is introduced. Detailed and validated system models are used in a simulation environment. Potential advantages and drawbacks of each of these schemes are summarised.

  7. Forecasting longitudinal changes in oropharyngeal tumor morphology throughout the course of head and neck radiation therapy.

    Science.gov (United States)

    Yock, Adam D; Rao, Arvind; Dong, Lei; Beadle, Beth M; Garden, Adam S; Kudchadker, Rajat J; Court, Laurence E

    2014-08-01

    To create models that forecast longitudinal trends in changing tumor morphology and to evaluate and compare their predictive potential throughout the course of radiation therapy. Two morphology feature vectors were used to describe 35 gross tumor volumes (GTVs) throughout the course of intensity-modulated radiation therapy for oropharyngeal tumors. The feature vectors comprised the coordinates of the GTV centroids and a description of GTV shape using either interlandmark distances or a spherical harmonic decomposition of these distances. The change in the morphology feature vector observed at 33 time points throughout the course of treatment was described using static, linear, and mean models. Models were adjusted at 0, 1, 2, 3, or 5 different time points (adjustment points) to improve prediction accuracy. The potential of these models to forecast GTV morphology was evaluated using leave-one-out cross-validation, and the accuracy of the models was compared using Wilcoxon signed-rank tests. Adding a single adjustment point to the static model without any adjustment points decreased the median error in forecasting the position of GTV surface landmarks by the largest amount (1.2 mm). Additional adjustment points further decreased the forecast error by about 0.4 mm each. Selection of the linear model decreased the forecast error for both the distance-based and spherical harmonic morphology descriptors (0.2 mm), while the mean model decreased the forecast error for the distance-based descriptor only (0.2 mm). The magnitude and statistical significance of these improvements decreased with each additional adjustment point, and the effect from model selection was not as large as that from adding the initial points. The authors present models that anticipate longitudinal changes in tumor morphology using various models and model adjustment schemes. The accuracy of these models depended on their form, and the utility of these models includes the characterization of patient

  8. Forecasting longitudinal changes in oropharyngeal tumor morphology throughout the course of head and neck radiation therapy

    Science.gov (United States)

    Yock, Adam D.; Rao, Arvind; Dong, Lei; Beadle, Beth M.; Garden, Adam S.; Kudchadker, Rajat J.; Court, Laurence E.

    2014-01-01

    Purpose: To create models that forecast longitudinal trends in changing tumor morphology and to evaluate and compare their predictive potential throughout the course of radiation therapy. Methods: Two morphology feature vectors were used to describe 35 gross tumor volumes (GTVs) throughout the course of intensity-modulated radiation therapy for oropharyngeal tumors. The feature vectors comprised the coordinates of the GTV centroids and a description of GTV shape using either interlandmark distances or a spherical harmonic decomposition of these distances. The change in the morphology feature vector observed at 33 time points throughout the course of treatment was described using static, linear, and mean models. Models were adjusted at 0, 1, 2, 3, or 5 different time points (adjustment points) to improve prediction accuracy. The potential of these models to forecast GTV morphology was evaluated using leave-one-out cross-validation, and the accuracy of the models was compared using Wilcoxon signed-rank tests. Results: Adding a single adjustment point to the static model without any adjustment points decreased the median error in forecasting the position of GTV surface landmarks by the largest amount (1.2 mm). Additional adjustment points further decreased the forecast error by about 0.4 mm each. Selection of the linear model decreased the forecast error for both the distance-based and spherical harmonic morphology descriptors (0.2 mm), while the mean model decreased the forecast error for the distance-based descriptor only (0.2 mm). The magnitude and statistical significance of these improvements decreased with each additional adjustment point, and the effect from model selection was not as large as that from adding the initial points. Conclusions: The authors present models that anticipate longitudinal changes in tumor morphology using various models and model adjustment schemes. The accuracy of these models depended on their form, and the utility of these models

  9. Forecasting longitudinal changes in oropharyngeal tumor morphology throughout the course of head and neck radiation therapy

    Energy Technology Data Exchange (ETDEWEB)

    Yock, Adam D.; Kudchadker, Rajat J. [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States); Rao, Arvind [Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States); Dong, Lei [Scripps Proton Therapy Center, San Diego, California 92121 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States); Beadle, Beth M.; Garden, Adam S. [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States); Court, Laurence E., E-mail: LECourt@MDAnderson.org [Department of Radiation Physics and Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States)

    2014-08-15

    Purpose: To create models that forecast longitudinal trends in changing tumor morphology and to evaluate and compare their predictive potential throughout the course of radiation therapy. Methods: Two morphology feature vectors were used to describe 35 gross tumor volumes (GTVs) throughout the course of intensity-modulated radiation therapy for oropharyngeal tumors. The feature vectors comprised the coordinates of the GTV centroids and a description of GTV shape using either interlandmark distances or a spherical harmonic decomposition of these distances. The change in the morphology feature vector observed at 33 time points throughout the course of treatment was described using static, linear, and mean models. Models were adjusted at 0, 1, 2, 3, or 5 different time points (adjustment points) to improve prediction accuracy. The potential of these models to forecast GTV morphology was evaluated using leave-one-out cross-validation, and the accuracy of the models was compared using Wilcoxon signed-rank tests. Results: Adding a single adjustment point to the static model without any adjustment points decreased the median error in forecasting the position of GTV surface landmarks by the largest amount (1.2 mm). Additional adjustment points further decreased the forecast error by about 0.4 mm each. Selection of the linear model decreased the forecast error for both the distance-based and spherical harmonic morphology descriptors (0.2 mm), while the mean model decreased the forecast error for the distance-based descriptor only (0.2 mm). The magnitude and statistical significance of these improvements decreased with each additional adjustment point, and the effect from model selection was not as large as that from adding the initial points. Conclusions: The authors present models that anticipate longitudinal changes in tumor morphology using various models and model adjustment schemes. The accuracy of these models depended on their form, and the utility of these models

  10. The Oil Point Method - A tool for indicative environmental evaluation in material and process selection

    DEFF Research Database (Denmark)

    Bey, Niki

    2000-01-01

    to three essential assessment steps, the method enables rough environmental evaluations and supports in this way material- and process-related decision-making in the early stages of design. In its overall structure, the Oil Point Method is related to Life Cycle Assessment - except for two main differences...... industrial activity world-wide - makes it increasingly evident that our current way of life is not sustainable. A major contribution of society's negative impact on the environment is related to industrial products and the processes during their life cycle, from raw materials extraction over manufacturing...... of environmental evaluation and only approximate information about the product and its life cycle. This dissertation addresses this challenge in presenting a method, which is tailored to these requirements of designers - the Oil Point Method (OPM). In providing environmental key information and confining itself...

  11. Using Wireless Handheld Computers to Seek Information at the Point of Care: An Evaluation by Clinicians

    Science.gov (United States)

    Hauser, Susan E.; Demner-Fushman, Dina; Jacobs, Joshua L.; Humphrey, Susanne M.; Ford, Glenn; Thoma, George R.

    2007-01-01

    Objective To evaluate: (1) the effectiveness of wireless handheld computers for online information retrieval in clinical settings; (2) the role of MEDLINE® in answering clinical questions raised at the point of care. Design A prospective single-cohort study: accompanying medical teams on teaching rounds, five internal medicine residents used and evaluated MD on Tap, an application for handheld computers, to seek answers in real time to clinical questions arising at the point of care. Measurements All transactions were stored by an intermediate server. Evaluators recorded clinical scenarios and questions, identified MEDLINE citations that answered the questions, and submitted daily and summative reports of their experience. A senior medical librarian corroborated the relevance of the selected citation to each scenario and question. Results Evaluators answered 68% of 363 background and foreground clinical questions during rounding sessions using a variety of MD on Tap features in an average session length of less than four minutes. The evaluator, the number and quality of query terms, the total number of citations found for a query, and the use of auto-spellcheck significantly contributed to the probability of query success. Conclusion Handheld computers with Internet access are useful tools for healthcare providers to access MEDLINE in real time. MEDLINE citations can answer specific clinical questions when several medical terms are used to form a query. The MD on Tap application is an effective interface to MEDLINE in clinical settings, allowing clinicians to quickly find relevant citations. PMID:17712085

  12. Statistical Correction of Air Temperature Forecasts for City and Road Weather Applications

    Science.gov (United States)

    Mahura, Alexander; Petersen, Claus; Sass, Bent; Gilet, Nicolas

    2014-05-01

    that the CPU time required for the operational procedure is relatively short (less than 15 minutes including a large time spent for interpolation). These also showed that in order to start correction of forecasts there is no need to have a long-term pre-historical data (containing forecasts and observations) and, at least, a couple of weeks will be sufficient when a new observational station is included and added to the forecast point. Note for the road weather application, the operationalization of the statistical correction of the road surface temperature forecasts (for the RWM system daily hourly runs covering forecast length up to 5 hours ahead) for the Danish road network (for about 400 road stations) was also implemented, and it is running in a test mode since Sep 2013. The method can also be applied for correction of the dew point temperature and wind speed (as a part of observations/ forecasts at synoptical stations), where these both meteorological parameters are parts of the proposed system of equations. The evaluation of the method performance for improvement of the wind speed forecasts is planned as well, with considering possibilities for the wind direction improvements (which is more complex due to multi-modal types of such data distribution). The method worked for the entire domain of mainland Denmark (tested for 60 synoptical and 395 road stations), and hence, it can be also applied for any geographical point within this domain, as through interpolation to about 100 cities' locations (for Danish national byvejr forecasts). Moreover, we can assume that the same method can be used in other geographical areas. The evaluation for other domains (with a focus on Greenland and Nordic countries) is planned. In addition, a similar approach might be also tested for statistical correction of concentrations of chemical species, but such approach will require additional elaboration and evaluation.

  13. A Forecast Model for Unemployment by Education

    DEFF Research Database (Denmark)

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

    1994-01-01

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

  14. Evaluation of real time and future global monitoring and forecasting systems at Mercator Océan

    Science.gov (United States)

    Lellouche, J.-M.; Le Galloudec, O.; Drévillon, M.; Régnier, C.; Greiner, E.; Garric, G.; Ferry, N.; Desportes, C.; Testut, C.-E.; Bricaud, C.; Bourdallé-Badie, R.; Tranchant, B.; Benkiran, M.; Drillet, Y.; Daudin, A.; de Nicola, C.

    2012-03-01

    Since December 2010, the global analysis and forecast of the MyOcean system consists in the Mercator Océan NEMO global 1/4° configuration with a 1/12° "zoom" over the Atlantic and Mediterranean Sea. The zoom open boundaries come from the global 1/4° at 20° S and 80° N. The data assimilation uses a reduced order Kalman filter with a 3-D multivariate modal decomposition of the forecast error. It includes an adaptative error and a localization algorithm. A 3D-Var scheme corrects for the slowly evolving large-scale biases in temperature and salinity. Altimeter data, satellite temperature and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions for the numerical ocean forecasting. This paper gives a description of the recent systems. The validation procedure is introduced and applied to the current and future systems. This paper shows how the validation impacts on the quality of the systems. It is shown how quality check (in situ, drifters) and data source (satellite temperature) impacts as much as the systems design (model physics and assimilation parameters). The validation demonstrates the accuracy of the MyOcean global products. Their quality is stable in time. The future systems under development still suffer from a drift. This could only be detected with a 5 yr hindcast of the systems. This emphasizes the need for continuous research efforts in the process of building future versions of MyOcean2 forecasting capacities.

  15. Energy and economic evaluation of policies for accelerated investment in efficient automobiles. [Jack Faucett Automobile Sector Forecasting Model

    Energy Technology Data Exchange (ETDEWEB)

    Brooks, Walter; Carhart, Steven C.; McGranahan, Gordon; Mulherkar, Shirish S.

    1978-08-01

    This report examines the effect of an energy-conservation policy that imposes excise taxes on cars having low fuel efficiency, coupled with a rebate on cars having high fuel efficiency. Two oil price cases are considered. The Jack Faucett Automobile Sector Forecasting Model is used to measure direct effects. The Brookhaven National Laboratory-University of Illinois Input-Output/Linear Programming model is used for economy-wide effects and impact on employment.

  16. pawg Terminal Aerodrome Forecast

    Data.gov (United States)

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

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    Data.gov (United States)

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

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

  19. kden 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. kmgm 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. kswf 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...

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    Data.gov (United States)

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

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    Data.gov (United States)

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

  4. khot Terminal Aerodrome Forecast

    Data.gov (United States)

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

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    Data.gov (United States)

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

  6. krdd 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. kabq 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. klax 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. krut 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. kpvu 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. pagy 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. 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...

  13. khya 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. phog 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. kpeq 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. keko 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. pail 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. kelp Terminal Aerodrome Forecast

    Data.gov (United States)

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

  19. kdab 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. keld 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. 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...

  2. paom 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. 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...

  4. ktix Terminal Aerodrome Forecast

    Data.gov (United States)

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

  5. kpln 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. kgag 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. kbuf 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. ptkk 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. klyh 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. kslc 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. kabe 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. pahn Terminal Aerodrome Forecast

    Data.gov (United States)

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

  13. kbvo 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. kfoe 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. kbff Terminal Aerodrome Forecast

    Data.gov (United States)

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

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    Data.gov (United States)

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

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    Data.gov (United States)

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

  18. kals 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. kgrb 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...

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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. kgso 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. khlg 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. kjan 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. kbce 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. ktys 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. kcha 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. kdug Terminal Aerodrome Forecast

    Data.gov (United States)

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

  8. kpub 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. ksrq Terminal Aerodrome Forecast

    Data.gov (United States)

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

  10. kaeg 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. pata 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. klgu 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. kmsl 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. kbrl 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. ksfb 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. kpsc 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. kely 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. ksyr 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. katw 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. kama 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. kpae 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. kmli 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. kokc 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. kjst 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. kgup 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. padl 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. klit 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. kalb Terminal Aerodrome Forecast

    Data.gov (United States)

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

  10. kact 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. kink Terminal Aerodrome Forecast

    Data.gov (United States)

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

  12. kshv 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. pajn 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. kpna Terminal Aerodrome Forecast

    Data.gov (United States)

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

  15. ktph 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. ksux 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. kcon 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. khio 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. konp Terminal Aerodrome Forecast

    Data.gov (United States)

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

  20. kpnc 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. kmlu Terminal Aerodrome Forecast

    Data.gov (United States)

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

  2. kgsp Terminal Aerodrome Forecast

    Data.gov (United States)

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

  3. kgpt Terminal Aerodrome Forecast

    Data.gov (United States)

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

  4. 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...

  5. keri Terminal Aerodrome Forecast

    Data.gov (United States)

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

  6. kcid Terminal Aerodrome Forecast

    Data.gov (United States)

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

  7. ksaf Terminal Aerodrome Forecast

    Data.gov (United States)

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

  8. kcvg 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. ptya Terminal Aerodrome Forecast

    Data.gov (United States)

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

  10. katl Terminal Aerodrome Forecast

    Data.gov (United States)

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

  11. kmth Terminal Aerodrome Forecast

    Data.gov (United States)

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

  12. Developing and using a rubric for evaluating evidence-based medicine point-of-care tools.

    Science.gov (United States)

    Shurtz, Suzanne; Foster, Margaret J

    2011-07-01

    The research sought to establish a rubric for evaluating evidence-based medicine (EBM) point-of-care tools in a health sciences library. The authors searched the literature for EBM tool evaluations and found that most previous reviews were designed to evaluate the ability of an EBM tool to answer a clinical question. The researchers' goal was to develop and complete rubrics for assessing these tools based on criteria for a general evaluation of tools (reviewing content, search options, quality control, and grading) and criteria for an evaluation of clinical summaries (searching tools for treatments of common diagnoses and evaluating summaries for quality control). Differences between EBM tools' options, content coverage, and usability were minimal. However, the products' methods for locating and grading evidence varied widely in transparency and process. As EBM tools are constantly updating and evolving, evaluation of these tools needs to be conducted frequently. Standards for evaluating EBM tools need to be established, with one method being the use of objective rubrics. In addition, EBM tools need to provide more information about authorship, reviewers, methods for evidence collection, and grading system employed.

  13. Effective Feature Preprocessing for Time Series Forecasting

    DEFF Research Database (Denmark)

    Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

    2006-01-01

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

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

    Science.gov (United States)

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

    2016-12-01

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

  15. A Robust Multimodel Framework for Ensemble Seasonal Hydroclimatic Forecasts

    Science.gov (United States)

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

    2014-12-01

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

  16. Combined time-varying forecast based on the proper scoring approach for wind power generation

    DEFF Research Database (Denmark)

    Chen, Xingying; Jiang, Yu; Yu, Kun

    2017-01-01

    Compared with traditional point forecasts, combined forecast have been proposed as an effective method to provide more accurate forecasts than individual model. However, the literature and research focus on wind-power combined forecasts are relatively limited. Here, based on forecasting error dis...... demonstrate that the proposed method improves the accuracy of overall forecasts, even compared with a numerical weather prediction.......Compared with traditional point forecasts, combined forecast have been proposed as an effective method to provide more accurate forecasts than individual model. However, the literature and research focus on wind-power combined forecasts are relatively limited. Here, based on forecasting error...... distribution, a proper scoring approach is applied to combine plausible models to form an overall time-varying model for the next day forecasts, rather than weights-based combination. To validate the effectiveness of the proposed method, real data of 3 years were used for testing. Simulation results...

  17. [Evaluation of a new blood gas analysis system: RapidPoint 500(®)].

    Science.gov (United States)

    Nicolas, Thierry; Cabrolier, Nadège; Bardonnet, Karine; Davani, Siamak

    2013-01-01

    We present here evaluation of a new blood gas analysis system, RapidPoint 500(®) (Siemens Healthcare Diagnostics). The aim of this research was to compare the ergonomics and analytical performances of this analyser with those of the RapidLab 1265 for the following parameters: pH, partial oxygen pressure, partial carbon dioxide pressure, sodium, potassium, ionized calcium, lactate and the CO-oximetry parameters: hemoglobin, oxyhemoglobin, carboxyhemoglobin, methemoglobin, reduced hemoglobin, neonatal bilirubin; as well as with the Dimension Vista 500 results for chloride and glucose. The Valtec protocol, recommended by the French Society of Clinical Biology (SFBC), was used to analyze the study results. The experiment was carried out over a period of one month in the Department of medical biochemistry. One hundred sixty five samples from adult patients admitted to the ER or hospitalized in intensive care were tested. The RapidPoint 500(®) was highly satisfactory from an ergonomic point of view. Intra-and inter- assay coefficients of variation (CV) with the three control levels were below those recommended by the SFBC for all parameters, and the comparative study gave coefficients of determination higher than 0.91. Taken together, the RapidPoint 500(®) appears fully satisfactory in terms of ergonomics and analytical performance.

  18. Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications

    Directory of Open Access Journals (Sweden)

    Abdulla Al-Rawabdeh

    2017-10-01

    Full Text Available Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research.

  19. Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications.

    Science.gov (United States)

    Al-Rawabdeh, Abdulla; Moussa, Adel; Foroutan, Marzieh; El-Sheimy, Naser; Habib, Ayman

    2017-10-18

    Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research.

  20. How to Improve the SPF Forecasts?

    Directory of Open Access Journals (Sweden)

    Bratu (Simionescu Mihaela

    2013-04-01

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

  1. Creating the Data Basis for Environmental Evaluations with the Oil Point Method

    DEFF Research Database (Denmark)

    Bey, Niki; Lenau, Torben Anker

    1999-01-01

    it is the case with rules-of-thumb. The central idea is that missing indicators can be calculated or estimated by the designers themselves.After discussing energy-related environmental evaluation and arguing for its application in evaluation of concepts, the paper focuses on the basic problem of missing data...... and describes the way in which the problem may be solved by making Oil Point evaluations. Sources of energy data are mentioned. Typical deficits to be aware of - such as the negligence of efficiency factors - are revealed and discussed. Comparative case studies which have shown encouraging results are mentioned......In order to support designers in decision-making, some methods have been developed which are based on environmental indicators. These methods, however, can only be used, if indicators for the specific product concept exist and are readily available.Based on this situation, the authors developed...

