Sample records for traffic forecasting

  1. North Carolina forecasts for truck traffic

    DOT National Transportation Integrated Search

    2006-07-01

    North Carolina has experienced significant increases in truck traffic on many of its highways. Yet, current NCDOT : project-level highway traffic forecasts do not appropriately capture anticipated truck traffic growth. NCDOT : methods forecast total ...

  2. Traffic flow forecasting for intelligent transportation systems.

    DOT National Transportation Integrated Search

    1995-01-01

    The capability to forecast traffic volume in an operational setting has been identified as a critical need for intelligent transportation systems (ITS). In particular, traffic volume forecasts will directly support proactive traffic control and accur...

  3. Traffic forecasting report : 2007.

    DOT National Transportation Integrated Search

    2008-05-01

    This is the sixth edition of the Traffic Forecasting Report (TFR). This edition of the TFR contains the latest (predominantly 2007) forecasting/modeling data as follows: : Functional class average traffic volume growth rates and trends : Vehi...

  4. Fuzzy State Transition and Kalman Filter Applied in Short-Term Traffic Flow Forecasting

    PubMed Central

    Ming-jun, Deng; Shi-ru, Qu

    2015-01-01

    Traffic flow is widely recognized as an important parameter for road traffic state forecasting. Fuzzy state transform and Kalman filter (KF) have been applied in this field separately. But the studies show that the former method has good performance on the trend forecasting of traffic state variation but always involves several numerical errors. The latter model is good at numerical forecasting but is deficient in the expression of time hysteretically. This paper proposed an approach that combining fuzzy state transform and KF forecasting model. In considering the advantage of the two models, a weight combination model is proposed. The minimum of the sum forecasting error squared is regarded as a goal in optimizing the combined weight dynamically. Real detection data are used to test the efficiency. Results indicate that the method has a good performance in terms of short-term traffic forecasting. PMID:26779258

  5. Fuzzy State Transition and Kalman Filter Applied in Short-Term Traffic Flow Forecasting.

    PubMed

    Deng, Ming-jun; Qu, Shi-ru

    2015-01-01

    Traffic flow is widely recognized as an important parameter for road traffic state forecasting. Fuzzy state transform and Kalman filter (KF) have been applied in this field separately. But the studies show that the former method has good performance on the trend forecasting of traffic state variation but always involves several numerical errors. The latter model is good at numerical forecasting but is deficient in the expression of time hysteretically. This paper proposed an approach that combining fuzzy state transform and KF forecasting model. In considering the advantage of the two models, a weight combination model is proposed. The minimum of the sum forecasting error squared is regarded as a goal in optimizing the combined weight dynamically. Real detection data are used to test the efficiency. Results indicate that the method has a good performance in terms of short-term traffic forecasting.

  6. Optimized Structure of the Traffic Flow Forecasting Model With a Deep Learning Approach.

    PubMed

    Yang, Hao-Fan; Dillon, Tharam S; Chen, Yi-Ping Phoebe

    2017-10-01

    Forecasting accuracy is an important issue for successful intelligent traffic management, especially in the domain of traffic efficiency and congestion reduction. The dawning of the big data era brings opportunities to greatly improve prediction accuracy. In this paper, we propose a novel model, stacked autoencoder Levenberg-Marquardt model, which is a type of deep architecture of neural network approach aiming to improve forecasting accuracy. The proposed model is designed using the Taguchi method to develop an optimized structure and to learn traffic flow features through layer-by-layer feature granulation with a greedy layerwise unsupervised learning algorithm. It is applied to real-world data collected from the M6 freeway in the U.K. and is compared with three existing traffic predictors. To the best of our knowledge, this is the first time that an optimized structure of the traffic flow forecasting model with a deep learning approach is presented. The evaluation results demonstrate that the proposed model with an optimized structure has superior performance in traffic flow forecasting.

  7. An investigation into incident duration forecasting for FleetForward

    DOT National Transportation Integrated Search

    2000-08-01

    Traffic condition forecasting is the process of estimating future traffic conditions based on current and archived data. Real-time forecasting is becoming an important tool in Intelligent Transportation Systems (ITS). This type of forecasting allows ...