  2. Day-Ahead Wind Power Forecasting Using a Two-Stage Hybrid Modeling Approach Based on SCADA and Meteorological Information, and Evaluating the Impact of Input-Data Dependency on Forecasting Accuracy

    Directory of Open Access Journals (Sweden)

    Dehua Zheng

    2017-12-01

    Full Text Available The power generated by wind generators is usually associated with uncertainties, due to the intermittency of wind speed and other weather variables. This creates a big challenge for transmission system operators (TSOs and distribution system operators (DSOs in terms of connecting, controlling and managing power networks with high-penetration wind energy. Hence, in these power networks, accurate wind power forecasts are essential for their reliable and efficient operation. They support TSOs and DSOs in enhancing the control and management of the power network. In this paper, a novel two-stage hybrid approach based on the combination of the Hilbert-Huang transform (HHT, genetic algorithm (GA and artificial neural network (ANN is proposed for day-ahead wind power forecasting. The approach is composed of two stages. The first stage utilizes numerical weather prediction (NWP meteorological information to predict wind speed at the exact site of the wind farm. The second stage maps actual wind speed vs. power characteristics recorded by SCADA. Then, the wind speed forecast in the first stage for the future day is fed to the second stage to predict the future day’s wind power. Comparative selection of input-data parameter sets for the forecasting model and impact analysis of input-data dependency on forecasting accuracy have also been studied. The proposed approach achieves significant forecasting accuracy improvement compared with three other artificial intelligence-based forecasting approaches and a benchmark model using the smart persistence method.

  3. An evaluation of fall speed characteristics in bin and bulk microphysical schemes and use of bin fall speeds to improve forecasts of warm-season rainfall

    Science.gov (United States)

    Aligo, Eric A.

    2011-12-01

    evaluated. First, various tests were performed with various microphysical schemes and cases in order to find the vertical grid configuration that provides the best rainfall forecast. Rainfall forecasts worsened when the number of vertical levels was doubled from a control configuration of 31 levels and an over prediction of rainfall occurred. The largest improvement in skill occurred when the levels above the melting level were doubled and this was attributed to better resolved cold-cloud microphysical processes. As such, simulations using the probability matching technique employed the vertical configuration with refined vertical grid resolution above the melting layer. The different convective morphologies responded similarly when the fall speed modifications were made with all systems simulating a narrower stratiform region, less stratiform rainfall and a larger anvil. Rainfall forecasts generally improved with the use of the probability matching technique with improvements in the lightest and heaviest rainfall. The reduced stratiform rainfall occurred as a result of slower falling snow and a reduction in downward fluxes of snow, while forecasts of convective rainfall intensity improved as a result of faster falling graupel. Sensitivity tests were performed by computing bulk-like fall speeds in the bin scheme, which resulted in a modification of the particle size distribution of snow, which led to faster falling snow, larger downward fluxes of snow and a larger stratiform rain region.

  4. Evaluation of various Deformable Image Registrations for Point and Volume Variations

    CERN Document Server

    Han, Su Chul; Park, Seungwoo; Lee, Soon Sung; Jung, Haijo; Kim, Mi-Sook; Yoo, Hyung Jun; Ji, Young Hoon; Yi, Chul Young; Kim, Kum Bae

    2015-01-01

    The accuracy of deformable image registration (DIR) has a significant dosimetric impact in radiation treatment planning. We evaluated accuracy of various DIR algorithms using variations of the deformation point and volume. The reference image (Iref) and volume (Vref) was first generated with virtual deformation QA software (ImSimQA, Oncology System Limited, UK). We deformed Iref with axial movement of deformation point and Vref depending on the types of deformation that are the deformation1 is to increase the Vref (relaxation) and the deformation 2 is to decrease . The deformed image (Idef) and volume (Vdef) acquired by ImSimQA software were inversely deformed to Iref and Vref using DIR algorithms. As a result, we acquired deformed image (Iid) from Idef and volume (Vid) from Vdef. The DIR algorithms were the Horn Schunk optical flow (HS), Iterative Optical Flow (IOF), Modified Demons (MD) and Fast Demons (FD) with the Deformable Image Registration and Adaptive Radiotherapy Toolkit (DIRART) of MATLAB. The imag...

  5. Forecasting In One-Dimensional And Generalized Integrated ...

    African Journals Online (AJOL)

    In this paper, forecast of one-dimensional integrated autoregressive bilinear is compared with forecast of generalized integrated autoregressive bilinear model. We describe the method for estimation of these models and the forecast. It is also pointed out that for this class of non-linear time series models; it is possible to ...

  6. Load forecasting of supermarket refrigeration

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  7. Weather forecast

    CERN Document Server

    Courtier, P

    1994-02-07

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

  8. Forecasting Turbine Icing Events

    DEFF Research Database (Denmark)

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

    2012-01-01

    In this study, we present a method for forecasting icing events. The method is validated at two European wind farms in with known icing events. The icing model used was developed using current ice accretion methods, and newly developed ablation algorithms. The model is driven by inputs from the WRF...... mesoscale model, allowing for both climatological estimates of icing and short term icing forecasts. The current model was able to detect periods of icing reasonably well at the warmer site. However at the cold climate site, the model was not able to remove ice quickly enough leading to large ice...... accumulations, which have not been seen in observations. In addition to the model evaluation we were able to investigate the potential occurrence of ice induced power loss at two wind parks in Europe using observed data. We found that the potential loss during an icing event is large even when the turbine...

  9. Forecasting Turbine Icing Events

    DEFF Research Database (Denmark)

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

    In this study, we present a method for forecasting icing events. The method is validated at two European wind farms in with known icing events. The icing model used was developed using current ice accretion methods, and newly developed ablation algorithms. The model is driven by inputs from the WRF...... mesoscale model, allowing for both climatological estimates of icing and short term icing forecasts. The current model was able to detect periods of icing reasonably well at the warmer site. However at the cold climate site, the model was not able to remove ice quickly enough leading to large ice...... accumulations, which have not been seen in observations. In addition to the model evaluation we were able to investigate the potential occurrence of ice induced power loss at two wind parks in Europe using observed data. We found that the potential loss during an icing event is large even when the turbine...

  10. A Laboratory-Based Evaluation of Four Rapid Point-of-Care Tests for Syphilis

    Science.gov (United States)

    Causer, Louise M.; Kaldor, John M.; Fairley, Christopher K.; Donovan, Basil; Karapanagiotidis, Theo; Leslie, David E.; Robertson, Peter W.; McNulty, Anna M.; Anderson, David; Wand, Handan; Conway, Damian P.; Denham, Ian; Ryan, Claire; Guy, Rebecca J.

    2014-01-01

    Background Syphilis point-of-care tests may reduce morbidity and ongoing transmission by increasing the proportion of people rapidly treated. Syphilis stage and co-infection with HIV may influence test performance. We evaluated four commercially available syphilis point-of-care devices in a head-to-head comparison using sera from laboratories in Australia. Methods Point-of-care tests were evaluated using sera stored at Sydney and Melbourne laboratories. Sensitivity and specificity were calculated by standard methods, comparing point-of-care results to treponemal immunoassay (IA) reference test results. Additional analyses by clinical syphilis stage, HIV status, and non-treponemal antibody titre were performed. Non-overlapping 95% confidence intervals (CI) were considered statistically significant differences in estimates. Results In total 1203 specimens were tested (736 IA-reactive, 467 IA-nonreactive). Point-of-care test sensitivities were: Determine 97.3%(95%CI:95.8–98.3), Onsite 92.5%(90.3–94.3), DPP 89.8%(87.3–91.9) and Bioline 87.8%(85.1–90.0). Specificities were: Determine 96.4%(94.1–97.8), Onsite 92.5%(90.3–94.3), DPP 98.3%(96.5–99.2), and Bioline 98.5%(96.8–99.3). Sensitivity of the Determine test was 100% for primary and 100% for secondary syphilis. The three other tests had reduced sensitivity among primary (80.4–90.2%) compared to secondary syphilis (94.3–98.6%). No significant differences in sensitivity were observed by HIV status. Test sensitivities were significantly higher among high-RPR titre (RPR≥8) (range: 94.6–99.5%) than RPR non-reactive infections (range: 76.3–92.9%). Conclusions The Determine test had the highest sensitivity overall. All tests were most sensitive among high-RPR titre infections. Point-of-care tests have a role in syphilis control programs however in developed countries with established laboratory infrastructures, the lower sensitivities of some tests observed in primary syphilis suggest these would

  11. A laboratory-based evaluation of four rapid point-of-care tests for syphilis.

    Directory of Open Access Journals (Sweden)

    Louise M Causer

    Full Text Available BACKGROUND: Syphilis point-of-care tests may reduce morbidity and ongoing transmission by increasing the proportion of people rapidly treated. Syphilis stage and co-infection with HIV may influence test performance. We evaluated four commercially available syphilis point-of-care devices in a head-to-head comparison using sera from laboratories in Australia. METHODS: Point-of-care tests were evaluated using sera stored at Sydney and Melbourne laboratories. Sensitivity and specificity were calculated by standard methods, comparing point-of-care results to treponemal immunoassay (IA reference test results. Additional analyses by clinical syphilis stage, HIV status, and non-treponemal antibody titre were performed. Non-overlapping 95% confidence intervals (CI were considered statistically significant differences in estimates. RESULTS: In total 1203 specimens were tested (736 IA-reactive, 467 IA-nonreactive. Point-of-care test sensitivities were: Determine 97.3%(95%CI:95.8-98.3, Onsite 92.5%(90.3-94.3, DPP 89.8%(87.3-91.9 and Bioline 87.8%(85.1-90.0. Specificities were: Determine 96.4%(94.1-97.8, Onsite 92.5%(90.3-94.3, DPP 98.3%(96.5-99.2, and Bioline 98.5%(96.8-99.3. Sensitivity of the Determine test was 100% for primary and 100% for secondary syphilis. The three other tests had reduced sensitivity among primary (80.4-90.2% compared to secondary syphilis (94.3-98.6%. No significant differences in sensitivity were observed by HIV status. Test sensitivities were significantly higher among high-RPR titre (RPR ≥ 8 (range: 94.6-99.5% than RPR non-reactive infections (range: 76.3-92.9%. CONCLUSIONS: The Determine test had the highest sensitivity overall. All tests were most sensitive among high-RPR titre infections. Point-of-care tests have a role in syphilis control programs however in developed countries with established laboratory infrastructures, the lower sensitivities of some tests observed in primary syphilis suggest these would need to be

  12. Broadband Traffic Forecasting in the Transport Network

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    Valentina Radojičić

    2012-07-01

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

  13. Global evaluation of a semiempirical model for yield anomalies and application to within-season yield forecasting.

    Science.gov (United States)

    Schauberger, Bernhard; Gornott, Christoph; Wechsung, Frank

    2017-11-01

    Quantifying the influence of weather on yield variability is decisive for agricultural management under current and future climate anomalies. We extended an existing semiempirical modeling scheme that allows for such quantification. Yield anomalies, measured as interannual differences, were modeled for maize, soybeans, and wheat in the United States and 32 other main producer countries. We used two yield data sets, one derived from reported yields and the other from a global yield data set deduced from remote sensing. We assessed the capacity of the model to forecast yields within the growing season. In the United States, our model can explain at least two-thirds (63%-81%) of observed yield anomalies. Its out-of-sample performance (34%-55%) suggests a robust yield projection capacity when applied to unknown weather. Out-of-sample performance is lower when using remote sensing-derived yield data. The share of weather-driven yield fluctuation varies spatially, and estimated coefficients agree with expectations. Globally, the explained variance in yield anomalies based on the remote sensing data set is similar to the United States (71%-84%). But the out-of-sample performance is lower (15%-42%). The performance discrepancy is likely due to shortcomings of the remote sensing yield data as it diminishes when using reported yield anomalies instead. Our model allows for robust forecasting of yields up to 2 months before harvest for several main producer countries. An additional experiment suggests moderate yield losses under mean warming, assuming no major changes in temperature extremes. We conclude that our model can detect weather influences on yield anomalies and project yields with unknown weather. It requires only monthly input data and has a low computational demand. Its within-season yield forecasting capacity provides a basis for practical applications like local adaptation planning. Our study underlines high-quality yield monitoring and statistics as critical

  14. Evaluation of methodological protocols using point counts and mist nets: a case study in southeastern Brazil

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    Vagner Cavarzere

    2013-01-01

    Full Text Available Despite their wide use in ornithological surveys, point counts and mist nets follow protocols developed in temperate regions, with little attention to possible modifications for tropical systems. Using these methods on a 3-month basis from December 2009-January 2011 in two forest fragments in southeastern Brazil, we wished to evaluate how long these locations needed to be surveyed with point counts for a relatively complete avifaunal inventory (at least 90% of all species and contacts, and if mist net hourly captures can equally detect numbers of species and individuals. Daily counting with four 20-min points during five consecutive days in a rain forest (MC detected 90% of the estimated species richness after 20 h (60 20-min point counts, while 17 h (51 20-min point counts did not detect 90% of the estimated species richness in a semideciduous forest (IT. The first 5 min of point counting in MC (63% of all species and in IT (65% detected significantly more species than the remaining minutes, but it took 15 min to accumulate 86% of all contacts in both forests. Consecutive 5-day mist netting (~ 9 h/day resulted in 70.5 net-h/m² (MC and 74.8 net-h/m² (IT of sample effort, but 80-85% of the estimated number of species was obtained. Although accumulation curves showed no tendency towards stabilization of the number of observed species, the estimated number of species began to stabilize after the first 20 h in both forests. There was no significant difference in capture rates for both species richness and abundance among hourly net checks, but a trend in which these parameters were highest between the second and fourth checks of the day was observed. A 3-day (43.8 and 63.3 net-h/m² mist netting section was enough to record 90% of the species captured during five days in MC and IT, respectively, while precise enough not to jeopardize species richness estimation. The number of individuals, however, decreased order 34% in MC and 38% in IT under the

  15. Precise and efficient evaluation of gravimetric quantities at arbitrarily scattered points in space

    Science.gov (United States)

    Ivanov, Kamen G.; Pavlis, Nikolaos K.; Petrushev, Pencho

    2017-12-01

    Gravimetric quantities are commonly represented in terms of high degree surface or solid spherical harmonics. After EGM2008, such expansions routinely extend to spherical harmonic degree 2190, which makes the computation of gravimetric quantities at a large number of arbitrarily scattered points in space using harmonic synthesis, a very computationally demanding process. We present here the development of an algorithm and its associated software for the efficient and precise evaluation of gravimetric quantities, represented in high degree solid spherical harmonics, at arbitrarily scattered points in the space exterior to the surface of the Earth. The new algorithm is based on representation of the quantities of interest in solid ellipsoidal harmonics and application of the tensor product trigonometric needlets. A FORTRAN implementation of this algorithm has been developed and extensively tested. The capabilities of the code are demonstrated using as examples the disturbing potential T, height anomaly ζ , gravity anomaly Δ g , gravity disturbance δ g , north-south deflection of the vertical ξ , east-west deflection of the vertical η , and the second radial derivative T_{rr} of the disturbing potential. After a pre-computational step that takes between 1 and 2 h per quantity, the current version of the software is capable of computing on a standard PC each of these quantities in the range from the surface of the Earth up to 544 km above that surface at speeds between 20,000 and 40,000 point evaluations per second, depending on the gravimetric quantity being evaluated, while the relative error does not exceed 10^{-6} and the memory (RAM) use is 9.3 GB.

  16. Probabilistic forecasting of the solar irradiance with recursive ARMA and GARCH models

    DEFF Research Database (Denmark)

    David, M.; Ramahatana, F.; Trombe, Pierre-Julien

    2016-01-01

    Forecasting of the solar irradiance is a key feature in order to increase the penetration rate of solar energy into the energy grids. Indeed, the anticipation of the fluctuations of the solar renewables allows a better management of the production means of electricity and a better operation...... of the grid-connected storage systems. If numerous methods for forecasting the mean of the solar irradiance were recently developed, there are only few works dedicated to the evaluation of prediction intervals associated to these point forecasts. Time series of solar irradiance and more specifically of clear...... sky index show some similarities with that of financial time series. The aim of this paper is to assess the performances of a commonly used combination of two linear models (ARMA and GARCH) in econometrics in order to provide probabilistic forecasts of solar irradiance. In addition, a recursive...

  17. Detecting, categorizing and forecasting large romps in wind farm power output using meteorological observations and WPPT

    DEFF Research Database (Denmark)

    Cutler, N.; Kay, M.; Jacka, K.

    2007-01-01

    The Wind Power Prediction Tool (WPPT) has been installed in Australia for the first time, to forecast the power output from the 65MW Roaring 40s Renewable Energy P/L Woolnorth Bluff Point wind form. This article analyses the general performance of WPPT as well as its performance during large romps...... (swings) in power output. In addition to this, detected large ramps are studied in detail and categorized. WPPT combines wind speed and direction forecasts from the Australian Bureau of Meteorology regional numerical weather prediction model, MesoLAPS, with real-time wind power observations to make hourly...... forecasts of the wind farm power output. The general performances of MesoLAPS and WPPTore evaluated over I year using the root mean square error (RMSE). The errors are significantly lower than for basic benchmark forecasts but higher than for many other WPPT installations, where the site conditions...

  18. Propagation of Uncertainty in Bayesian Kernel Models - Application to Multiple-Step Ahead Forecasting

    DEFF Research Database (Denmark)

    Quinonero, Joaquin; Girard, Agathe; Larsen, Jan

    2003-01-01

    The object of Bayesian modelling is predictive distribution, which, in a forecasting scenario, enables evaluation of forecasted values and their uncertainties. We focus on reliably estimating the predictive mean and variance of forecasted values using Bayesian kernel based models...

  19. Communicating uncertainty in hydrological forecasts: mission impossible?

    Science.gov (United States)

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

    2010-05-01

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

  20. SHORT-TERM SOLAR RADIATION FORECASTING BY USING AN ITERATIVE COMBINATION OF WAVELET ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Julio Cesar Royer

    2016-03-01

    Full Text Available The information provided by accurate forecasts of solar energy time series are considered essential for performing an appropriate prediction of the electrical power that will be available in an electric system, as pointed out in Zhou et al. (2011. However, since the underlying data are highly non-stationary, it follows that to produce their accurate predictions is a very difficult assignment. In order to accomplish it, this paper proposes an iterative Combination of Wavelet Artificial Neural Networks (CWANN which is aimed to produce short-term solar radiation time series forecasting. Basically, the CWANN method can be split into three stages: at first one, a decomposition of level p, defined in terms of a wavelet basis, of a given solar radiation time series is performed, generating r+1 Wavelet Components (WC; at second one, these r+1 WCs are individually modeled by the k different ANNs, where k>5, and the 5 best forecasts of each WC are combined by means of another ANN, producing the combined forecasts of WC; and, at third one, the combined forecasts WC are simply added, generating the forecasts of the underlying solar radiation data. An iterative algorithm is proposed for iteratively searching for the optimal values for the CWANN parameters, as we will see. In order to evaluate it, ten real solar radiation time series of Brazilian system were modeled here. In all statistical results, the CWANN method has achieved remarkable greater forecasting performances when compared with a traditional ANN (described in Section 2.1.

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

    Directory of Open Access Journals (Sweden)

    N.D. Geomelos

    2014-12-01

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

  2. Strategies to Evaluate the Visibility Along AN Indoor Path in a Point Cloud Representation

    Science.gov (United States)

    Grasso, N.; Verbree, E.; Zlatanova, S.; Piras, M.

    2017-09-01

    Many research works have been oriented to the formulation of different algorithms for estimating the paths in indoor environments from three-dimensional representations of space. The architectural configuration, the actions that take place within it, and the location of some objects in the space influence the paths along which is it possible to move, as they may cause visibility problems. To overcome the visibility issue, different methods have been proposed which allow to identify the visible areas and from a certain point of view, but often they do not take into account the user's visual perception of the environment and not allow estimating how much may be complicated to follow a certain path. In the field of space syntax and cognitive science, it has been attempted to describe the characteristics of a building or an urban environment by the isovists and visibility graphs methods; some numerical properties of these representations allow to describe the space as for how it is perceived by a user. However, most of these studies are directed to analyze the environment in a two-dimensional space. In this paper we propose a method to evaluate in a quantitative way the complexity of a certain path within an environment represented by a three-dimensional point cloud, by the combination of some of the previously mentioned techniques, considering the space visible from a certain point of view, depending on the moving agent (pedestrian , people in wheelchairs, UAV, UGV, robot).

  3. STRATEGIES TO EVALUATE THE VISIBILITY ALONG AN INDOOR PATH IN A POINT CLOUD REPRESENTATION

    Directory of Open Access Journals (Sweden)

    N. Grasso

    2017-09-01

    Full Text Available Many research works have been oriented to the formulation of different algorithms for estimating the paths in indoor environments from three-dimensional representations of space. The architectural configuration, the actions that take place within it, and the location of some objects in the space influence the paths along which is it possible to move, as they may cause visibility problems. To overcome the visibility issue, different methods have been proposed which allow to identify the visible areas and from a certain point of view, but often they do not take into account the user’s visual perception of the environment and not allow estimating how much may be complicated to follow a certain path. In the field of space syntax and cognitive science, it has been attempted to describe the characteristics of a building or an urban environment by the isovists and visibility graphs methods; some numerical properties of these representations allow to describe the space as for how it is perceived by a user. However, most of these studies are directed to analyze the environment in a two-dimensional space. In this paper we propose a method to evaluate in a quantitative way the complexity of a certain path within an environment represented by a three-dimensional point cloud, by the combination of some of the previously mentioned techniques, considering the space visible from a certain point of view, depending on the moving agent (pedestrian , people in wheelchairs, UAV, UGV, robot.

  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. Are Forecast Updates Progressive?

    NARCIS (Netherlands)

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

    2013-01-01

    textabstractMany macroeconomic forecasts and forecast updates like those from IMF and OECD typically involve both a model component, which is replicable, as well as intuition, which is non-replicable. Intuition is expert knowledge possessed by a forecaster. If forecast updates are progressive,

  6. Evaluation of new indigenous "point-of-care" ABO and Rh grouping device.

    Science.gov (United States)

    Tiwari, Aseem Kumar; Setya, Divya; Aggarwal, Geet; Arora, Dinesh; Dara, Ravi C; Ratan, Ankita; Bhardwaj, Gunjan; Acharya, Devi Prasad

    2018-01-01

    Erycard 2.0 is a "point-of-care" device that is primarily being used for patient blood grouping before transfusion. Erycard 2.0 was compared with conventional slide technology for accuracy and time taken for ABO and Rh forward grouping result with column agglutination technology (CAT) being the gold standard. Erycard 2.0 as a device was also evaluated for its stability under different storage conditions and stability of result till 48 h. In addition, grouping of hemolyzed samples was also tested with Erycard 2.0. Ease of use of Erycard 2.0 was evaluated with a survey among paramedical staff. Erycard 2.0 demonstrated 100% concordance with CAT as compared with slide technique (98.9%). Mean time taken per test by Erycard 2.0 and slide technique was 5.13 min and 1.7 min, respectively. After pretesting storage under different temperature and humidity conditions, Erycard 2.0 did not show any deviation from the result. The result did not change even after 48 h of testing and storage under room temperature. 100% concordance was recorded between pre- and post-hemolyzed blood grouping. Ease of use survey revealed that Erycard 2.0 was more acceptable to paramedical staff for its simplicity, objectivity, and performance than conventional slide technique. Erycard 2.0 can be used as "point-of-care" device for blood donor screening for ABO and Rh blood group and can possibly replace conventional slide technique.

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

    Science.gov (United States)

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

    2017-02-01

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

  8. Evaluation of a multiple regression model for the forecasting of the concentrations of NOx and PM10 in Athens and Helsinki.

    Science.gov (United States)

    Vlachogianni, A; Kassomenos, P; Karppinen, Ari; Karakitsios, S; Kukkonen, Jaakko

    2011-03-15

    Forecasting models based on stepwise multiple linear regression (MLR) have been developed for Athens and Helsinki. The predictor variables were the hourly concentrations of pollutants (NO, NO(2), NO(x), CO, O(3), PM(2.5) and PM(10)) and the meteorological variables (ambient temperature, wind speed/direction, and relative humidity) and in case of Helsinki also Monin-Obukhov length and mixing height of the present day. The variables to be forecasted are the maximum hourly concentrations of PM(10) and NO(x), and the daily average PM(10) concentrations of the next day. The meteorological pre-processing model MPP-FMI was used for computing the Monin-Obukhov length and the mixing height. The limitations of such statistical models include the persistence of both the meteorological and air quality situation; the model cannot account for rapid changes (on a temporal scale of hours or less than a day) that are commonly associated, e.g., with meteorological fronts, or episodes of a long-range transport origin. We have selected the input data for the model from one urban background and one urban traffic station both in Athens and Helsinki, in 2005. We have used various statistical evaluation parameters to analyze the performance of the models, and inter-compared the performance of the predictions for both cities. Forecasts from the MLR model were also compared to those from an Artificial Neural Network model (ANN) to investigate, if there are substantial gains that might justify the additional computational effort. The best predictor variables for both cities were the concentrations of NO(x) and PM(10) during the evening hours as well as wind speed, and the Monin-Obukhov length. In Athens, the index of agreement (IA) for NO(x) ranged from 0.77 to 0.84 and from 0.69 to 0.72, in the warm and cold periods of the year. In Helsinki, the corresponding values of IA ranged from 0.32 to 0.82 and from 0.67 to 0.86 for the warm and cold periods. In case of Helsinki the model accuracy was

  9. Evaluation of the first seizure patient: Key points in the history and physical examination.

    Science.gov (United States)

    Nowacki, Tomasz A; Jirsch, Jeffrey D

    2017-07-01

    This review will present the history and physical examination as the launching point of the first seizure evaluation, from the initial characterization of the event, to the exclusion of alternative diagnoses, and then to the determination of specific acute or remote causes. Clinical features that may distinguish seizures from alternative diagnoses are discussed in detail, followed by a discussion of acute and remote first seizure etiologies. This review article is based on a discretionary selection of English language articles retrieved by a literature search in the PubMed database, and the authors' clinical experience. The first seizure is a dramatic event with often profound implications for patients and family members. The initial clinical evaluation focuses on an accurate description of the spell to confirm the diagnosis, along with careful scrutiny for previously unrecognized seizures that would change the diagnosis more definitively to one of epilepsy. The first seizure evaluation rests primarily on the clinical history, and to a lesser extent, the physical examination. Even in the era of digital EEG recording and neuroimaging, the initial clinical evaluation remains essential for the diagnosis, treatment, and prognostication of the first seizure. Copyright © 2016. Published by Elsevier Ltd.

  10. The evaluation of reflective learning from the nursing student's point of view: A mixed method approach.

    Science.gov (United States)

    Fernández-Peña, Rosario; Fuentes-Pumarola, Concepció; Malagón-Aguilera, M Carme; Bonmatí-Tomàs, Anna; Bosch-Farré, Cristina; Ballester-Ferrando, David

    2016-09-01

    Adapting university programmes to European Higher Education Area criteria has required substantial changes in curricula and teaching methodologies. Reflective learning (RL) has attracted growing interest and occupies an important place in the scientific literature on theoretical and methodological aspects of university instruction. However, fewer studies have focused on evaluating the RL methodology from the point of view of nursing students. To assess nursing students' perceptions of the usefulness and challenges of RL methodology. Mixed method design, using a cross-sectional questionnaire and focus group discussion. The research was conducted via self-reported reflective learning questionnaire complemented by focus group discussion. Students provided a positive overall evaluation of RL, highlighting the method's capacity to help them better understand themselves, engage in self-reflection about the learning process, optimize their strengths and discover additional training needs, along with searching for continuous improvement. Nonetheless, RL does not help them as much to plan their learning or identify areas of weakness or needed improvement in knowledge, skills and attitudes. Among the difficulties or challenges, students reported low motivation and lack of familiarity with this type of learning, along with concerns about the privacy of their reflective journals and about the grading criteria. In general, students evaluated RL positively. The results suggest areas of needed improvement related to unfamiliarity with the methodology, ethical aspects of developing a reflective journal and the need for clear evaluation criteria. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

    2005-05-01

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

  12. Long-term forecasting and comparison of mortality in the Evaluation of the Xience Everolimus Eluting Stent vs. Coronary Artery Bypass Surgery for Effectiveness of Left Main Revascularization (EXCEL) trial: Prospective validation of the SYNTAX Score II

    NARCIS (Netherlands)

    C.A.M. Campos (Carlos); D. van Klaveren (David); V. Farooq (Vasim); C. Simonton (Charles); A.P. Kappetein (Arie Pieter); J.F. Sabik (Joseph); E.W. Steyerberg (Ewout); G.W. Stone (Gregg); P.W.J.C. Serruys (Patrick)

    2015-01-01

    textabstractAims To prospectively validate the SYNTAX Score II and forecast the outcomes of the randomized Evaluation of the Xience Everolimus-Eluting Stent Versus Coronary Artery Bypass Surgery for Effectiveness of Left Main Revascularization (EXCEL) Trial. Methods and results Evaluation of the

  13. Experimental evaluation of ALS point cloud ground extraction over different land cover in the Malopolska Province

    Science.gov (United States)

    Korzeniowska, Karolina; Mandlburger, Gottfried; Klimczyk, Agata

    2013-04-01

    The paper presents an evaluation of different terrain point extraction algorithms for Airborne Laser Scanning (ALS) point clouds. The research area covers eight test sites in the Małopolska Province (Poland) with varying point density between 3-15points/m² and surface as well as land cover characteristics. In this paper the existing implementations of algorithms were considered. Approaches based on mathematical morphology, progressive densification, robust surface interpolation and segmentation were compared. From the group of morphological filters, the Progressive Morphological Filter (PMF) proposed by Zhang K. et al. (2003) in LIS software was evaluated. From the progressive densification filter methods developed by Axelsson P. (2000) the Martin Isenburg's implementation in LAStools software (LAStools, 2012) was chosen. The third group of methods are surface-based filters. In this study, we used the hierarchic robust interpolation approach by Kraus K., Pfeifer N. (1998) as implemented in SCOP++ (Trimble, 2012). The fourth group of methods works on segmentation. From this filtering concept the segmentation algorithm available in LIS was tested (Wichmann V., 2012). The main aim in executing the automatic classification for ground extraction was operating in default mode or with default parameters which were selected by the developers of the algorithms. It was assumed that the default settings were equivalent to the parameters on which the best results can be achieved. In case it was not possible to apply an algorithm in default mode, a combination of the available and most crucial parameters for ground extraction were selected. As a result of these analyses, several output LAS files with different ground classification were achieved. The results were described on the basis of qualitative and quantitative analyses, both being in a formal description. The classification differences were verified on point cloud data. Qualitative verification of ground extraction was

  14. Brazilian Program For HIV Point-Of-Care Test Evaluation: A Decade’s Experience

    Directory of Open Access Journals (Sweden)

    Orlando da Costa Ferreira Jr.

    2017-11-01

    Full Text Available The point-of-care tests (POCTs for HIV diagnosis have been widely used in Brazil in order to expand and to allow HIV diagnosis outside health units including remote areas, such as the Amazon region. In order to guarantee the quality of HIV diagnostics based on rapid tests, the Brazilian Ministry of Health (MoH implemented the HIV POCT Evaluation Program. This study compiles the Brazilian experience acquired over the last 13 years conducting the HIV POCT Evaluation Program.   Methods and Findings The selection of tests was based on the interest of manufacturers to qualify for the MoH tenders. Each round was performed with fresh whole blood and oral fluid samples, always including HIV positive and negative ones. In addition to the POCT, every sample was submitted to a reference testing protocol, based on an immunoassay followed by Western blot. The POCTs were evaluated for clinical sensitivity, clinical specificity, assay operational characteristics, detection of HIV-2 antibodies, sensitivity to subtypes panels; and sensitivity to seroconversion panels. Since its implementation in 2003, the POCT evaluation protocol has undergone some modifications aiming to improve and simplify the evaluation process, to know: (i  for HIV-positive samples, perform EIA and Western blot only if the POCT is non-reactive; (ii reduction from 800 to 600 HIV negative samples; (iii increase from one to three subtype panels (including HIV-2 samples; and (iv inclusion of seroconversion panel. We evaluated six tests, four of which met the sensitivity criteria of 99.5%: BD Chek™ HIV Multi-test (whole blood, HIV 1/2 Colloidal Gold (whole blood, OraQuick ADVANCE® Rapid HIV-1/2 Antibody Test (whole blood and oral fluid and TR DPP HIV-1/2 (whole blood, plasma and oral fluid. Regarding other evaluated criteria, all assays met the requirements.   Conclusions The successful Brazilian policy on POCT use for HIV infection diagnosis includes the evaluation of the POCT itself in

  15. Online short-term solar power forecasting

    DEFF Research Database (Denmark)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

  17. Ecological evaluation of proposed dredged material from the Point Frazer Bend Reach, Winyah Bay, South Carolina

    Energy Technology Data Exchange (ETDEWEB)

    Gardiner, W.W.; Ward, J.A.; Word, J.Q.

    1995-02-01

    The port of Georgetown, South Carolina, is served by navigational channels within Winyah Bay and the lower Sampit River. Dredging is required to maintain these waterways and to facilitate normal shipping traffic. Prior to dredging, ecological evaluations must be conducted to determine the suitability of the proposed dredged material for open-ocean disposal. These evaluations are to be performed under Section 103 of the Marine Protection, Research, and, Sanctuaries Act of 1972 (MPRSA), following the testing protocols presented in Evaluation of Dredged Material Proposed for Ocean Disposal Testing Manual, hereafter referred to as the 1991 Implementation Manual. The Charleston Intensive Project is a reevaluation of sediments collected from two stations (IH-2 and IH-3) in the Frazier Point Bend reach of the Winyah Bay channel. Reference sediment was also collected from site IH-R2, just south of Hare Island. The results of physical/chemical analyses indicated that some contaminants of concern were present in test treatments representing dredged material when compared with the reference treatment IH-R2. The results of this study indicate that, based on the acute toxicity and chemical analyses, dredged material represented by these test treatments is suitable for open-ocean disposal.

  18. Resource and Performance Evaluations of Fixed Point QRD-RLS Systolic Array through FPGA Implementation

    Science.gov (United States)

    Yokoyama, Yoshiaki; Kim, Minseok; Arai, Hiroyuki

    At present, when using space-time processing techniques with multiple antennas for mobile radio communication, real-time weight adaptation is necessary. Due to the progress of integrated circuit technology, dedicated processor implementation with ASIC or FPGA can be employed to implement various wireless applications. This paper presents a resource and performance evaluation of the QRD-RLS systolic array processor based on fixed-point CORDIC algorithm with FPGA. In this paper, to save hardware resources, we propose the shared architecture of a complex CORDIC processor. The required precision of internal calculation, the circuit area for the number of antenna elements and wordlength, and the processing speed will be evaluated. The resource estimation provides a possible processor configuration with a current FPGA on the market. Computer simulations assuming a fading channel will show a fast convergence property with a finite number of training symbols. The proposed architecture has also been implemented and its operation was verified by beamforming evaluation through a radio propagation experiment.

  19. Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (Myocastor coypus)

    Science.gov (United States)

    Jarnevich, Catherine S.; Young, Nicholas E; Sheffels, Trevor R.; Carter, Jacoby; Systma, Mark D.; Talbert, Colin

    2017-01-01

    Invasive species provide a unique opportunity to evaluate factors controlling biogeographic distributions; we can consider introduction success as an experiment testing suitability of environmental conditions. Predicting potential distributions of spreading species is not easy, and forecasting potential distributions with changing climate is even more difficult. Using the globally invasive coypu (Myocastor coypus [Molina, 1782]), we evaluate and compare the utility of a simplistic ecophysiological based model and a correlative model to predict current and future distribution. The ecophysiological model was based on winter temperature relationships with nutria survival. We developed correlative statistical models using the Software for Assisted Habitat Modeling and biologically relevant climate data with a global extent. We applied the ecophysiological based model to several global circulation model (GCM) predictions for mid-century. We used global coypu introduction data to evaluate these models and to explore a hypothesized physiological limitation, finding general agreement with known coypu distribution locally and globally and support for an upper thermal tolerance threshold. Global circulation model based model results showed variability in coypu predicted distribution among GCMs, but had general agreement of increasing suitable area in the USA. Our methods highlighted the dynamic nature of the edges of the coypu distribution due to climate non-equilibrium, and uncertainty associated with forecasting future distributions. Areas deemed suitable habitat, especially those on the edge of the current known range, could be used for early detection of the spread of coypu populations for management purposes. Combining approaches can be beneficial to predicting potential distributions of invasive species now and in the future and in exploring hypotheses of factors controlling distributions.

  20. Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: an example with coypu (Myocastor coypus

    Directory of Open Access Journals (Sweden)

    Catherine S. Jarnevich

    2017-01-01

    Full Text Available Invasive species provide a unique opportunity to evaluate factors controlling biogeographic distributions; we can consider introduction success as an experiment testing suitability of environmental conditions. Predicting potential distributions of spreading species is not easy, and forecasting potential distributions with changing climate is even more difficult. Using the globally invasive coypu (Myocastor coypus [Molina, 1782], we evaluate and compare the utility of a simplistic ecophysiological based model and a correlative model to predict current and future distribution. The ecophysiological model was based on winter temperature relationships with nutria survival. We developed correlative statistical models using the Software for Assisted Habitat Modeling and biologically relevant climate data with a global extent. We applied the ecophysiological based model to several global circulation model (GCM predictions for mid-century. We used global coypu introduction data to evaluate these models and to explore a hypothesized physiological limitation, finding general agreement with known coypu distribution locally and globally and support for an upper thermal tolerance threshold. Global circulation model based model results showed variability in coypu predicted distribution among GCMs, but had general agreement of increasing suitable area in the USA. Our methods highlighted the dynamic nature of the edges of the coypu distribution due to climate non-equilibrium, and uncertainty associated with forecasting future distributions. Areas deemed suitable habitat, especially those on the edge of the current known range, could be used for early detection of the spread of coypu populations for management purposes. Combining approaches can be beneficial to predicting potential distributions of invasive species now and in the future and in exploring hypotheses of factors controlling distributions.

  1. Research and application of a hybrid model based on dynamic fuzzy synthetic evaluation for establishing air quality forecasting and early warning system: A case study in China.

    Science.gov (United States)

    Xu, Yunzhen; Du, Pei; Wang, Jianzhou

    2017-04-01

    As the atmospheric environment pollution has been becoming more and more serious in China, it is highly desirable to develop a scientific and effective early warning system that plays a great significant role in analyzing and monitoring air quality. However, establishing a robust early warning system for warning the public in advance and ameliorating air quality is not only an extremely challenging task but also a public concerned problem for human health. Most previous studies are focused on improving the prediction accuracy, which usually ignore the significance of uncertainty information and comprehensive evaluation concerning air pollutants. Therefore, in this paper a novel robust early warning system was successfully developed, which consists of three modules: evaluation module, forecasting module and characteristics estimating module. In this system, a new dynamic fuzzy synthetic evaluation is proposed and applied to determine air quality levels and primary pollutants, which can be regarded as the research objectives; Moreover, to further mine and analyze the characteristics of air pollutants, four different distribution functions and interval forecasting method are also employed that can not only provide predictive range, confidence level and the other uncertain information of the pollutants future values, but also assist decision-makers in reducing and controlling the emissions of atmospheric pollutants. Case studies utilizing hourly PM2.5, PM10 and SO2 data collected from Tianjin and Shanghai in China are applied as illustrative examples to estimate the effectiveness and efficiency of the proposed system. Experimental results obviously indicated that the developed novel early warning system is much suitable for analyzing and monitoring air pollution, which can also add a novel viable option for decision-makers. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Evaluating the Potential of Imaging Rover for Automatic Point Cloud Generation

    Science.gov (United States)

    Cera, V.; Campi, M.