  8. A retrospective evaluation of traffic forecasting techniques.

    DOT National Transportation Integrated Search

    2016-08-01

    Traffic forecasting techniquessuch as extrapolation of previous years traffic volumes, regional travel demand models, or : local trip generation rateshelp planners determine needed transportation improvements. Thus, knowing the accuracy of t...

  9. Small-time Scale Network Traffic Prediction Based on Complex-valued Neural Network

    NASA Astrophysics Data System (ADS)

    Yang, Bin

    2017-07-01

    Accurate models play an important role in capturing the significant characteristics of the network traffic, analyzing the network dynamic, and improving the forecasting accuracy for system dynamics. In this study, complex-valued neural network (CVNN) model is proposed to further improve the accuracy of small-time scale network traffic forecasting. Artificial bee colony (ABC) algorithm is proposed to optimize the complex-valued and real-valued parameters of CVNN model. Small-scale traffic measurements data namely the TCP traffic data is used to test the performance of CVNN model. Experimental results reveal that CVNN model forecasts the small-time scale network traffic measurement data very accurately

  10. Studies of air traffic forecasts, airspace load and the effect of ADS-B via satellites on flight times

    NASA Astrophysics Data System (ADS)

    Zhong, Z. W.; Ridhwan Salleh, Saiful; Chow, W. X.; Ong, Z. M.

    2016-10-01

    Air traffic forecasting is important as it helps stakeholders to plan their budgets and facilities. Thus, three most commonly used forecasting models were compared to see which model suited the air passenger traffic the best. General forecasting equations were also created to forecast the passenger traffic. The equations could forecast around 6.0% growth from 2015 onwards. Another study sought to provide an initial work for determining a theoretical airspace load with relevant calculations. The air traffic was simulated to investigate the current airspace load. Logical and reasonable results were obtained from the modelling and simulations. The current utilization percentages for airspace load per hour and the static airspace load in the interested airspace were found to be 6.64% and 11.21% respectively. Our research also studied how ADS-B would affect the time taken for aircraft to travel. 6000 flights departing from and landing at the airport were studied. New flight plans were simulated with improved flight paths due to the implementation of ADS-B, and flight times of all studied flights could be improved.

  11. Forecasting daily passenger traffic volumes in the Moscow metro

    NASA Astrophysics Data System (ADS)

    Ivanov, V. V.; Osetrov, E. S.

    2018-01-01

    In this paper we have developed a methodology for the medium-term prediction of daily volumes of passenger traffic in the Moscow metro. It includes three options for the forecast: (1) based on artificial neural networks (ANNs), (2) singular-spectral analysis implemented in the Caterpillar-SSA package, and (3) a combination of the ANN and Caterpillar-SSA approaches. The methods and algorithms allow the mediumterm forecasting of passenger traffic flows in the Moscow metro with reasonable accuracy.

  12. Techniques for Forecasting Air Passenger Traffic

    NASA Technical Reports Server (NTRS)

    Taneja, N.

    1972-01-01

    The basic techniques of forecasting the air passenger traffic are outlined. These techniques can be broadly classified into four categories: judgmental, time-series analysis, market analysis and analytical. The differences between these methods exist, in part, due to the degree of formalization of the forecasting procedure. Emphasis is placed on describing the analytical method.

  13. Application of Artificial Neural Networks and Singular-Spectral Analysis in Forecasting the Daily Traffic in the Moscow Metro

    NASA Astrophysics Data System (ADS)

    Ivanov, Victor; Osetrov, Evgenii

    2018-02-01

    In this paper, we investigate the possibility of applying various approaches to solving the problem of medium-term forecasting of daily passenger traffic volumes in the Moscow metro (MM): 1) on the basis of artificial neural networks (ANN); 2) using the singular-spectral analysis implemented in the package "Caterpillar"-SSA; 3) sharing the ANN and the "Caterpillar"-SSA approach. We demonstrate that the developed methods and algorithms allow us to conduct medium-term forecasting of passenger traffic in the MM with reasonable accuracy.