    2017-02-01

    The paper presents a phase of an on-going interdisciplinary research concerning the medieval site of Casertavecchia (Italy). The project aims to develop a multi-technique approach for the semantic - enriched 3D modeling starting from the automatic acquisition of several data. In particular, the paper reports the results of the first stage about the Cathedral square of the medieval village. The work is focused on evaluating the potential of an imaging rover for automatic point cloud generation. Each of survey techniques has its own advantages and disadvantages so the ideal approach is an integrated methodology in order to maximize single instrument performance. The experimentation was conducted on the Cathedral square of the ancient site of Casertavecchia, in Campania, Italy.

  3. A dissipated energy comparison to evaluate fatigue resistance using 2-point bending

    Directory of Open Access Journals (Sweden)

    Cinzia Maggiore

    2014-02-01

    Full Text Available Fatigue is the main failure mode in pavement engineering. Typically, micro-cracks originate at the bottom of asphalt concrete layer due to horizontal tensile strains. Micro-cracks start to propagate towards the upper layers under repeated loading which can lead to pavement failure. Different methods are usually used to describe fatigue behavior in asphalt materials such as: phenomenological approach, fracture mechanics approach and dissipated energy approach. This paper presents a comparison of fatigue resistances calculated for different dissipated energy models using 2-point bending (2PB at IFSTTAR in Nantes. 2PB tests have been undertaken under different loading and environmental conditions in order to evaluate the properties of the mixtures (stiffness, dissipated energy, fatigue life and healing effect.

  4. Experimental Evaluation of Stagnation Point Collection Efficiency of the NACA 0012 Swept Wing Tip

    Science.gov (United States)

    Tsao, Jen-Ching; Kreeger, Richard E.

    2010-01-01

    This paper presents the experimental work of a number of icing tests conducted in the Icing Research Tunnel at NASA Glenn Research Center to develop a test method for measuring the local collection efficiency of an impinging cloud at the leading edge of a NACA 0012 swept wing and with the data obtained to further calibrate a proposed correlation for such impingement efficiency calculation as a function of the modified inertia parameter and the sweep angle. The preliminary results showed that there could be some limitation of the test method due to the ice erosion problem when encountered, and also found that, for conditions free of such problem, the stagnation point collection efficiency measurement for sweep angles up to 45 could be well approximated by the proposed correlation. Further evaluation of this correlation is recommended in order to assess its applicability for swept-wing icing scaling analysis.

  5. Seamless hydrological forecasts from daily to seasonal scale for Europe

    Science.gov (United States)

    Wetterhall, Fredrik; Arnal, Louise; Krzeminski, Blazej

    2017-04-01

    Seasonal hydrological forecasts are a useful tool to asses water resources management on longer time scales. Applications are for example water power production, transport, drought forecasting and reservoir management. Seasonal forecasts are typically issued once a month which limits the possibility of more frequent updates. In this study the ECMWF extended ensemble forecast with a 46-day lead time was merged with the seasonal ensemble forecast from ECMWF to create a seamless forecasting system updated biweekly. The forecast was then used as input to the LISFLOOD model to create a probabilistic sub-seasonal to seasonal hydrological outlook on a pan-European scale. The model system was evaluated on a basin scale against a water balance run using observed meteorological input as forcing. The advantages with the merged system over using the seasonal forecast system was an improvement in skill as well as providing more frequent forecasts.

  6. Management earnings forecasts and analyst forecasts: Evidence from mandatory disclosure system

    Directory of Open Access Journals (Sweden)

    Yutao Wang

    2015-06-01

    Full Text Available Distinct from the literature on the effects that management earnings forecasts (MEFs properties, such as point, range and qualitative estimations, have on analyst forecasts, this study explores the effects of selective disclosure of MEFs. Under China’s mandatory disclosure system, this study proposes that managers issue frequent forecasts to take advantage of opportune changes in predicted earnings. The argument herein is that this selective disclosure of MEFs increases information asymmetry and uncertainty, negatively influencing analyst earnings forecasts. Empirical evidence shows that firms that issue more frequent forecasts and make significant changes in MEFs are less likely to attract an analyst following, which can lead to less accurate analyst forecasts. The results imply that the selective disclosure of MEFs damages information transmission and market efficiency, which can enlighten regulators seeking to further enhance disclosure policies.

  7. Stochastic model of forecasting spare parts demand

    Directory of Open Access Journals (Sweden)

    Ivan S. Milojević

    2012-01-01

    hypothesis of the existence of phenomenon change trends, the next step in the methodology of forecasting is the determination of a specific growth curve that describes the regularity of the development in time. These curves of growth are obtained by the analytical representation (expression of dynamic lines. There are two basic stages in the process of expression and they are: - The choice of the type of curve the shape of which corresponds to the character of the dynamic order variation - the determination of the number of values (evaluation of the curve parameters. The most widespread method of forecasting is the trend extrapolation. The basis of the trend extrapolation is the continuing of past trends in the future. The simplicity of the trend extrapolation process, on the one hand, and the absence of other information on the other hand, are the main reasons why the trend extrapolation is used for forecasting. The trend extrapolation is founded on the following assumptions: - The phenomenon development can be presented as an evolutionary trajectory or trend, - General conditions that influenced the trend development in the past will not undergo substantial changes in the future. Spare parts demand forecasting is constantly being done in all warehouses, workshops, and at all levels. Without demand forecasting, neither planning nor decision making can be done. Demand forecasting is the input for determining the level of reserve, size of the order, ordering cycles, etc. The question that arises is the one of the reliability and accuracy of a forecast and its effects. Forecasting 'by feeling' is not to be dismissed if there is nothing better, but in this case, one must be prepared for forecasting failures that cause unnecessary accumulation of certain spare parts, and also a chronic shortage of other spare parts. All this significantly increases costs and does not provide a satisfactory supply of spare parts. The main problem of the application of this model is that each

  8. An evaluation of Bayesian techniques for controlling model complexity and selecting inputs in a neural network for short-term load forecasting.

    Science.gov (United States)

    Hippert, Henrique S; Taylor, James W

    2010-04-01

    Artificial neural networks have frequently been proposed for electricity load forecasting because of their capabilities for the nonlinear modelling of large multivariate data sets. Modelling with neural networks is not an easy task though; two of the main challenges are defining the appropriate level of model complexity, and choosing the input variables. This paper evaluates techniques for automatic neural network modelling within a Bayesian framework, as applied to six samples containing daily load and weather data for four different countries. We analyse input selection as carried out by the Bayesian 'automatic relevance determination', and the usefulness of the Bayesian 'evidence' for the selection of the best structure (in terms of number of neurones), as compared to methods based on cross-validation. Copyright 2009 Elsevier Ltd. All rights reserved.

  9. Fast computation of quadrupole and hexadecapole approximations in microlensing with a single point-source evaluation

    Science.gov (United States)

    Cassan, Arnaud

    2017-07-01

    The exoplanet detection rate from gravitational microlensing has grown significantly in recent years thanks to a great enhancement of resources and improved observational strategy. Current observatories include ground-based wide-field and/or robotic world-wide networks of telescopes, as well as space-based observatories such as satellites Spitzer or Kepler/K2. This results in a large quantity of data to be processed and analysed, which is a challenge for modelling codes because of the complexity of the parameter space to be explored and the intensive computations required to evaluate the models. In this work, I present a method that allows to compute the quadrupole and hexadecapole approximations of the finite-source magnification with more efficiency than previously available codes, with routines about six times and four times faster, respectively. The quadrupole takes just about twice the time of a point-source evaluation, which advocates for generalizing its use to large portions of the light curves. The corresponding routines are available as open-source python codes.

  10. Evaluating the sustainability of ceramic filters for point-of-use drinking water treatment.

    Science.gov (United States)

    Ren, Dianjun; Colosi, Lisa M; Smith, James A

    2013-10-01

    This study evaluates the social, economic, and environmental sustainability of ceramic filters impregnated with silver nanoparticles for point-of-use (POU) drinking water treatment in developing countries. The functional unit for this analysis was the amount of water consumed by a typical household over ten years (37,960 L), as delivered by either the POU technology or a centralized water treatment and distribution system. Results indicate that the ceramic filters are 3-6 times more cost-effective than the centralized water system for reduction of waterborne diarrheal illness among the general population and children under five. The ceramic filters also exhibit better environmental performance for four of five evaluated life cycle impacts: energy use, water use, global warming potential, and particulate matter emissions (PM10). For smog formation potential, the centralized system is preferable to the ceramic filter POU technology. This convergence of social, economic, and environmental criteria offers clear indication that the ceramic filter POU technology is a more sustainable choice for drinking water treatment in developing countries than the centralized treatment systems that have been widely adopted in industrialized countries.

  11. Evaluation of a point-of-care transcutaneous bilirubinometer in Chinese neonates at an accident and emergency department

    National Research Council Canada - National Science Library

    Lam, Tommy S K; Tsui, K L; Kam, C W

    2008-01-01

    To evaluate the use of a point-of-care transcutaneous bilirubinometer, JM-103 Minolta, for estimation of the serum bilirubin level in the management of neonatal jaundice in term or near-term Chinese neonates...

  12. An automated method for the evaluation of the pointing accuracy of Sun-tracking devices

    Science.gov (United States)

    Baumgartner, Dietmar J.; Pötzi, Werner; Freislich, Heinrich; Strutzmann, Heinz; Veronig, Astrid M.; Rieder, Harald E.

    2017-03-01

    The accuracy of solar radiation measurements, for direct (DIR) and diffuse (DIF) radiation, depends significantly on the precision of the operational Sun-tracking device. Thus, rigid targets for instrument performance and operation have been specified for international monitoring networks, e.g., the Baseline Surface Radiation Network (BSRN) operating under the auspices of the World Climate Research Program (WCRP). Sun-tracking devices that fulfill these accuracy requirements are available from various instrument manufacturers; however, none of the commercially available systems comprise an automatic accuracy control system allowing platform operators to independently validate the pointing accuracy of Sun-tracking sensors during operation. Here we present KSO-STREAMS (KSO-SunTRackEr Accuracy Monitoring System), a fully automated, system-independent, and cost-effective system for evaluating the pointing accuracy of Sun-tracking devices. We detail the monitoring system setup, its design and specifications, and the results from its application to the Sun-tracking system operated at the Kanzelhöhe Observatory (KSO) Austrian radiation monitoring network (ARAD) site. The results from an evaluation campaign from March to June 2015 show that the tracking accuracy of the device operated at KSO lies within BSRN specifications (i.e., 0.1° tracking accuracy) for the vast majority of observations (99.8 %). The evaluation of manufacturer-specified active-tracking accuracies (0.02°), during periods with direct solar radiation exceeding 300 W m-2, shows that these are satisfied in 72.9 % of observations. Tracking accuracies are highest during clear-sky conditions and on days where prevailing clear-sky conditions are interrupted by frontal movement; in these cases, we obtain the complete fulfillment of BSRN requirements and 76.4 % of observations within manufacturer-specified active-tracking accuracies. Limitations to tracking surveillance arise during overcast conditions and

  13. Evaluation of NOAA's High Resolution Rapid Refresh (HRRR), 12 km North America Model (NAM12) and 4km North America Model (NAM 4) hub-height wind speed forecasts

    Science.gov (United States)

    Pendergrass, W.; Vogel, C. A.

    2013-12-01

    As an outcome of discussions between Duke Energy Generation and NOAA/ARL following the 2009 AMS Summer Community Meeting, in Norman Oklahoma, ARL and Duke Energy Generation (Duke) signed a Cooperative Research and Development Agreement (CRADA) which allows NOAA to conduct atmospheric boundary layer (ABL) research using Duke renewable energy sites as research testbeds. One aspect of this research has been the evaluation of forecast hub-height winds from three NOAA atmospheric models. Forecasts of 10m (surface) and 80m (hub-height) wind speeds from (1) NOAA/GSD's High Resolution Rapid Refresh (HRRR) model, (2) NOAA/NCEP's 12 km North America Model (NAM12) and (3) NOAA/NCEP's 4k high resolution North America Model (NAM4) were evaluated against 18 months of surface-layer wind observations collected at the joint NOAA/Duke Energy research station located at Duke Energy's West Texas Ocotillo wind farm over the period April 2011 through October 2012. HRRR, NAM12 and NAM4 10m wind speed forecasts were compared with 10m level wind speed observations measured on the NOAA/ATDD flux-tower. Hub-height (80m) HRRR , NAM12 and NAM4 forecast wind speeds were evaluated against the 80m operational PMM27-28 meteorological tower supporting the Ocotillo wind farm. For each HRRR update, eight forecast hours (hour 01, 02, 03, 05, 07, 10, 12, 15) plus the initialization hour (hour 00), evaluated. For the NAM12 and NAM4 models forecast hours 00-24 from the 06z initialization were evaluated. Performance measures or skill score based on absolute error 50% cumulative probability were calculated for each forecast hour. HRRR forecast hour 01 provided the best skill score with an absolute wind speed error within 0.8 m/s of observed 10m wind speed and 1.25 m/s for hub-height wind speed at the designated 50% cumulative probability. For both NAM4 and NAM12 models, skill scores were diurnal with comparable best scores observed during the day of 0.7 m/s of observed 10m wind speed and 1.1 m/s for hub

  14. Influence of the details of topography onweather forecastevaluation of HARMONIEexperiments in the Sochi Olympics domainover the Caucasian mountains

    Directory of Open Access Journals (Sweden)

    Laura eRontu

    2016-02-01

    Full Text Available New fine-resolution surface elevation data was implemented intoHARMONIE-AROME-SURFEX Numerical Weather Prediction (NWP system. Thegrid-scale mean orography, used as a basis of the model'sterrain-following vertical coordinate, as well as variables forsuggested new parametrizations of radiation and momentum fluxes werederived. Validation against the surface observations from the SochiWinter Olympic Games 2014, provided by the WMO FROST-2014 program atthe Caucasian mountains, showed minor degradation of the of thenscreen-level temperature forecast when only the source orography wasupdated. Implementation of the orographic radiation parametrizationsallowed to alleviate the degradation of scores. Detailed sensitivitystudies, done by using three-dimensional and single-columnexperiments, showed that substantial and physically realistic changesin the downwelling short- and longwave radiation fluxes took placelocally. However, their influence on the the simulated screen-leveltemperature remained small. Comparison of the simulated and observedradiation fluxes would offer a reliable alternative for validation ofNWP models. Unfortunately, surface-level radiation observations were notmade during the Sochi Olympics.

  15. Forecasting the start of the pollen season of Poaceæ: evaluation of some methods based on meteorological factors

    Science.gov (United States)

    Laaidi, M.

    The pollen of anemogamous plants is responsible for half the allergic diseases, that is to say a prevalence of 10% in the French population. Poaceæ produce the first allergenic pollen almost everywhere. The work described in this article aimed to validate forecast methods for the use of physicians and allergic people who need accurate and early information on the first appearance of pollen in the air. The methods were based on meteorological parameters, mainly temperature. Four volumetric Hirst traps were used from 1995 to 1998, situated in two departments of Burgundy. Two of the methods tested proved to be of particular interest: the sum of the temperatures and the sum of Q10 values, an agrometeorological coefficient integrating temperature. A multiple regression, using maximum temperature and rainfall, was also performed but it gave slightly less accurate results. A χ2-test was then used to compare the accuracy of the three methods. It was found that the date of onset of the pollen season could be predicted early enough to be useful in medical practice. Results were verified in 1999, and the research must be continued to obtain better statistical validity.

  16. A two-stage method of quantitative flood risk analysis for reservoir real-time operation using ensemble-based hydrologic forecasts

    Science.gov (United States)

    Liu, P.

    2013-12-01

    Quantitative analysis of the risk for reservoir real-time operation is a hard task owing to the difficulty of accurate description of inflow uncertainties. The ensemble-based hydrologic forecasts directly depict the inflows not only the marginal distributions but also their persistence via scenarios. This motivates us to analyze the reservoir real-time operating risk with ensemble-based hydrologic forecasts as inputs. A method is developed by using the forecast horizon point to divide the future time into two stages, the forecast lead-time and the unpredicted time. The risk within the forecast lead-time is computed based on counting the failure number of forecast scenarios, and the risk in the unpredicted time is estimated using reservoir routing with the design floods and the reservoir water levels of forecast horizon point. As a result, a two-stage risk analysis method is set up to quantify the entire flood risks by defining the ratio of the number of scenarios that excessive the critical value to the total number of scenarios. The China's Three Gorges Reservoir (TGR) is selected as a case study, where the parameter and precipitation uncertainties are implemented to produce ensemble-based hydrologic forecasts. The Bayesian inference, Markov Chain Monte Carlo, is used to account for the parameter uncertainty. Two reservoir operation schemes, the real operated and scenario optimization, are evaluated for the flood risks and hydropower profits analysis. With the 2010 flood, it is found that the improvement of the hydrologic forecast accuracy is unnecessary to decrease the reservoir real-time operation risk, and most risks are from the forecast lead-time. It is therefore valuable to decrease the avarice of ensemble-based hydrologic forecasts with less bias for a reservoir operational purpose.

  17. Evaluation of Maximum a Posteriori Estimation as Data Assimilation Method for Forecasting Infiltration-Inflow Affected Urban Runoff with Radar Rainfall Input

    DEFF Research Database (Denmark)

    Wied Pedersen, Jonas; Lund, Nadia Schou Vorndran; Borup, Morten

    2016-01-01

    High quality on-line flow forecasts are useful for real-time operation of urban drainage systems and wastewater treatment plants. This requires computationally efficient models, which are continuously updated with observed data to provide good initial conditions for the forecasts. This paper...... period of time that precedes the forecast. The method is illustrated for an urban catchment, where flow forecasts of 0–4 h are generated by applying a lumped linear reservoir model with three cascading reservoirs. Radar rainfall observations are used as input to the model. The effects of different prior...

  18. Why preferring parametric forecasting to nonparametric methods?

    Science.gov (United States)

    Jabot, Franck

    2015-05-07

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

  19. Global Energy Forecasting Competition 2012

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2014-01-01

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

  20. The Forecast Performance of Competing Implied Volatility Measures

    DEFF Research Database (Denmark)

    Tsiaras, Leonidas

    volatility (CIV) measures are explored. For all pair-wise comparisons, it is found that a CIV measure that is closely related to the model-free implied volatility, nearly always delivers the most accurate forecasts for the majority of the firms. This finding remains consistent for different forecast horizons......, volatility definitions, loss functions and forecast evaluation settings....

  1. An Overview of Short-term Statistical Forecasting Methods

    DEFF Research Database (Denmark)

    Elias, Russell J.; Montgomery, Douglas C.; Kulahci, Murat

    2006-01-01

    An overview of statistical forecasting methodology is given, focusing on techniques appropriate to short- and medium-term forecasts. Topics include basic definitions and terminology, smoothing methods, ARIMA models, regression methods, dynamic regression models, and transfer functions. Techniques...... for evaluating and monitoring forecast performance are also summarized....

  2. Retirement Forecasting. Evaluation of Models Shows Need for Information on Forecast Accuracy. Volume I. Report to the Chairman, Subcommittee on Social Security and Income Maintenance Programs, Committee on Finance, United States Senate.

    Science.gov (United States)

    General Accounting Office, Washington, DC.

    The Government Accounting Office (GAO) reviewed 71 actuarial, behavioral, and economic models that are used for retirement forecasting, focusing on models of federal retirement program costs, civilian retirement decisions, and retirement income. GAO wished to determine to what extent the models have been documented, to what extent the models are…

  3. Evaluating gaze-based interface tools to facilitate point-and-select tasks with small targets

    DEFF Research Database (Denmark)

    Skovsgaard, Henrik; Mateo, Julio C.; Hansen, John Paulin

    2011-01-01

    Gaze interaction affords hands-free control of computers. Pointing to and selecting small targets using gaze alone is difficult because of the limited accuracy of gaze pointing. This is the first experimental comparison of gaze-based interface tools for small-target (e.g. <12 × 12 pixels) point-a...