  14. Airfreight forecasting methodology and results

    NASA Technical Reports Server (NTRS)

    1978-01-01

    A series of econometric behavioral equations was developed to explain and forecast the evolution of airfreight traffic demand for the total U.S. domestic airfreight system, the total U.S. international airfreight system, and the total scheduled international cargo traffic carried by the top 44 foreign airlines. The basic explanatory variables used in these macromodels were the real gross national products of the countries involved and a measure of relative transportation costs. The results of the econometric analysis reveal that the models explain more than 99 percent of the historical evolution of freight traffic. The long term traffic forecasts generated with these models are based on scenarios of the likely economic outlook in the United States and 31 major foreign countries.

  15. Forecasting short-term data center network traffic load with convolutional neural networks.

    PubMed

    Mozo, Alberto; Ordozgoiti, Bruno; Gómez-Canaval, Sandra

    2018-01-01

    Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution.

  16. Forecasting short-term data center network traffic load with convolutional neural networks

    PubMed Central

    Ordozgoiti, Bruno; Gómez-Canaval, Sandra

    2018-01-01

    Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution. PMID:29408936

  17. Guidelines for project-level traffic forecasting for Hawaii Department of Transportation.

    DOT National Transportation Integrated Search

    2015-12-01

    These guidelines describe both best practice and acceptable practice for performing project-level traffic : forecasts for the State of Hawaii. The guidelines describe a number of techniques and options that are all : acceptable within their intended ...

  18. Forecasting the daily electricity consumption in the Moscow region using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Ivanov, V. V.; Kryanev, A. V.; Osetrov, E. S.

    2017-07-01

    In [1] we demonstrated the possibility in principle for short-term forecasting of daily volumes of passenger traffic in the Moscow metro with the help of artificial neural networks. During training and predicting, a set of the factors that affect the daily passenger traffic in the subway is passed to the input of the neural network. One of these factors is the daily power consumption in the Moscow region. Therefore, to predict the volume of the passenger traffic in the subway, we must first to solve the problem of forecasting the daily energy consumption in the Moscow region.

  19. Predicting Airspace Capacity Impacts Using the Consolidated Storm Prediction for Aviation

    NASA Technical Reports Server (NTRS)

    Russell, Carl

    2010-01-01

    Convective weather is currently the largest contributor to air traffic delays in the United States. In order to make effective traffic flow management decisions to mitigate these delays, weather forecasts must be made as early and as accurately as possible. A forecast product that could be used to mitigate convective weather impacts is the Consolidated Storm Prediction for Aviation. This product provides forecasts of cloud water content and convective top heights at 0- to 8-hour look-ahead times. The objective of this study was to examine a method of predicting the impact of convective weather on air traffic sector capacities using these forecasts. Polygons representing forecast convective weather were overlaid at multiple flight levels on a sector map to calculate the fraction of each sector covered by weather. The fractional volume coverage was used as the primary metric to determine convection s impact on sectors. Results reveal that the forecasts can be used to predict the probability and magnitude of weather impacts on sector capacity up to eight hours in advance.

  20. A travel time forecasting model based on change-point detection method

    NASA Astrophysics Data System (ADS)

    LI, Shupeng; GUANG, Xiaoping; QIAN, Yongsheng; ZENG, Junwei

    2017-06-01

    Travel time parameters obtained from road traffic sensors data play an important role in traffic management practice. A travel time forecasting model is proposed for urban road traffic sensors data based on the method of change-point detection in this paper. The first-order differential operation is used for preprocessing over the actual loop data; a change-point detection algorithm is designed to classify the sequence of large number of travel time data items into several patterns; then a travel time forecasting model is established based on autoregressive integrated moving average (ARIMA) model. By computer simulation, different control parameters are chosen for adaptive change point search for travel time series, which is divided into several sections of similar state.Then linear weight function is used to fit travel time sequence and to forecast travel time. The results show that the model has high accuracy in travel time forecasting.