  4. Improving Software Reliability Forecasting

    NARCIS (Netherlands)

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

    1996-01-01

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

  5. Medium-term hydrologic forecasting in mountain basins using forecasting of a mesoscale numerical weather model

    Science.gov (United States)

    Castro Heredia, L. M.; Suarez, F. I.; Fernandez, B.; Maass, T.

    2016-12-01

    For forecasting of water resources, weather outputs provide a valuable source of information which is available online. Compared to traditional ground-based meteorological gauges, weather forecasts data offer spatially and temporally continuous data not yet evaluated and used in the forecasting of water resources in mountainous regions in Chile. Nevertheless, the use of this non-conventional data has been limited or null in developing countries, basically because of the spatial resolution, despite the high potential in the management of water resources. The adequate incorporation of these data in hydrological models requires its evaluation while taking into account the features of river basins in mountainous regions. This work presents an integrated forecasting system which represents a radical change in the way of making the streamflow forecasts in Chile, where the snowmelt forecast is the principal component of water resources management. The integrated system is composed of a physically based hydrological model, which is the prediction tool itself, together with a methodology for remote sensing data gathering that allows feed the hydrological model in real time, and meteorological forecasts from NCEP-CFSv2. Previous to incorporation of meteorological forecasts into the hydrological model, the weather outputs were evaluated and downscaling using statistical downscaling methods. The hydrological forecasts were evaluated in two mountain basins in Chile for a term of six months for the snowmelt period. In every month an assimilation process was performed, and the hydrological forecast was improved. Each month, the snow cover area (from remote sensing) and the streamflow observed were used to assimilate the model parameters in order to improve the next hydrological forecast using meteorological forecasts. The operation of the system in real time shows a good agreement between the streamflow and the snow cover area observed. The hydrological model and the weather

  6. Call Forecasting for Inbound Call Center

    Directory of Open Access Journals (Sweden)

    Peter Vinje

    2009-01-01

    Full Text Available In a scenario of inbound call center customer service, the ability to forecast calls is a key element and advantage. By forecasting the correct number of calls a company can predict staffing needs, meet service level requirements, improve customer satisfaction, and benefit from many other optimizations. This project will show how elementary statistics can be used to predict calls for a specific company, forecast the rate at which calls are increasing/decreasing, and determine if the calls may stop at some point.

  7. Very Short-term Nonparametric Probabilistic Forecasting of Renewable Energy Generation - with Application to Solar Energy

    DEFF Research Database (Denmark)

    Golestaneh, Faranak; Pinson, Pierre; Gooi, Hoay Beng

    2016-01-01

    Due to the inherent uncertainty involved in renewable energy forecasting, uncertainty quantification is a key input to maintain acceptable levels of reliability and profitability in power system operation. A proposal is formulated and evaluated here for the case of solar power generation, when only...... approach to generate very short-term predictive densities, i.e., for lead times between a few minutes to one hour ahead, with fast frequency updates. We rely on an Extreme Learning Machine (ELM) as a fast regression model, trained in varied ways to obtain both point and quantile forecasts of solar power...... generation. Four probabilistic methods are implemented as benchmarks. Rival approaches are evaluated based on a number of test cases for two solar power generation sites in different climatic regions, allowing us to show that our approach results in generation of skilful and reliable probabilistic forecasts...

  8. Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-07-26

    In the traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of load forecasting technique can provide accurate prediction of load power that will happen in future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during the longer time period instead of using the snapshot of load at the time when the reconfiguration happens, and thus it can provide information to the distribution system operator (DSO) to better operate the system reconfiguration to achieve optimal solutions. Thus, this paper proposes a short-term load forecasting based approach for automatically reconfiguring distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with support vector regression (SVR) based forecaster and parallel parameters optimization. And the network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum loss at the future time. The simulation results validate and evaluate the proposed approach.

  9. Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-08-23

    In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operator can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.

  10. Forecasts of land uses

    Science.gov (United States)

    David N. Wear

    2013-01-01

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

  11. [Evaluation on the effect of Point of Decision Prompt to increase the use of stairs].

    Science.gov (United States)

    Li, Yu; Lv, Jun; Li, Li-ming

    2011-03-01

    To evaluate whether Point of Decision Prompt (PDP) could effectively increase the use of stairs in the Chinese university dormitory buildings. Number and certain features of students who used stairs and lifts were respectively recorded through observation in both buildings A (intervened) and building B (not intervened) simultaneously one week before the intervention (stage I), the first week after the intervention (stage II) and the fourth week after the intervention (stage III). Self-questionnaires were also used to evaluate the effect of the intervention program in building A. According to the observation, the overall stair-use in building A increased from 34.3% in stage I to 37.5% (P stair-use in building B between these three stages was not statistically significant. The change of the stair-use varied with different sexes, different directions (up or down) and different days (weekday or weekend). Data from the questionnaires showed that 97.3% of the students being surveyed reported that they had noticed the PDPs and 26.4% of whom reported that they had increased the frequency of stair-use. Results from the logistic analysis of the questionnaire showed that girls (OR = 8.78, 95%CI: 3.23 - 23.87, deff = 1.24) and those who lived under the fifth floor (OR = 2.78, 95%CI: 1.28 - 6.06, deff = 1.38) were more inclined to increase the stair-use. PDP could effectively increase the frequency of stair-use in the Chinese university dormitory buildings.

  12. Flight-Test Evaluation of Kinematic Precise Point Positioning of Small UAVs

    Directory of Open Access Journals (Sweden)

    Jason N. Gross

    2016-01-01

    Full Text Available An experimental analysis of Global Positioning System (GPS flight data collected onboard a Small Unmanned Aerial Vehicle (SUAV is conducted in order to demonstrate that postprocessed kinematic Precise Point Positioning (PPP solutions with precisions approximately 6 cm 3D Residual Sum of Squares (RSOS can be obtained on SUAVs that have short duration flights with limited observational periods (i.e., only ~≤5 minutes of data. This is a significant result for the UAV flight testing community because an important and relevant benefit of the PPP technique over traditional Differential GPS (DGPS techniques, such as Real-Time Kinematic (RTK, is that there is no requirement for maintaining a short baseline separation to a differential GNSS reference station. Because SUAVs are an attractive platform for applications such as aerial surveying, precision agriculture, and remote sensing, this paper offers an experimental evaluation of kinematic PPP estimation strategies using SUAV platform data. In particular, an analysis is presented in which the position solutions that are obtained from postprocessing recorded UAV flight data with various PPP software and strategies are compared to solutions that were obtained using traditional double-differenced ambiguity fixed carrier-phase Differential GPS (CP-DGPS. This offers valuable insight to assist designers of SUAV navigation systems whose applications require precise positioning.

  13. A spatial point pattern analysis in Drosophila blastoderm embryos evaluating the potential inheritance of transcriptional states.

    Directory of Open Access Journals (Sweden)

    Feng He

    Full Text Available The Drosophila blastoderm embryo undergoes rapid cycles of nuclear division. This poses a challenge to genes that need to reliably sense the concentrations of morphogen molecules to form desired expression patterns. Here we investigate whether the transcriptional state of hunchback (hb, a target gene directly activated by the morphogenetic protein Bicoid (Bcd, exhibits properties indicative of inheritance between mitotic cycles. To achieve this, we build a dataset of hb transcriptional states at the resolution of individual nuclei in embryos at early cycle 14. We perform a spatial point pattern (SPP analysis to evaluate the spatial relationships among the nuclei that have distinct numbers of hb gene copies undergoing active transcription in snapshots of embryos. Our statistical tests and simulation studies reveal properties of dispersed clustering for nuclei with both or neither copies of hb undergoing active transcription. Modeling of nuclear lineages from cycle 11 to cycle 14 suggests that these two types of nuclei can achieve spatial clustering when, and only when, the transcriptional states are allowed to propagate between mitotic cycles. Our results are consistent with the possibility where the positional information encoded by the Bcd morphogen gradient may not need to be decoded de novo at all mitotic cycles in the Drosophila blastoderm embryo.

  14. Evaluation of the removal of point-of-sale tobacco displays in Ireland.

    Science.gov (United States)

    McNeill, Ann; Lewis, Sarah; Quinn, Casey; Mulcahy, Maurice; Clancy, Luke; Hastings, Gerard; Edwards, Richard

    2011-03-01

    To evaluate the short-term impacts of removing point-of-sale tobacco displays in Ireland, implemented in July 2009. Retailer compliance was assessed using audit surveys in 2007, 2008 and 2009. Using a monthly survey of 1000 adults carried out since 2002, changes in smoking prevalence were assessed; attitudes were measured using extra questions added for a 10-month period before and after the law. Youth responses were assessed using a cohort of 180 13-15 year olds, interviewed in June and August 2009. Immediately following implementation, compliance was 97%. Support for the law increased among adults after implementation (58% Apr-Jun vs 66% Jul-Dec, p<0.001). Recall of displays decreased significantly for adults (49% to 22%; p<0.001), more so among teenagers (81% to 22%; p<0.001). There were no significant short-term changes in prevalence among youths or adults. The proportion of youths believing more than a fifth of children their age smoked decreased from 62% to 46%, p<0.001). Post-legislation, 14% of adult smokers thought the law had made it easier to quit smoking and 38% of teenagers thought it would make it easier for children not to smoke. Compliance was very high and the law was well supported. Recall of displays dropped significantly among adults and teenagers post-legislation and there were encouraging signs that the law helped de-normalise smoking.

  15. Evaluation of myofascial trigger points using infrared thermography: a critical review of the literature.

    Science.gov (United States)

    Dibai-Filho, Almir Vieira; Guirro, Rinaldo Roberto de Jesus

    2015-01-01

    The aim of this study was to review recent studies published on the use of infrared thermography for the assessment of myofascial trigger points (MTrPs). A search of the MEDLINE, CINAHL, PEDro, and SciELO databases was carried out between November 2012 and January 2013 for articles published in English, Portuguese, or Spanish from the year 2000 to 2012. Because of the nature of the included studies and the purpose of this review, the analysis of methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. The search retrieved 11 articles, 2 of which were excluded based on language (German and Chinese). Three were duplicated in different databases, 1 did not use infrared thermography for diagnostic purposes, and the other did not use infrared thermography to measure the skin temperature. Thus, the final sample was made up of 4 observational investigations: 3 comparative studies and 1 accuracy study. At present, there are few studies evaluating the accuracy and reliability of infrared thermography for the diagnosis and assessment of MTrPs. Of the few studies present, there is no agreement on skin temperature patterns in the presence of MTrPs. Copyright © 2015 National University of Health Sciences. Published by Elsevier Inc. All rights reserved.

  16. Evaluating operational specifications of point-of-care diagnostic tests: a standardized scorecard.

    Science.gov (United States)

    Lehe, Jonathan D; Sitoe, Nádia E; Tobaiwa, Ocean; Loquiha, Osvaldo; Quevedo, Jorge I; Peter, Trevor F; Jani, Ilesh V

    2012-01-01

    The expansion of HIV antiretroviral therapy into decentralized rural settings will increasingly require simple point-of-care (POC) diagnostic tests that can be used without laboratory infrastructure and technical skills. New POC test devices are becoming available but decisions around which technologies to deploy may be biased without systematic assessment of their suitability for decentralized healthcare settings. To address this, we developed a standardized, quantitative scorecard tool to objectively evaluate the operational characteristics of POC diagnostic devices. The tool scores devices on a scale of 1-5 across 30 weighted characteristics such as ease of use, quality control, electrical requirements, shelf life, portability, cost and service, and provides a cumulative score that ranks products against a set of ideal POC characteristics. The scorecard was tested on 19 devices for POC CD4 T-lymphocyte cell counting, clinical chemistry or hematology testing. Single and multi-parameter devices were assessed in each of test categories. The scores across all devices ranged from 2.78 to 4.40 out of 5. The tool effectively ranked devices within each category (p0.80; ptechnology. It is particularly relevant for countries and testing programs considering the adoption of new POC diagnostic tests.

  17. Communicating uncertainty in hydrological forecasts: mission impossible?

    OpenAIRE

    Ramos, M. H.; T. Mathevet; J. Thielen; Pappenberger, F.

    2010-01-01

    International audience; Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point...

  18. MP3DG-PCC, open source software framework for implementation and evaluation of point cloud compression

    NARCIS (Netherlands)

    R.N. Mekuria (Rufael); P.S. Cesar Garcia (Pablo Santiago)

    2016-01-01

    textabstractWe present MP3DG-PCC, an open source framework for design, implementation and evaluation of point cloud compression algorithms. The framework includes objective quality metrics, lossy and lossless anchor codecs, and a test bench for consistent comparative evaluation. The framework and

  19. Optimising seasonal streamflow forecast lead time for operational decision making in Australia

    Science.gov (United States)

    Schepen, Andrew; Zhao, Tongtiegang; Wang, Q. J.; Zhou, Senlin; Feikema, Paul

    2016-10-01

    Statistical seasonal forecasts of 3-month streamflow totals are released in Australia by the Bureau of Meteorology and updated on a monthly basis. The forecasts are often released in the second week of the forecast period, due to the onerous forecast production process. The current service relies on models built using data for complete calendar months, meaning the forecast production process cannot begin until the first day of the forecast period. Somehow, the bureau needs to transition to a service that provides forecasts before the beginning of the forecast period; timelier forecast release will become critical as sub-seasonal (monthly) forecasts are developed. Increasing the forecast lead time to one month ahead is not considered a viable option for Australian catchments that typically lack any predictability associated with snowmelt. The bureau's forecasts are built around Bayesian joint probability models that have antecedent streamflow, rainfall and climate indices as predictors. In this study, we adapt the modelling approach so that forecasts have any number of days of lead time. Daily streamflow and sea surface temperatures are used to develop predictors based on 28-day sliding windows. Forecasts are produced for 23 forecast locations with 0-14- and 21-day lead time. The forecasts are assessed in terms of continuous ranked probability score (CRPS) skill score and reliability metrics. CRPS skill scores, on average, reduce monotonically with increase in days of lead time, although both positive and negative differences are observed. Considering only skilful forecast locations, CRPS skill scores at 7-day lead time are reduced on average by 4 percentage points, with differences largely contained within +5 to -15 percentage points. A flexible forecasting system that allows for any number of days of lead time could benefit Australian seasonal streamflow forecast users by allowing more time for forecasts to be disseminated, comprehended and made use of prior to

  20. Hydroacoustic Evaluation of Juvenile Salmonid Passage and Distribution at Lookout Point Dam, 2010

    Energy Technology Data Exchange (ETDEWEB)

    Khan, Fenton; Johnson, Gary E.; Royer, Ida M.; Hughes, James S.; Fischer, Eric S.; Trott, Donna M.; Ploskey, Gene R.

    2011-07-01

    This report presents the results of an evaluation of juvenile salmonid passage and distribution at Lookout Point Dam (LOP) on the Middle Fork Willamette River. The study was conducted by the Pacific Northwest National Laboratory for the U.S. Army Corps of Engineers, Portland District (USACE). The goal of the study was to provide fish passage and distribution data to support decisions on long-term measures to enhance downstream passage at LOP and others dams in USACE’s Willamette Valley Project in response to the listing of Upper Willamette River Spring Chinook salmon (Oncorhynchus tshawytscha) and Upper Willamette River steelhead (O. mykiss) as threatened under the Endangered Species Act. During the year-long study period - February 1, 2010 to January 31, 2011the objectives of the hydroacoustic evaluation of fish passage and distribution at LOP were to: 1. Estimate passage rates, run timing, horizontal distribution, and diel distribution at turbine penstock intakes for smolt-size fish. 2. Estimate passage rates, run timing and diel distribution at turbine penstock intakes for small-size fish. 3. Estimate passage rates and run timing at the regulating outlets for smolt-size fish. 4. Estimate vertical distribution of smolt-size fish in the forebay near the upstream face of the dam. The fixed-location hydroacoustic technique was used to accomplish the objectives of this study. Transducers (420 kHz) were deployed in each penstock intake, above each RO entrance, and on the dam face; a total of nine transducers (2 single-beam and 7 split-beam) were used. We summarize the findings from the hydroacoustic evaluation of juvenile salmonid passage and distribution at LOP during February 2010 through January 2011 as follows. • Fish passage rates for smolt-size fish (> ~90 mm) were highest during December-January and lowest in mid-summer through early fall. • During the entire study period, an estimated total of 142,463 fish ± 4,444 (95% confidence interval) smolt

  1. Evaluation of spatial dependence of point spread function-based PET reconstruction using a traceable point-like 22Na source

    Directory of Open Access Journals (Sweden)

    Taisuke Murata

    2016-10-01

    Full Text Available Abstract Background The point spread function (PSF of positron emission tomography (PET depends on the position across the field of view (FOV. Reconstruction based on PSF improves spatial resolution and quantitative accuracy. The present study aimed to quantify the effects of PSF correction as a function of the position of a traceable point-like 22Na source over the FOV on two PET scanners with a different detector design. Methods We used Discovery 600 and Discovery 710 (GE Healthcare PET scanners and traceable point-like 22Na sources (<1 MBq with a spherical absorber design that assures uniform angular distribution of the emitted annihilation photons. The source was moved in three directions at intervals of 1 cm from the center towards the peripheral FOV using a three-dimensional (3D-positioning robot, and data were acquired over a period of 2 min per point. The PET data were reconstructed by filtered back projection (FBP, the ordered subset expectation maximization (OSEM, OSEM + PSF, and OSEM + PSF + time-of-flight (TOF. Full width at half maximum (FWHM was determined according to the NEMA method, and total counts in regions of interest (ROI for each reconstruction were quantified. Results The radial FWHM of FBP and OSEM increased towards the peripheral FOV, whereas PSF-based reconstruction recovered the FWHM at all points in the FOV of both scanners. The radial FWHM for PSF was 30–50 % lower than that of OSEM at the center of the FOV. The accuracy of PSF correction was independent of detector design. Quantitative values were stable across the FOV in all reconstruction methods. The effect of TOF on spatial resolution and quantitation accuracy was less noticeable. Conclusions The traceable 22Na point-like source allowed the evaluation of spatial resolution and quantitative accuracy across the FOV using different reconstruction methods and scanners. PSF-based reconstruction reduces dependence of the spatial resolution on the

  2. Options to Improve the Quality of Wind Generation Output Forecasting with the Use of Available Information as Explanatory Variables

    Directory of Open Access Journals (Sweden)

    Rafał Magulski

    2015-06-01

    Full Text Available Development of wind generation, besides its positive aspects related to the use of renewable energy, is a challenge from the point of view of power systems’ operational security and economy. The uncertain and variable nature of wind generation sources entails the need for the for the TSO to provide adequate reserves of power, necessary to maintain the grid’s stable operation, and the actors involved in the trading of energy from these sources incur additional of balancing unplanned output deviations. The paper presents the results of analyses concerning the options to forecast a selected wind farm’s output exercised by means of different methods of prediction, using a different range of measurement and forecasting data available on the farm and its surroundings. The analyses focused on the evaluation of forecast errors, and selection of input data for forecasting models and assessment of their impact on prediction quality improvement.