  1. Urban pavement surface temperature. Comparison of numerical and statistical approach

    NASA Astrophysics Data System (ADS)

    Marchetti, Mario; Khalifa, Abderrahmen; Bues, Michel; Bouilloud, Ludovic; Martin, Eric; Chancibaut, Katia

    2015-04-01

    The forecast of pavement surface temperature is very specific in the context of urban winter maintenance. to manage snow plowing and salting of roads. Such forecast mainly relies on numerical models based on a description of the energy balance between the atmosphere, the buildings and the pavement, with a canyon configuration. Nevertheless, there is a specific need in the physical description and the numerical implementation of the traffic in the energy flux balance. This traffic was originally considered as a constant. Many changes were performed in a numerical model to describe as accurately as possible the traffic effects on this urban energy balance, such as tires friction, pavement-air exchange coefficient, and infrared flux neat balance. Some experiments based on infrared thermography and radiometry were then conducted to quantify the effect fo traffic on urban pavement surface. Based on meteorological data, corresponding pavement temperature forecast were calculated and were compared with fiels measurements. Results indicated a good agreement between the forecast from the numerical model based on this energy balance approach. A complementary forecast approach based on principal component analysis (PCA) and partial least-square regression (PLS) was also developed, with data from thermal mapping usng infrared radiometry. The forecast of pavement surface temperature with air temperature was obtained in the specific case of urban configurtation, and considering traffic into measurements used for the statistical analysis. A comparison between results from the numerical model based on energy balance, and PCA/PLS was then conducted, indicating the advantages and limits of each approach.

  2. Use of the Box and Jenkins time series technique in traffic forecasting

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Nihan, N.L.; Holmesland, K.O.

    The use of recently developed time series techniques for short-term traffic volume forecasting is examined. A data set containing monthly volumes on a freeway segment for 1968-76 is used to fit a time series model. The resultant model is used to forecast volumes for 1977. The forecast volumes are then compared with actual volumes in 1977. Time series techniques can be used to develop highly accurate and inexpensive short-term forecasts. The feasibility of using these models to evaluate the effects of policy changes or other outside impacts is considered. (1 diagram, 1 map, 14 references,2 tables)

  3. Flight Departure Delay and Rerouting Under Uncertainty in En Route Convective Weather

    NASA Technical Reports Server (NTRS)

    Mukherjee, Avijit; Grabbe, Shon; Sridhar, Banavar

    2011-01-01

    Delays caused by uncertainty in weather forecasts can be reduced by improving traffic flow management decisions. This paper presents a methodology for traffic flow management under uncertainty in convective weather forecasts. An algorithm for assigning departure delays and reroutes to aircraft is presented. Departure delay and route assignment are executed at multiple stages, during which, updated weather forecasts and flight schedules are used. At each stage, weather forecasts up to a certain look-ahead time are treated as deterministic and flight scheduling is done to mitigate the impact of weather on four-dimensional flight trajectories. Uncertainty in weather forecasts during departure scheduling results in tactical airborne holding of flights. The amount of airborne holding depends on the accuracy of forecasts as well as the look-ahead time included in the departure scheduling. The weather forecast look-ahead time is varied systematically within the experiments performed in this paper to analyze its effect on flight delays. Based on the results, longer look-ahead times cause higher departure delays and additional flying time due to reroutes. However, the amount of airborne holding necessary to prevent weather incursions reduces when the forecast look-ahead times are higher. For the chosen day of traffic and weather, setting the look-ahead time to 90 minutes yields the lowest total delay cost.

  4. How long will the traffic flow time series keep efficacious to forecast the future?

    NASA Astrophysics Data System (ADS)

    Yuan, PengCheng; Lin, XuXun

    2017-02-01

    This paper investigate how long will the historical traffic flow time series keep efficacious to forecast the future. In this frame, we collect the traffic flow time series data with different granularity at first. Then, using the modified rescaled range analysis method, we analyze the long memory property of the traffic flow time series by computing the Hurst exponent. We calculate the long-term memory cycle and test its significance. We also compare it with the maximum Lyapunov exponent method result. Our results show that both of the freeway traffic flow time series and the ground way traffic flow time series demonstrate positively correlated trend (have long-term memory property), both of their memory cycle are about 30 h. We think this study is useful for the short-term or long-term traffic flow prediction and management.