  3. Analytical evaluation of a new point of care system for measuring cardiac Troponin I.

    Science.gov (United States)

    Kemper, Danielle Wm; Semjonow, Veronique; de Theije, Femke; Keizer, Diederick; van Lippen, Lian; Mair, Johannes; Wille, Bernadette; Christ, Michael; Geier, Felicitas; Hausfater, Pierre; Pariente, David; Scharnhorst, Volkher; Curvers, Joyce; Nieuwenhuis, Jeroen

    2017-03-01

    Point-of-care cardiac troponin testing with adequate analytical performances has the potential to improve chest pain patients flow in the emergency department. We present the analytical evaluation of the newly developed Philips Minicare cTnI point-of-care immunoassay. Li-heparin whole blood and plasma were used to perform analytical studies. The sample type comparison study was performed at 4 different hospitals. The 99th percentile upper reference limit (URL) study was performed using Li-heparin plasma, Li-heparin whole blood and capillary blood samples from 750 healthy adults, aging from 18 to 86years. Limit of the blank, limit of detection and limit of quantitation at 20% coefficient of variation (CV) were determined to be 8.5ng/L, 18ng/L and 38ng/L respectively without significant differences between whole blood and plasma for LoQ. Cross-reactivity and interferences were minimal and no high-dose hook was observed. Total CV was found to be from 7.3% to 12% for cTnI concentrations between 109.6 and 6135.4ng/L. CV at the 99th percentile URL was 18.6%. The sample type comparison study between capillary blood, Li-heparin whole blood and Li-heparin plasma samples demonstrated correlation coefficients between 0.99 and 1.00 with slopes between 1.03 and 1.08. The method comparison between Minicare cTnI and Beckman Coulter Access, AccuTnI+3 demonstrated a correlation coefficient of 0.973 with a slope of 1.09. The 99th percentile URL of a healthy population was calculated to be 43ng/L with no significant difference between genders or sample types. The Minicare cTnI assay is a sensitive and precise, clinical usable test for determination of cTnI concentration that can be used in a near-patient setting as an aid in the diagnosis of acute myocardial infarction. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  4. Paranoia.Ada: A diagnostic program to evaluate Ada floating-point arithmetic

    Science.gov (United States)

    Hjermstad, Chris

    1986-01-01

    Many essential software functions in the mission critical computer resource application domain depend on floating point arithmetic. Numerically intensive functions associated with the Space Station project, such as emphemeris generation or the implementation of Kalman filters, are likely to employ the floating point facilities of Ada. Paranoia.Ada appears to be a valuabe program to insure that Ada environments and their underlying hardware exhibit the precision and correctness required to satisfy mission computational requirements. As a diagnostic tool, Paranoia.Ada reveals many essential characteristics of an Ada floating point implementation. Equipped with such knowledge, programmers need not tremble before the complex task of floating point computation.

  5. Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

    Science.gov (United States)

    Bell, Jordan R.; Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.

    2012-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the SPoRT-MODIS GVF dataset on a land surface model (LSM) apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. In the West, higher latent heat fluxes prevailed, which enhanced the rates of evapotranspiration and soil moisture depletion in the LSM. By late Summer and Autumn, both the average sensible and latent heat fluxes increased in the West as a result of the more rapid soil drying and higher coverage of GVF. The impacts of the SPoRT GVF dataset on NWP was also examined for a single severe weather case study using the Weather Research and Forecasting (WRF) model. Two separate coupled LIS/WRF model simulations were made for the 17 July 2010 severe weather event in the Upper Midwest using the NCEP and SPoRT GVFs, with all other model parameters remaining the same. Based on the sensitivity results, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and

  6. Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

    Science.gov (United States)

    Bell, Jordan R.; Case, Jonathan L.; Molthan, Andrew L.

    2011-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center develops new products and techniques that can be used in operational meteorology. The majority of these products are derived from NASA polar-orbiting satellite imagery from the Earth Observing System (EOS) platforms. One such product is a Greenness Vegetation Fraction (GVF) dataset, which is produced from Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the new SPoRT-MODIS GVF dataset on land surface models apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. The second phase of the project is to examine the impacts of the SPoRT GVF dataset on NWP using the Weather Research and Forecasting (WRF) model. Two separate WRF model simulations were made for individual severe weather case days using the NCEP GVF (control) and SPoRT GVF (experimental), with all other model parameters remaining the same. Based on the sensitivity results in these case studies, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and lower direct surface heating, which typically resulted in lower (higher) predicted 2-m temperatures (2-m dewpoint temperatures). The opposite was true

  7. Post-Processing of NWP Models Forecasts: Case of Denmark and Greenland

    Science.gov (United States)

    Mahura, Alexander; Petersen, Claus; Amstrup, Bjarne; Stig Andersen, Bjarne; Hansen Sass, Bent

    2016-04-01

    Any Numerical Weather Prediction (NWP) model generates forecasts with some degree of accuracy. Although NWP forecasts are continuously improving through more advanced model resolutions, refining existing and developing new parameterizations for physical processes, detalization of land-cover/use properties, etc. the verification results show that forecasts still have errors. As a possible solution, statistical corrections to forecasts can be applied. For that, in our study, the developed method uses forecasted meteorological parameters (2m air, dew point, and surface temperatures as well as 10m wind speed) and observations covering only a pre-historical period (up to 30 days). For faster calculations, the singular value decomposition method is applied. Afterwards, additional improvement/adjustment of forecasts is based on generated statistics of forecasted meteorological parameters. The DMI operationally runs two NWP models - HIRLAM (HIgh Resolution Limited Area Model) and HARMONIE (Hirlam Aladin Regional/Meso-scale Operational NWP In Europe) for domains with Denmark and Greenland in focus. The HIRLAM-SKA model is run for Denmark at about 3 km horizontal resolution, and HIRLAM-K05 model is run for Greenland at 5 km horizontal resolution (these models runs are performed at 00, 06, 12, and 18 UTC). The HARMONIE-GLB is run for Greenland at 2.5 km horizontal resolution (runs at 03, 09, 15, and 21 UTC); and HARMONIE-DKA is run for Denmark at 2.5 km as well (at 00, 03, 06, 09, 12, 15, 18, and 21 UTCs). The statistical procedure (so-called NWPStatCor) for correction of the air temperature and wind speed forecasts is running for all models outputs covering 48 h forecast length. For each synoptical station, the steps are extraction of both observation and model forecast data, assigning these data to corresponding forecast lengths, calculation of statistical correction and evaluation of model performance (before vs. after correction applied). Long-term month

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

    Science.gov (United States)

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

    2009-09-01

    The DMI has in collaboration with the Danish Road Directorate (DRD) for almost two decades used a Road Condition Model (RCM) system (based on a dense road observations network and the numerical weather prediction model - HIgh Resolution Limited Area Model, HIRLAM) to provide operational forecasts of main road conditions at selected road stations of the Danish road network. As of Jan 2009, there are 357 road stations (equipped in total with 456 sensors), where measurements and forecasts of road surface temperature, air and dew point temperatures are conducted. Forecasts of other important meteorological parameters such as cloud cover and precipitations as well as radar and satellite images are also distributed to the users through the web-based interface vejvejr.dk and through DMI and DRD web-pages. For icing conditions, new technology has made it easy to vary the dose of spreaded salt, making it possible to use salt only on the parts of the road network where it is really needed. In our study measurements of road surface temperature from road stations and salt spreaders have additionally been used to examine both road stations and road stretches forecasts along the main roads of the Danish Road Network (accounting almost 23 thousand points located at distances of 250 m). These results showed critical importance of availability of detailed characteristics of the roads surroundings. To make local forecasts in a specific point all possible local detailed information is needed. Since high resolution models running at faster supercomputers as well as detailed physiographic datasets now are available, it is possible to improve the modelling and parameterization of significant physical processes influencing the formation of the slippery road conditions. First of all, it is based on a new dataset available from Kort og Matrikel styrelsen, the so-called Danish Height Model (Danmarks Højdemodel) which is a very detailed set of data with horizontal resolution of a few meters

  9. Analysis of mesoscale forecasts using ensemble methods

    CERN Document Server

    Gross, Markus

    2016-01-01

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

  10. Engaging Earth- and Environmental-Science Undergraduates Through Weather Discussions and an eLearning Weather Forecasting Contest

    Science.gov (United States)

    Schultz, David M.; Anderson, Stuart; Seo-Zindy, Ryo

    2013-06-01

    For students who major in meteorology, engaging in weather forecasting can motivate learning, develop critical-thinking skills, improve their written communication, and yield better forecasts. Whether such advances apply to students who are not meteorology majors has been less demonstrated. To test this idea, a weather discussion and an eLearning weather forecasting contest were devised for a meteorology course taken by third-year undergraduate earth- and environmental-science students. The discussion consisted of using the recent, present, and future weather to amplify the topics of the week's lectures. Then, students forecasted the next day's high temperature and the probability of precipitation for Woodford, the closest official observing site to Manchester, UK. The contest ran for 10 weeks, and the students received credit for participation. The top students at the end of the contest received bonus points on their final grade. A Web-based forecast contest application was developed to register the students, receive their forecasts, and calculate weekly standings. Students who were successful in the forecast contest were not necessarily those who achieved the highest scores on the tests, demonstrating that the contest was possibly testing different skills than traditional learning. Student evaluations indicate that the weather discussion and contest were reasonably successful in engaging students to learn about the weather outside of the classroom, synthesize their knowledge from the lectures, and improve their practical understanding of the weather. Therefore, students taking a meteorology class, but not majoring in meteorology, can derive academic benefits from weather discussions and forecast contests. Nevertheless, student evaluations also indicate that better integration of the lectures, weather discussions, and the forecasting contests is necessary.

  11. Interior Point Method Evaluation for Reactive Power Flow Optimization in the Power System

    Directory of Open Access Journals (Sweden)

    Zbigniew Lubośny

    2013-03-01

    Full Text Available The paper verifies the performance of an interior point method in reactive power flow optimization in the power system. The study was conducted on a 28 node CIGRE system, using the interior point method optimization procedures implemented in Power Factory software.

  12. Design, implementation and evaluation of a point cloud codec for Tele-Immersive Video

    NARCIS (Netherlands)

    R.N. Mekuria (Rufael); C.L. Blom (Kees); P.S. Cesar Garcia (Pablo Santiago)

    2017-01-01

    htmlabstractwe present a generic and real-time time-varying point cloud codec for 3D immersive video. This codec is suitable for mixed reality applications where 3D point clouds are acquired at a fast rate. In this codec, intra frames are coded progressively in an octree subdivision. To further

  13. Evaluation of two devices for point-of-care testing of haemoglobin in neonatal pigs.

    Science.gov (United States)

    Kutter, Annette P N; Mauch, Jacqueline Y; Riond, Barbara; Martin-Jurado, Olga; Spielmann, Nelly; Weiss, Markus; Bettschart-Wolfensberger, Regula

    2012-01-01

    In veterinary medicine, point-of-care testing (POCT) techniques have become popular, since they provide immediate results and only small amounts of blood are needed. However, their accuracy is controversial. Pigs are often used for research purposes and accurate measurement of haemoglobin (Hb) is important during invasive procedures. The aim of this study was to evaluate two different Hb POCT devices in neonatal pigs. A prospective study with 57 pigs of 3-6 weeks of age, weighing 4.1-6.2 kg (median 5.1 kg) was performed. Fifty-seven blood samples were analysed for Hb using a conductivity-based and a photometrical POCT device and compared with a photometrical reference method. Statistical analysis was performed with Bland-Altman analysis, Spearman correlation and Passing-Bablok regression analysis. Hb values ranged from 32 to 108 g/L (median 80 g/L) using the reference method. The bias of the photometrical method (HemoCue(®)) to the reference method was -1 g/L, with limits of agreement (LOA) of -7 to 6 g/L. The conductivity-based method (i-STAT(®)) had a bias of -15 g/L with LOA from -24 to -6 g/L. There was a significant association between protein values and the bias of i-STAT versus CellDyn (r(2) = 0.27, P CellDyn (r(2) = 0.001, P = 0.79). The lower the protein values were, the lower the Hb values were measured by the i-STAT. The conductivity-based measurement of Hb constantly underestimated Hb values, whereas the photometrical method demonstrated a better accuracy and is therefore more reliable for on-site measurement of Hb in pigs.

  14. Point-of-Sale Tobacco Advertising and Display Bans: Policy Evaluation Study in Five Russian Cities.

    Science.gov (United States)

    Kennedy, Ryan David; Grant, Ashley; Spires, Mark; Cohen, Joanna E

    2017-08-15

    The tobacco industry uses point-of-sale (POS) advertising, promotion, and product display to increase consumption of its products among current users, to attract new consumers, and to encourage former customers to resume tobacco use. As part of a comprehensive tobacco control effort, Russia-having one of the highest tobacco use prevalence rates in the world-enacted legislation that banned tobacco POS advertising, effective November 15, 2013, and banned the display of tobacco and the sale of cigarettes in kiosks, effective June 1, 2014. The objective of the study was to evaluate the implementation of the national law by assessing the state of POS advertising, promotion, and product display, and sales in kiosks across Russia. Two waves of observations were conducted to measure compliance with the POS restrictions: wave 1 took place in April-May 2014 after the advertising ban was in effect and again in August-September 2014 after the display ban and elimination of tobacco sales in kiosks came into effect. Observations were conducted by local trained staff that traveled to 5 populous cities in different regions of Russia (Moscow, St. Petersburg, Kazan, Ekaterinburg, and Novosibirsk). Staff followed a published POS evaluation protocol and used mobile phones to collect data. Observations were conducted in a roughly equal number of supermarket chains, convenience stores, and kiosks. Observed items included advertising at POS, product displays, and cigarette sales in kiosks. Observations were made in 780 venues in wave 1 and in 779 revisited venues in wave 2. In wave 1, approximately a third of supermarkets and convenience stores (34.2%, 184/538) were advertising cigarettes using light boxes, and over half of observed venues (54.3%, 292/538) had signage such as banners or shelf liners that used colors or images related to cigarette brands. Product displays were common in wave 1. In wave 2, compliance with advertising restrictions was very good: there were virtually no

  15. Point-of-Sale Tobacco Advertising and Display Bans: Policy Evaluation Study in Five Russian Cities

    Science.gov (United States)

    Grant, Ashley; Spires, Mark; Cohen, Joanna E

    2017-01-01

    Background The tobacco industry uses point-of-sale (POS) advertising, promotion, and product display to increase consumption of its products among current users, to attract new consumers, and to encourage former customers to resume tobacco use. As part of a comprehensive tobacco control effort, Russia—having one of the highest tobacco use prevalence rates in the world—enacted legislation that banned tobacco POS advertising, effective November 15, 2013, and banned the display of tobacco and the sale of cigarettes in kiosks, effective June 1, 2014. Objective The objective of the study was to evaluate the implementation of the national law by assessing the state of POS advertising, promotion, and product display, and sales in kiosks across Russia. Methods Two waves of observations were conducted to measure compliance with the POS restrictions: wave 1 took place in April-May 2014 after the advertising ban was in effect and again in August-September 2014 after the display ban and elimination of tobacco sales in kiosks came into effect. Observations were conducted by local trained staff that traveled to 5 populous cities in different regions of Russia (Moscow, St. Petersburg, Kazan, Ekaterinburg, and Novosibirsk). Staff followed a published POS evaluation protocol and used mobile phones to collect data. Observations were conducted in a roughly equal number of supermarket chains, convenience stores, and kiosks. Observed items included advertising at POS, product displays, and cigarette sales in kiosks. Results Observations were made in 780 venues in wave 1 and in 779 revisited venues in wave 2. In wave 1, approximately a third of supermarkets and convenience stores (34.2%, 184/538) were advertising cigarettes using light boxes, and over half of observed venues (54.3%, 292/538) had signage such as banners or shelf liners that used colors or images related to cigarette brands. Product displays were common in wave 1. In wave 2, compliance with advertising restrictions

  16. How is the weather? Forecasting inpatient glycemic control.

    Science.gov (United States)

    Saulnier, George E; Castro, Janna C; Cook, Curtiss B; Thompson, Bithika M

    2017-11-01

    Apply methods of damped trend analysis to forecast inpatient glycemic control. Observed and calculated point-of-care blood glucose data trends were determined over 62 weeks. Mean absolute percent error was used to calculate differences between observed and forecasted values. Comparisons were drawn between model results and linear regression forecasting. The forecasted mean glucose trends observed during the first 24 and 48 weeks of projections compared favorably to the results provided by linear regression forecasting. However, in some scenarios, the damped trend method changed inferences compared with linear regression. In all scenarios, mean absolute percent error values remained below the 10% accepted by demand industries. Results indicate that forecasting methods historically applied within demand industries can project future inpatient glycemic control. Additional study is needed to determine if forecasting is useful in the analyses of other glucometric parameters and, if so, how to apply the techniques to quality improvement.

  17. Comparison of Agricultural Forecasts with Actual Data

    Directory of Open Access Journals (Sweden)

    Y.A. Alseleem

    2001-01-01

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

  18. Laboratory evaluation of the pointing stability of the ASPS Vernier System

    Science.gov (United States)

    1980-01-01

    The annular suspension and pointing system (ASPS) is an end-mount experiment pointing system designed for use in the space shuttle. The results of the ASPS Vernier System (AVS) pointing stability tests conducted in a laboratory environment are documented. A simulated zero-G suspension was used to support the test payload in the laboratory. The AVS and the suspension were modelled and incorporated into a simulation of the laboratory test. Error sources were identified and pointing stability sensitivities were determined via simulation. Statistical predictions of laboratory test performance were derived and compared to actual laboratory test results. The predicted mean pointing stability during simulated shuttle disturbances was 1.22 arc seconds; the actual mean laboratory test pointing stability was 1.36 arc seconds. The successful prediction of laboratory test results provides increased confidence in the analytical understanding of the AVS magnetic bearing technology and allows confident prediction of in-flight performance. Computer simulations of ASPS, operating in the shuttle disturbance environment, predict in-flight pointing stability errors less than 0.01 arc seconds.

  19. Performance Evaluation of Different Ground Filtering Algorithms for Uav-Based Point Clouds

    Science.gov (United States)

    Serifoglu, C.; Gungor, O.; Yilmaz, V.

    2016-06-01

    Digital Elevation Model (DEM) generation is one of the leading application areas in geomatics. Since a DEM represents the bare earth surface, the very first step of generating a DEM is to separate the ground and non-ground points, which is called ground filtering. Once the point cloud is filtered, the ground points are interpolated to generate the DEM. LiDAR (Light Detection and Ranging) point clouds have been used in many applications thanks to their success in representing the objects they belong to. Hence, in the literature, various ground filtering algorithms have been reported to filter the LiDAR data. Since the LiDAR data acquisition is still a costly process, using point clouds generated from the UAV images to produce DEMs is a reasonable alternative. In this study, point clouds with three different densities were generated from the aerial photos taken from a UAV (Unmanned Aerial Vehicle) to examine the effect of point density on filtering performance. The point clouds were then filtered by means of five different ground filtering algorithms as Progressive Morphological 1D (PM1D), Progressive Morphological 2D (PM2D), Maximum Local Slope (MLS), Elevation Threshold with Expand Window (ETEW) and Adaptive TIN (ATIN). The filtering performance of each algorithm was investigated qualitatively and quantitatively. The results indicated that the ATIN and PM2D algorithms showed the best overall ground filtering performances. The MLS and ETEW algorithms were found as the least successful ones. It was concluded that the point clouds generated from the UAVs can be a good alternative for LiDAR data.

  20. Design and evaluation of aircraft heat source systems for use with high-freezing point fuels

    Science.gov (United States)

    Pasion, A. J.

    1979-01-01

    The objectives were the design, performance and economic analyses of practical aircraft fuel heating systems that would permit the use of high freezing-point fuels on long-range aircraft. Two hypothetical hydrocarbon fuels with freezing points of -29 C and -18 C were used to represent the variation from current day jet fuels. A Boeing 747-200 with JT9D-7/7A engines was used as the baseline aircraft. A 9300 Km mission was used as the mission length from which the heat requirements to maintain the fuel above its freezing point was based.

  1. National Weather Service Forecast Reference Evapotranspiration

    Science.gov (United States)

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

    2013-12-01

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

  2. Weather forecasting based on hybrid neural model

    Science.gov (United States)

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

    2017-02-01

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

  3. Weather forecasting based on hybrid neural model

    Science.gov (United States)

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

    2017-11-01

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

  4. Comparison between stochastic and machine learning methods for hydrological multi-step ahead forecasting: All forecasts are wrong!

    Science.gov (United States)

    Papacharalampous, Georgia; Tyralis, Hristos; Koutsoyiannis, Demetris

    2017-04-01

    compared to simpler methods. It is pointed out that the ML methods do not differ dramatically from the stochastic methods, while it is interesting that the NN, RF and SVM algorithms used in this study offer potentially very good performance in terms of accuracy. It should be noted that, although this study focuses on hydrological processes, the results are of general scientific interest. Another important point in this study is the use of several methods and metrics. Using fewer methods and fewer metrics would have led to a very different overall picture, particularly if those fewer metrics corresponded to fewer criteria. For this reason, we consider that the proposed methodology is appropriate for the evaluation of forecasting methods.

  5. Verification of rainfall forecasts for the Vaal Dam catchment for the ...

    African Journals Online (AJOL)

    Rainfall forecasts compiled by the South African Weather Service (SAWS) are used daily by agriculture, industry, sportsmen and the general public. Because of the importance of the rainfall forecast, it is of considerable interest to know how reliable these forecasts are. The SAWS evaluates the rainfall forecasts issued by the ...

  6. How to compare what seems incomparable in seasonal hydrological forecasting?

    Science.gov (United States)

    Crochemore, Louise; Pechlivanidis, Ilias; Ramos, Maria-Helena

    2017-04-01

    A number of climate forecasting systems have been developed at the global scale allowing the production of seasonal hydrological services at the regional, national and continental scales. With these services becoming increasingly available to dissemination institutes and occasionally directly to the public, forecasters have been requesting information on the reliability of the forecasts, particularly when they need to select one system for a specific application. The quality of the forecasts depends on the hydrological model used and, consequently, on its setup, structure, objective, and performance. These characteristics can be very different among models, adding a degree of complexity to any model output inter-comparison analysis. Here, we propose a framework to compare outputs from different modelling systems. We compare the seasonal streamflow forecasts produced by a continentally-calibrated complex model (E-HYPE) and a regionally-calibrated parsimonious model (GR6J) to forecast streamflow in a set of French catchments. Streamflow forecasts are obtained by using bias adjusted ECMWF System 4 seasonal precipitation and temperature forecasts as input to the E-HYPE and GR6J hydrological models. We first identify within the forecasting chain the origin of the differences between the two hydrological systems. We use the evaluation of forecast skill to highlight and isolate the differences in meteorological forcing, initial hydrological conditions and historical model performance, respectively. Forecast skill is thus evaluated by considering different benchmarks based on: i) historical observed streamflow, ii) historical simulated streamflow, and iii) the Extended Streamflow Prediction (ESP) system which uses meteorological climatology as input to the hydrological models. We also present the dependence of forecast quality (i.e., sharpness and reliability) on the hydrological models used. Lastly, we assess the impact of the two different model structures on forecast

  7. Evaluating the change of directional patterns for fingerprints with missing singular points under rotation

    CSIR Research Space (South Africa)

    Dorasamy, Kribashnee

    2016-12-01

    Full Text Available Overcoming small inter-class variation when fingerprints have missing singular points (SPs) is one of the current challenges faced in fingerprint classification, since class information is scarce. Grouping the orientation fields to form Directional...

  8. Forecasters priorities for improving probabilistic flood forecasts

    Science.gov (United States)

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

    2013-02-01

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

  9. Assessment of buildings with ventilated facade systems and evaluation of point thermal bridges

    OpenAIRE

    Šadauskienė, Jolanta; Šeduikytė, Lina; Juozas RAMANAUSKAS; Buska, Andrius

    2017-01-01

    Analyzes of influence of the point thermal bridges of buildings with ventilated facade systems on the thermal properties of envelops are presented in the paper. The relation between the separate components of the envelop were made: thermal properties and thickness of supporting wall's layer; value of thermal conductivity and thickness of insulation layer. Studies have shown, that the value of the point thermal transmittance, which depended on the thermal properties of the envelop and thicknes...

  10. Prospective Tests of Southern California Earthquake Forecasts

    Science.gov (United States)

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

    2004-12-01

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

  11. Field evaluation of a prototype paper-based point-of-care fingerstick transaminase test.

    Directory of Open Access Journals (Sweden)

    Nira R Pollock

    Full Text Available Monitoring for drug-induced liver injury (DILI via serial transaminase measurements in patients on potentially hepatotoxic medications (e.g., for HIV and tuberculosis is routine in resource-rich nations, but often unavailable in resource-limited settings. Towards enabling universal access to affordable point-of-care (POC screening for DILI, we have performed the first field evaluation of a paper-based, microfluidic fingerstick test for rapid, semi-quantitative, visual measurement of blood alanine aminotransferase (ALT. Our objectives were to assess operational feasibility, inter-operator variability, lot variability, device failure rate, and accuracy, to inform device modification for further field testing. The paper-based ALT test was performed at POC on fingerstick samples from 600 outpatients receiving HIV treatment in Vietnam. Results, read independently by two clinic nurses, were compared with gold-standard automated (Roche Cobas results from venipuncture samples obtained in parallel. Two device lots were used sequentially. We demonstrated high inter-operator agreement, with 96.3% (95% C.I., 94.3-97.7% agreement in placing visual results into clinically-defined "bins" (5x upper limit of normal, >90% agreement in validity determination, and intraclass correlation coefficient of 0.89 (95% C.I., 0.87-0.91. Lot variability was observed in % invalids due to hemolysis (21.1% for Lot 1, 1.6% for Lot 2 and correlated with lots of incorporated plasma separation membranes. Invalid rates <1% were observed for all other device controls. Overall bin placement accuracy for the two readers was 84% (84.3%/83.6%. Our findings of extremely high inter-operator agreement for visual reading-obtained in a target clinical environment, as performed by local practitioners-indicate that the device operation and reading process is feasible and reproducible. Bin placement accuracy and lot-to-lot variability data identified specific targets for device optimization and

  12. [Process and key points of clinical literature evaluation of post-marketing traditional Chinese medicine].

    Science.gov (United States)

    Liu, Huan; Xie, Yanming

    2011-10-01

    The clinical literature evaluation of the post-marketing traditional Chinese medicine is a comprehensive evaluation by the comprehensive gain, analysis of the drug, literature of drug efficacy, safety, economy, based on the literature evidence and is part of the evaluation of evidence-based medicine. The literature evaluation in the post-marketing Chinese medicine clinical evaluation is in the foundation and the key position. Through the literature evaluation, it can fully grasp the information, grasp listed drug variety of traditional Chinese medicines second development orientation, make clear further clinical indications, perfect the medicines, etc. This paper discusses the main steps and emphasis of the clinical literature evaluation. Emphasizing security literature evaluation should attach importance to the security of a comprehensive collection drug information. Safety assessment should notice traditional Chinese medicine validity evaluation in improving syndrome, improveing the living quality of patients with special advantage. The economics literature evaluation should pay attention to reliability, sensitivity and practicability of the conclusion.

  13. Spatio‐temporal analysis and modeling of short‐term wind power forecast errors

    DEFF Research Database (Denmark)

    Tastu, Julija; Pinson, Pierre; Kotwa, Ewelina

    2011-01-01

    Forecasts of wind power production are increasingly being used in various management tasks. So far, such forecasts and related uncertainty information have usually been generated individually for a given site of interest (either a wind farm or a group of wind farms), without properly accounting...... for the spatio‐temporal dependencies observed in the wind generation field. However, it is intuitively expected that, owing to the inertia of meteorological forecasting systems, a forecast error made at a given point in space and time will be related to forecast errors at other points in space in the following...... forecast errors are proposed, and their ability to mimic this structure is discussed. The best performing model is shown to explain 54% of the variations of the forecast errors observed for the individual forecasts used today. Even though focus is on 1‐h‐ahead forecast errors and on western Denmark only...

  14. Error analysis for Winters' Additive Seasonal Forecasting System

    OpenAIRE

    McKenzie, Edward

    1984-01-01

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

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

    Science.gov (United States)

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

    2014-05-01

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

  16. Hydroacoustic Evaluation of Juvenile Salmonid Passage and Distribution at Lookout Point Dam, 2010

    Energy Technology Data Exchange (ETDEWEB)

    Khan, Fenton; Johnson, Gary E.; Royer, Ida M.; Hughes, James S.; Fischer, Eric S.; Trott, Donna M.; Ploskey, Gene R.

    2012-05-31

    Pacific Northwest National Laboratory evaluated juvenile salmonid passage and distribution at Lookout Point Dam (LOP) on the Middle Fork Willamette River for the U.S. Army Corps of Engineers, Portland District (USACE), to provide data to support decisions on long-term measures to enhance downstream passage at LOP and others dams in USACE's Willamette Valley Project. This study was conducted in response to the listing of Upper Willamette River Spring Chinook salmon (Oncorhynchus tshawytscha) and Upper Willamette River steelhead (O. mykiss) as threatened under the Endangered Species Act. We conducted a hydroacoustic evaluation of juvenile salmonid passage and distribution at LOP during February 2010 through January 2011. Findings from this 1 year of study should be applied carefully because annual variation can be expected due to variability in adult salmon escapement, egg-to-fry and fry-to-smolt survival rates, reservoir rearing and predation, dam operations, and weather. Fish passage rates for smolt-size fish (> {approx}90 mm and < 300 mm) were highest during December-January and lowest in mid-summer through early fall. Passage peaks were also evident in early spring, early summer, and late fall. During the entire study period, an estimated total of 142,463 fish {+-} 4,444 (95% confidence interval) smolt-size fish passed through turbine penstock intakes. Of this total, 84% passed during December-January. Run timing for small-size fish ({approx}65-90 mm) peaked (702 fish) on December 18. Diel periodicity of smolt-size fish showing crepuscular peaks was evident in fish passage into turbine penstock intakes. Relatively few fish passed into the Regulating Outlets (ROs) when they were open in summer (2 fish/d) and winter (8 fish/d). Overall, when the ROs were open, RO efficiency (RO passage divided by total project passage) was 0.004. In linear regression analyses, daily fish passage (turbines and ROs combined) for smolt-size fish was significantly related to

  17. Performance and diagnostic evaluation of ozone predictions by the Eta-Community Multiscale Air Quality Forecast System during the 2002 New England Air Quality Study.

    Science.gov (United States)

    Yu, Shaocai; Mathur, Rohit; Kang, Daiwen; Schere, Kenneth; Eder, Brian; Pleim, Jonathan

    2006-10-01

    A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O3) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O3 was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O3 on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O3 concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O3 very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within +/- 20%. The model reproduced 53.3% of the observed hourly O3 within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites. The comparison of modeled and observed lidar O3 vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64-77% of observed NO2 photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O3/nitrogen oxide (NOx) ratios suggests that the site is mainly under strongly NOx-sensitive conditions (>53%). It was found that the modeled lower limits of the O3 production efficiency values (inferred from O3-CO correlation) are close to the observations.

  18. Statistical Flood Forecasting for the Mekong River

    Science.gov (United States)

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

    2009-04-01

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

  19. Improving weather forecasts for wind energy applications

    Energy Technology Data Exchange (ETDEWEB)

    Kay, Merlinde [School of Photovoltaic and Renewable Energy Engineering and Centre for Energy and Environmental Markets, University of New South Wales, Sydney, NSW 2052 (Australia); MacGill, Iain, E-mail: m.kay@unsw.edu.a [School of Electrical Engineering and Telecommunications, and Centre for Energy and Environmental Markets, University of New South Wales, Sydney, NSW 2052 (Australia)

    2010-08-15

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

  20. Severe Weather Forecast Decision Aid

    Science.gov (United States)

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

    2005-01-01

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

  1. Commuter Airline Forecasts,

    Science.gov (United States)

    1981-05-01

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

  2. Forecaster priorities for improving probabilistic flood forecasts

    Science.gov (United States)

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

    2014-05-01

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

  3. Breadth of Coverage, Ease of Use, and Quality of Mobile Point-of-Care Tool Information Summaries: An Evaluation.

    Science.gov (United States)

    Johnson, Emily; Emani, Vamsi K; Ren, Jinma

    2016-10-12

    With advances in mobile technology, accessibility of clinical resources at the point of care has increased. The objective of this research was to identify if six selected mobile point-of-care tools meet the needs of clinicians in internal medicine. Point-of-care tools were evaluated for breadth of coverage, ease of use, and quality. Six point-of-care tools were evaluated utilizing four different devices (two smartphones and two tablets). Breadth of coverage was measured using select International Classification of Diseases, Ninth Revision, codes if information on summary, etiology, pathophysiology, clinical manifestations, diagnosis, treatment, and prognosis was provided. Quality measures included treatment and diagnostic inline references and individual and application time stamping. Ease of use covered search within topic, table of contents, scrolling, affordance, connectivity, and personal accounts. Analysis of variance based on the rank of score was used. Breadth of coverage was similar among Medscape (mean 6.88), Uptodate (mean 6.51), DynaMedPlus (mean 6.46), and EvidencePlus (mean 6.41) (P>.05) with DynaMed (mean 5.53) and Epocrates (mean 6.12) scoring significantly lower (PUpToDate and DynaMedPlus allow for search within a topic. All point-of-care tools have remote access with the exception of UpToDate and Essential Evidence Plus. All tools except Medscape covered criteria for quality evaluation. Overall, there was no significant difference between the point-of-care tools with regard to coverage on common topics used by internal medicine clinicians. Selection of point-of-care tools is highly dependent on individual preference based on ease of use and cost of the application.

  4. Inaccuracy in traffic forecasts

    DEFF Research Database (Denmark)

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

    2006-01-01

    This paper presents results from the first statistically significant study of traffic forecasts in transportation infrastructure projects. The sample used is the largest of its kind, covering 210 projects in 14 nations worth US$58 billion. The study shows with very high statistical significance...... that forecasters generally do a poor job of estimating the demand for transportation infrastructure projects. The result is substantial downside financial and economic risk. Forecasts have not become more accurate over the 30-year period studied. If techniques and skills for arriving at accurate demand forecasts...

  5. Steam coal forecaster

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-07-01

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

  6. Flood Forecasting in River System Using ANFIS

    Science.gov (United States)

    Ullah, Nazrin; Choudhury, P.

    2010-10-01

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

  7. Evaluation of Escherichia coli as indicator of point-of-use ...

    African Journals Online (AJOL)

    In this study, the relevance of the presence of Escherichia coli in drinking water as an indicator of point-of-use chlorination efficiency is examined. The survival of clinical isolates of human enteric pathogenic bacteria (Klebsiella pneumoniae, Pseudomonas aeruginosa, Salmonella typhi, Shigella dysenteriae, Staphylococcus ...

  8. Evaluating 5 and 8 pH-point titrations for measuring VFA in full-scale ...

    African Journals Online (AJOL)

    2012-02-24

    Feb 24, 2012 ... results were compared for tap water and primary treated wastewater at the laboratory scale. ... Keywords: Multiple pH-point titration, volatile fatty acids, wastewater, full-scale, primary sludge hydrolysis. Introduction. At wastewater .... were filtered through a cellulose filter and analysed for NH4-N,. PO4-P, SO4.

  9. Correlation between Grade Point Averages and Student Evaluation of Teaching Scores: Taking a Closer Look

    Science.gov (United States)

    Griffin, Tyler J.; Hilton, John, III.; Plummer, Kenneth; Barret, Devynne

    2014-01-01

    One of the most contentious potential sources of bias is whether instructors who give higher grades receive higher ratings from students. We examined the grade point averages (GPAs) and student ratings across 2073 general education religion courses at a large private university. A moderate correlation was found between GPAs and student evaluations…

  10. Is Chronic Dialysis the Right Hard Renal End Point To Evaluate Renoprotective Drug Effects?

    NARCIS (Netherlands)

    Weldegiorgis, Misghina; de Zeeuw, Dick; Dwyer, Jamie P.; Mol, Peter; Heerspink, Hiddo J. L.

    2017-01-01

    Background and objectives: RRT and doubling of serum creatinine are considered the objective hard end points in nephrology intervention trials. Because both are assumed to reflect changes in the filtration capacity of the kidney, drug effects, if present, are attributed to kidney protection.

  11. Evaluation of flat, angled, and vertical computer mice and their effects on wrist posture, pointing performance, and preference.

    Science.gov (United States)

    Odell, Dan; Johnson, Peter

    2015-01-01

    Modern computer users use the mouse almost three times as much as the keyboard. As exposure rates are high, improving upper extremity posture while using a computer mouse is desirable due to the fact that posture is one risk factor for injury. Previous studies have found posture benefits associated with using alternative mouse designs, but at the cost of performance and preference. To develop new computer mouse shapes, evaluate them versus benchmarks, and determine whether there are differences in wrist posture, pointing performance, and subjective measures. Three concept mice were designed and evaluated relative to two existing benchmark models: a traditional flat mouse, and an alternative upright mouse. Using a repeated measures design, twelve subjects performed a standardized point-and-click task with each mouse. Pointing performance and wrist posture was measured, along with perceived fatigue ratings and subjective preferences pre and post use. All of the concept mice were shown to reduce forearm pronation relative to the traditional flat mouse. There were no differences in pointing performance between the traditional flat mouse and the concept mice. In contrast, the fully vertical mouse reduced pronation but had the poorest pointing performance. Perceived fatigue and subjective preferences were consistently better for one concept mouse. Increasing mouse height and angling the mouse topcase can improve wrist posture without negatively affecting performance.

  12. Data mining for wind power forecasting

    OpenAIRE

    Fugon, Lionel; Juban, Jérémie; Kariniotakis, Georges

    2008-01-01

    International audience; Short-term forecasting of wind energy production up to 2-3 days ahead is recognized as a major contribution for reliable large-scale wind power integration. Increasing the value of wind generation through the improvement of prediction systems performance is recognised as one of the priorities in wind energy research needs for the coming years. This paper aims to evaluate Data Mining type of models for wind power forecasting. Models that are examined include neural netw...

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

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Ruelke

    2013-01-01

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

  14. Adaptive correction of ensemble forecasts

    Science.gov (United States)

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

    2017-04-01

    -LEPS ensemble forecasts. Deterministic verification scores (e.g., mean absolute error, bias) and probabilistic scores (e.g., CRPS) are used to evaluate the post-processing techniques. We conclude that the new adaptive method outperforms the simpler running bias-correction. The proposed adaptive method often outperforms the MBM method in removing bias. The MBM method has the advantage of correcting the ensemble spread, although it needs more training data.

  15. World Area Forecast System (WAFS)

    Data.gov (United States)

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

  16. Forecasting the U.S. Population with the Gompertz Growth Curve

    OpenAIRE

    Pflaumer, Peter

    2012-01-01

    Population forecasts have received a great deal of attention during the past few years. They are widely used for planning and policy purposes. In this paper, the Gompertz growth curve is proposed to forecast the U.S. population. In order to evaluate its forecast error, population estimates from 1890 to 2010 are compared with the corresponding predictions for a variety of launch years, estimation periods, and forecast horizons. Various descriptive measures of these forecast errors are presente...

  17. Neural network versus classical time series forecasting models

    Science.gov (United States)

    Nor, Maria Elena; Safuan, Hamizah Mohd; Shab, Noorzehan Fazahiyah Md; Asrul, Mohd; Abdullah, Affendi; Mohamad, Nurul Asmaa Izzati; Lee, Muhammad Hisyam

    2017-05-01

    Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.

  18. Child pedestrian anthropometry: evaluation of potential impact points during a crash.

    Science.gov (United States)

    Serre, Thierry; Lalys, Loïc; Bartoli, Christophe; Christia-Lotter, Amandine; Leonetti, Georges; Brunet, Christian

    2010-11-01

    This paper highlights the potential impact points of a child pedestrian during a crash with the front end of a vehicle. Child anthropometry was defined for ages between 3 and 15 years. It was based on the measurement of seven different segment body heights (knee, femur, pelvis, shoulder, neck, chin, vertex) performed on about 2,000 French children. For each dimension, the 5(th), 50(th) and 95(th) percentile values were reported, and the corresponding linear regression lines were given. Then these heights were confronted with three different vehicle shapes, corresponding to a passenger car, a sport utility vehicle and a light truck, to identify impact points. In particular, we show that the thigh is directly hit by the bumper for children above 12 years of age, whereas the head principally impacts the hood. The influence of child anthropometry on the pedestrian trajectory and the comparison with test procedures in regulation are discussed. 2010 Elsevier Ltd. All rights reserved.

  19. A systematic evaluation of contemporary impurity correction methods in ITS-90 aluminium fixed point cells

    Science.gov (United States)

    da Silva, Rodrigo; Pearce, Jonathan V.; Machin, Graham

    2017-06-01

    The fixed points of the International Temperature Scale of 1990 (ITS-90) are the basis of the calibration of standard platinum resistance thermometers (SPRTs). Impurities in the fixed point material at the level of parts per million can give rise to an elevation or depression of the fixed point temperature of order of millikelvins, which often represents the most significant contribution to the uncertainty of SPRT calibrations. A number of methods for correcting for the effect of impurities have been advocated, but it is becoming increasingly evident that no single method can be used in isolation. In this investigation, a suite of five aluminium fixed point cells (defined ITS-90 freezing temperature 660.323 °C) have been constructed, each cell using metal sourced from a different supplier. The five cells have very different levels and types of impurities. For each cell, chemical assays based on the glow discharge mass spectroscopy (GDMS) technique have been obtained from three separate laboratories. In addition a series of high quality, long duration freezing curves have been obtained for each cell, using three different high quality SPRTs, all measured under nominally identical conditions. The set of GDMS analyses and freezing curves were then used to compare the different proposed impurity correction methods. It was found that the most consistent corrections were obtained with a hybrid correction method based on the sum of individual estimates (SIE) and overall maximum estimate (OME), namely the SIE/Modified-OME method. Also highly consistent was the correction technique based on fitting a Scheil solidification model to the measured freezing curves, provided certain well defined constraints are applied. Importantly, the most consistent methods are those which do not depend significantly on the chemical assay.

  20. Cultural Resources Evaluation of the Upper Atchafalaya Backwater Area, Iberville and Pointe Coupee Parishes, SOuth Louisiana

    Science.gov (United States)

    2001-05-01

    same year, noting the presence pean settlers at Pointe Coupee, followed by indigo of Bayou Lafourche (McWilliams 1953:23). Along during the Spanish...would become forfeit. Settle- ment began to burgeon in the region, and tobacco It is unclear what effect the immigration of French- and indigo ...f) Fragment from bottle of "Dr. Kilmer’s Swamp Root Kid - ney Cure" g) Molded, lipping-tool finished olive amber bottle neck. early Mississippi period

  1. Evaluation of spray and point inoculation methods for the phenotyping of Puccinia striiformis on wheat

    DEFF Research Database (Denmark)

    Sørensen, Chris Khadgi; Thach, Tine; Hovmøller, Mogens Støvring

    2016-01-01

    The fungus Puccinia striiformis causes yellow (stripe) rust on wheat worldwide. In the present article, new methods utilizing an engineered fluid (Novec 7100) as a carrier of urediniospores were compared with commonly used inoculation methods. In general, Novec 7100 facilitated a faster and more...... for the assessment of quantitative epidemiological parameters. New protocols for spray and point inoculation of P. striiformis on wheat are presented, along with the prospect for applying these in rust research and resistance breeding activities....

  2. Inconsistencies of the Evaluation of Home Advantage in Sports Competitions Under the Three Points Per Victory System

    Directory of Open Access Journals (Sweden)

    García Miguel Saavedra

    2014-10-01

    Full Text Available A recent letter sent to the Journal of Human Kinetics’ editor (Gómez & Pollard, 2014 warned about a supposed methodology error in the calculation of home advantage in football leagues used in Saavedra et al. (2013 and took the liberty of modifying the research’s data. The aim of this letter is to demonstrate that the evaluation system of the home advantage proposed by Pollard (1986 contains serious inconsistencies when applied to competitions which give three points for a win and one point for a draw, as it is the case of the UEFA football leagues in the 21th century

  3. Therapeutic evaluation of lumbar tender point deep massage for chronic non-specific low back pain.

    Science.gov (United States)

    Zheng, Zhixin; Wang, Jun; Gao, Qian; Hou, Jingshan; Ma, Ling; Jiang, Congbo; Chen, Guohui

    2012-12-01

    To observe the therapeutic effect of lumbar tender point deep tissue massage plus lumbar traction on chronic non-specific low back pain using change in pressure pain threshold, muscle hardness and pain intensity as indices. We randomly divided 64 patients into a treatment group (32 cases) and a control group (32 cases). Two drop-outs occurred in each group. Patients in the treatment group received tender point deep tissue massage plus lumbar traction and patients in the control group received lumbar traction, alone. We used a tissue hardness meter/algometer and visual analog scale (VAS) to assess the pressure pain threshold, muscle hardness and pain intensity. Following treatment, we obtained the following results in the treatment and control groups, respectively: the pressure pain threshold difference was 1.5 +/- 0.8 and 1.1 +/- 0.7; the muscle hardness difference was 4.2 +/- 1.6 and 3.5 +/- 1.3; and the VAS score difference was 1.9 +/- 0.9 and 1.4 +/- 0.8. Compared to the control group, the treatment group had higher pressure pain threshold (t = 2.09, P Lumbar tender point deep tissue massage combined with lumbar traction produced better improvement in pressure pain threshold, muscle hardness and pain intensity in patients with chronic non-specific low back pain than with lumbar traction alone.

  4. Using forecast information for storm ride-through control

    DEFF Research Database (Denmark)

    Barahona Garzón, Braulio; Trombe, Pierre-Julien; Vincent, Claire Louise

    2013-01-01

    Using probabilistic forecast information in control algorithms can improve the performance of wind farms during periods of extreme winds. This work presents a wind farm supervisor control concept that uses probabilistic forecast information to ride-through a storm with softer ramps of power. Wind...... speed forecasts are generated with a statistical approach (i.e. time series models). The supervisor control is based on a set of logical rules that consider point forecasts and predictive densities to ramp-down the power of the wind farm before the storm hits. The potential of this supervisor control...... information, and particularly weather radar images....

  5. Terrestrial ecosystem nowcasts and forecasts for North America

    Science.gov (United States)

    Nemani, R. R.; Votava, P.; Michaelis, A.; Ichii, K.; Hashimoto, H.; Milesi, C.; Dungan, J.; White, M.

    2006-12-01

    Understanding and predicting changes in carbon cycling of landscapes and adjacent oceans are important goals for the North American Carbon Program (NACP). Achieving these goals requires integration of a number of data sources that are both point-based and spatially explicit, as in the case of satellite data, and models to produce ecosystem fluxes at a variety of spatio-temporal scales. Here we show an adaptation of our data and modeling system, the Terrestrial Observation and Prediction System (TOPS) over North America to operationally produce nowcasts (daily) and forecasts (up to 7 days) of ecosystem fluxes including gross and net primary production and net ecosystem exchange. TOPS is a software system designed to seamlessly integrate data from satellite, aircraft, and ground sensors, and weather/climate models with application models to quickly and reliably produce operational nowcasts and forecasts of ecological conditions. The underlying technologies in TOPS are: 1) Ecosystem models of a variety of flavors ranging from process-based models that use satellite-derived inputs along with surface climate data, weather/climate forecasts to empirical models that rely on historical relationships between climate and ecological phenomenon such as fire risk, disease/pest outbreaks, etc.; 2) Planning and scheduling that facilitate a goal-based data collection and pre-processing so that all the necessary information is available in the required format for a given model run; and 3) Causality analysis and model generation using advances in data mining and machine learning. Nowcasts and forecasts are continuously evaluated using observations from diverse networks: SNOTEL for snow cover, USGS/Streamflow for runoff, USDA/SCAN for soil moisture, GLOBE for phenology and FLUXNET for carbon/water fluxes. Model parameters are optimized based on the spatio-temporal biases identified during model evaluation

  6. A Small-Sample Adaptive Hybrid Model for Annual Electricity Consumption Forecasting

    Directory of Open Access Journals (Sweden)

    Ming Meng

    2017-01-01

    Full Text Available Annual electricity consumption forecasting is one of the important foundations of power system planning. Considering that the long-term electricity consumption curves of developing countries usually present approximately exponential growth trends and linear and accelerated growth rate trends may also appear in certain periods, this paper first proposes a small-sample adaptive hybrid model (AHM to extrapolate the above curves. The iterative trend extrapolation equation of the proposed model can simulate the linear, exponential, and steep trends adaptively at the same time. To estimate the equation parameters using small samples, the partial least squares (PLS and iteration starting point optimization algorithms are suggested. To evaluate forecasting performance, the artificial neural network (ANN, grey model (GM, and AHM are used to forecast electricity consumption in China from 1991 to 2014, and then the results of these models are compared. Analysis of the forecasting results shows that the AHM can overcome stochastic changes and respond quickly to changes in the main electricity consumption trend because of its specialized equation structure. Overall error analysis indicators also show that AHM often obtains more precise forecasting results than the other two models.

  7. Improving Garch Volatility Forecasts

    NARCIS (Netherlands)

    Klaassen, F.J.G.M.

    1998-01-01

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

  8. Forecasts of forest conditions

    Science.gov (United States)

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

    2013-01-01

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

  9. Forecasting in Planning

    NARCIS (Netherlands)

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

    2004-01-01

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

  10. Assessment of storm forecast

    DEFF Research Database (Denmark)

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

    at analysing the ability of existing forecast tools to predict storms at the Horns Rev 2 wind farm. The focus will be on predicting the time where the wind turbine will need to shut down to protect itself, e.g. the time where wind speed exceeds 25 m/s. At the same time, the planned shut-down should cost...... as little lost wind energy as possible. Therefore, the planned shut down time should be as close as possible to the time where the wind turbine itself would shut down, but still reliable. The forecast systems available to ENERGINET.dk will be applied. The forecast tools ability of accurately predicting...... stopped, completely or partially, producing due to extreme wind speeds. Wind speed and power measurements from those events are presented and compared to the forecast available at Energinet.dk. The analysis looked at wind speed and wind power forecast. The main conclusion of the analysis is that the wind...

  11. Reliability of radiologic evaluation of abdominal aortic calcification using the 24-point scale.

    Science.gov (United States)

    Pariente-Rodrigo, E; Sgaramella, G Alessia; García-Velasco, P; Hernández-Hernández, J L; Landeras-Alvaro, R; Olmos-Martínez, J Manuel

    2016-01-01

    Calcification of the abdominal aorta is associated with increased cardiovascular morbidity, so a reliable method to quantify it is clinically transcendent. The 24-point scale (AAC-24) is the standard method for assessing abdominal aortic calcification on lateral plain films of the lumbar spine. The aim of this study was to determine the intraobserver and interobserver agreements for the AAC-24, taking into account the heterogeneity of the distribution of the calcifications in the design of the statistical analysis. We analyzed the intraobserver agreement (in plain films from 81 patients, with a four-year separation between observations) and the interobserver agreement (in plain films from 100 patients, with three observers), using both intraclass correlation and Bland-Altman plots. The intraobserver intraclass correlation coefficient was 0.93 (95% confidence interval [CI95%]: 0.6-0.9), and the interobserver intraclass correlation coefficient was 0.91 (CI95%: 0.8-0.9) with an increase in the coefficient in the tercile with the greatest discrepancy. The difference in means ranged from 0.3 to 1.2 points, and the distance between the limits of agreement ranged from 4.7 to 9.4 points. These differences increased significantly as the calcification progressed. Using the AAC-24 on lateral plain films of the lumbar spine is a reliable and reproducible method of assessing calcification of the abdominal aorta; both intraobserver and interobserver agreement are higher during the initial phases of calcification. Copyright © 2014 SERAM. Published by Elsevier España, S.L.U. All rights reserved.

  12. Laboratory evaluation of the effect of nitric acid uptake on frost point hygrometer performance

    Directory of Open Access Journals (Sweden)

    T. Thornberry

    2011-02-01

    Full Text Available Chilled mirror hygrometers (CMH are widely used to measure water vapour in the troposphere and lower stratosphere from balloon-borne sondes. Systematic discrepancies among in situ water vapour instruments have been observed at low water vapour mixing ratios (<5 ppm in the upper troposphere and lower stratosphere (UT/LS. Understanding the source of the measurement discrepancies is important for a more accurate and reliable determination of water vapour abundance in this region. We have conducted a laboratory study to investigate the potential interference of gas-phase nitric acid (HNO3 with the measurement of frost point temperature, and consequently the water vapour mixing ratio, determined by CMH under conditions representative of operation in the UT/LS. No detectable interference in the measured frost point temperature was found for HNO3 mixing ratios of up to 4 ppb for exposure times up to 150 min. HNO3 was observed to co-condense on the mirror frost, with the adsorbed mass increasing linearly with time at constant exposure levels. Over the duration of a typical balloon sonde ascent (90–120 min, the maximum accumulated HNO3 amounts were comparable to monolayer coverage of the geometric mirror surface area, which corresponds to only a small fraction of the actual frost layer surface area. This small amount of co-condensed HNO3 is consistent with the observed lack of HNO3 interference in the frost point measurement because the CMH utilizes significant reductions (>10% in surface reflectivity by the condensate to determine H2O.

  13. Colocalization coefficients evaluating the distribution of molecular targets in microscopy methods based on pointed patterns

    Czech Academy of Sciences Publication Activity Database

    Pastorek, Lukáš; Sobol, Margaryta; Hozák, Pavel

    2016-01-01

    Roč. 146, č. 4 (2016), s. 391-406 ISSN 0948-6143 R&D Projects: GA TA ČR(CZ) TE01020118; GA ČR GA15-08738S; GA MŠk(CZ) ED1.1.00/02.0109; GA MŠk(CZ) LM2015062 Grant - others:Human Frontier Science Program(FR) RGP0017/2013 Institutional support: RVO:68378050 Keywords : Colocalization * Quantitative analysis * Pointed patterns * Transmission electron microscopy * Manders' coefficients * Immunohistochemistry Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.553, year: 2016

  14. Forecasting biodiversity in breeding birds using best practices

    Directory of Open Access Journals (Sweden)

    David J. Harris

    2018-02-01

    Full Text Available Biodiversity forecasts are important for conservation, management, and evaluating how well current models characterize natural systems. While the number of forecasts for biodiversity is increasing, there is little information available on how well these forecasts work. Most biodiversity forecasts are not evaluated to determine how well they predict future diversity, fail to account for uncertainty, and do not use time-series data that captures the actual dynamics being studied. We addressed these limitations by using best practices to explore our ability to forecast the species richness of breeding birds in North America. We used hindcasting to evaluate six different modeling approaches for predicting richness. Hindcasts for each method were evaluated annually for a decade at 1,237 sites distributed throughout the continental United States. All models explained more than 50% of the variance in richness, but none of them consistently outperformed a baseline model that predicted constant richness at each site. The best practices implemented in this study directly influenced the forecasts and evaluations. Stacked species distribution models and “naive” forecasts produced poor estimates of uncertainty and accounting for this resulted in these models dropping in the relative performance compared to other models. Accounting for observer effects improved model performance overall, but also changed the rank ordering of models because it did not improve the accuracy of the “naive” model. Considering the forecast horizon revealed that the prediction accuracy decreased across all models as the time horizon of the forecast increased. To facilitate the rapid improvement of biodiversity forecasts, we emphasize the value of specific best practices in making forecasts and evaluating forecasting methods.

  15. Forecasting Companies’ Future Economic Development

    Directory of Open Access Journals (Sweden)

    Jaroslav Dvořáček

    2012-12-01

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

  16. Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

    Science.gov (United States)

    Duda, David P.; Minnis, Patrick

    2009-01-01

    Previous studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.

  17. The evaluation of electrodermal properties in the identification of myofascial trigger points.

    Science.gov (United States)

    Shultz, Sarah P; Driban, Jeffrey B; Swanik, Charles B

    2007-06-01

    To determine whether skin resistance measurements can objectively identify the location of myofascial trigger points (MTPs) and to differentiate between 3 states. Static group comparison. Climate-controlled laboratory. Forty-nine participants (age, 20.5+/-2.6 y) were assigned to 1 of 3 groups based on clinical examination result: absent (n=21), latent (n=16), or active (n=12) MTP. Not applicable. Skin resistance (in kilo-ohms). The 16 data points were divided into 3 categories for analysis: MTP site, surrounding tissue proximal to the MTP (first ring), and area furthest from the MTP (second ring). There was a significant increase in skin resistance between the MTP (403.64+/-124.73 kOmega), first ring (419.66+/-123.04 kOmega), and second ring (454.61+/-163.19 kOmega) (P<.01). The measurements did not differ significantly between the 3 MTP states. The changes in skin resistance between the MTP and the surrounding tissue support the inclusion of this technique to help identify MTPs. The similarity between MTP states warrants investigation into the physiologic differences at specific anatomic locations.

  18. Evaluation of GPS Standard Point Positioning with Various Ionospheric Error Mitigation Techniques

    Science.gov (United States)

    Panda, Sampad K.; Gedam, Shirish S.

    2016-12-01

    The present paper investigates accuracy of single and dual-frequency Global Positioning System (GPS) standard point positioning solutions employing different ionosphere error mitigation techniques. The total electron content (TEC) in the ionosphere is the prominent delay error source in GPS positioning, and its elimination is essential for obtaining a relatively precise positioning solution. The estimated delay error from different ionosphere models and maps, such as Klobuchar model, global ionosphere models, and vertical TEC maps are compared with the locally derived ionosphere error following the ion density and frequency dependence with delay error. Finally, the positional accuracy of the single and dual-frequency GPS point positioning solutions are probed through different ionospheric mitigation methods including exploitation of models, maps, and ionosphere-free linear combinations and removal of higher order ionospheric effects. The results suggest the superiority of global ionosphere maps for single-frequency solution, whereas for the dual-frequency measurement the ionosphere-free linear combination with prior removal of higher-order ionosphere effects from global ionosphere maps and geomagnetic reference fields resulted in improved positioning quality among the chosen mitigation techniques. Conspicuously, the susceptibility of height component to different ionospheric mitigation methods are demonstrated in this study which may assist the users in selecting appropriate technique for precise GPS positioning measurements.

  19. Forecaster’s utility and forecasts coherence

    DEFF Research Database (Denmark)

    Chini, Emilio Zanetti

    I provide general frequentist framework to elicit the forecaster’s expected utility based on a Lagrange Multiplier-type test for the null of locality of the scoring rules associated to the probabilistic forecast. These are assumed to be observed transition variables in a nonlinear autoregressive...... model to ease the statistical inference. A simulation study reveals that the test behaves consistently with the requirements of the theoretical literature. The locality of the scoring rule is fundamental to set dating algorithms to measure and forecast probability of recession in US business cycle....... An investigation of Bank of Norway’s forecasts on output growth leads us to conclude that forecasts are often suboptimal with respect to some simplistic benchmark if forecaster’s reward is not properly evaluated....

  20. Evidence-Based Practice Point-of-Care Resources: A Quantitative Evaluation of Quality, Rigor, and Content.

    Science.gov (United States)

    Campbell, Jared M; Umapathysivam, Kandiah; Xue, Yifan; Lockwood, Craig

    2015-12-01

    Clinicians and other healthcare professionals need access to summaries of evidence-based information in order to provide effective care to their patients at the point-of-care. Evidence-based practice (EBP) point-of-care resources have been developed and are available online to meet this need. This study aimed to develop a comprehensive list of available EBP point-of-care resources and evaluate their processes and policies for the development of content, in order to provide a critical analysis based upon rigor, transparency and measures of editorial quality to inform healthcare providers and promote quality improvement amongst publishers of EBP resources. A comprehensive and systematic search (Pubmed, CINAHL, and Cochrane Central) was undertaken to identify available EBP point-of-care resources, defined as "web-based medical compendia specifically designed to deliver predigested, rapidly accessible, comprehensive, periodically updated, and evidence-based information (and possibly also guidance) to clinicians." A pair of investigators independently extracted information on general characteristics, content presentation, editorial quality, evidence-based methodology, and breadth and volume. Twenty-seven summary resources were identified, of which 22 met the predefined inclusion criteria for EBP point-of-care resources, and 20 could be accessed for description and assessment. Overall, the upper quartile of EBP point-of-care providers was assessed to be UpToDate, Nursing Reference Centre, Mosby's Nursing Consult, BMJ Best Practice, and JBI COnNECT+. The choice of which EBP point-of-care resources are suitable for an organization is a decision that depends heavily on the unique requirements of that organization and the resources it has available. However, the results presented in this study should enable healthcare providers to make that assessment in a clear, evidence-based manner, and provide a comprehensive list of the available options. © 2015 Sigma Theta Tau