  5. Modeling the heterogeneous traffic correlations in urban road systems using traffic-enhanced community detection approach

    NASA Astrophysics Data System (ADS)

    Lu, Feng; Liu, Kang; Duan, Yingying; Cheng, Shifen; Du, Fei

    2018-07-01

    A better characterization of the traffic influence among urban roads is crucial for traffic control and traffic forecasting. The existence of spatial heterogeneity imposes great influence on modeling the extent and degree of road traffic correlation, which is usually neglected by the traditional distance based method. In this paper, we propose a traffic-enhanced community detection approach to spatially reveal the traffic correlation in city road networks. First, the road network is modeled as a traffic-enhanced dual graph with the closeness between two road segments determined not only by their topological connection, but also by the traffic correlation between them. Then a flow-based community detection algorithm called Infomap is utilized to identify the road segment clusters. Evaluated by Moran's I, Calinski-Harabaz Index and the traffic interpolation application, we find that compared to the distance based method and the community based method, our proposed traffic-enhanced community based method behaves better in capturing the extent of traffic relevance as both the topological structure of the road network and the traffic correlations among urban roads are considered. It can be used in more traffic-related applications, such as traffic forecasting, traffic control and guidance.

  6. Forecasting new product diffusion using both patent citation and web search traffic.

    PubMed

    Lee, Won Sang; Choi, Hyo Shin; Sohn, So Young

    2018-01-01

    Accurate demand forecasting for new technology products is a key factor in the success of a business. We propose a way to forecasting a new product's diffusion through technology diffusion and interest diffusion. Technology diffusion and interest diffusion are measured by the volume of patent citations and web search traffic, respectively. We apply the proposed method to forecast the sales of hybrid cars and industrial robots in the US market. The results show that that technology diffusion, as represented by patent citations, can explain long-term sales for hybrid cars and industrial robots. On the other hand, interest diffusion, as represented by web search traffic, can help to improve the predictability of market sales of hybrid cars in the short-term. However, interest diffusion is difficult to explain the sales of industrial robots due to the different market characteristics. Finding indicates our proposed model can relatively well explain the diffusion of consumer goods.

  7. Algorithm and data support of traffic congestion forecasting in the controlled transport

    NASA Astrophysics Data System (ADS)

    Dmitriev, S. V.

    2015-06-01

    The topicality of problem of the traffic congestion forecasting in the logistic systems of product movement highways is considered. The concepts: the controlled territory, the highway occupancy by vehicles, the parking and the controlled territory are introduced. Technical realizabilityof organizing the necessary flow of information on the state of the transport system for its regulation has been marked. Sequence of practical implementation of the solution is given. An algorithm for predicting traffic congestion in the controlled transport system is suggested.

  8. Traffic operational evaluation of traffic impact analysis (TIA) case sites.

    DOT National Transportation Integrated Search

    2010-09-22

    This report summarizes traffic operational evaluation of six select traffic impact analysis (TIA) case sites and the effectiveness of forecasting methods used in TIA studies. Six TIA case sites comprising 15 signalized intersections and 2 unsignalize...

  9. An Enhanced Convective Forecast (ECF) for the New York TRACON Area

    NASA Technical Reports Server (NTRS)

    Wheeler, Mark; Stobie, James; Gillen, Robert; Jedlovec, Gary; Sims, Danny

    2008-01-01

    In an effort to relieve summer-time congestion in the NY Terminal Radar Approach Control (TRACON) area, the FAA is testing an enhanced convective forecast (ECF) product. The test began in June 2008 and is scheduled to run through early September. The ECF is updated every two hours, right before the Air Traffic Control System Command Center (ATCSCC) national planning telcon. It is intended to be used by traffic managers throughout the National Airspace System (NAS) and airlines dispatchers to supplement information from the Collaborative Convective Forecast Product (CCFP) and the Corridor Integrated Weather System (CIWS). The ECF begins where the current CIWS forecast ends at 2 hours and extends out to 12 hours. Unlike the CCFP it is a detailed deterministic forecast with no aerial coverage limits. It is created by an ENSCO forecaster using a variety of guidance products including, the Weather Research and Forecast (WRF) model. This is the same version of the WRF that ENSCO runs over the Florida peninsula in support of launch operations at the Kennedy Space Center. For this project, the WRF model domain has been shifted to the Northeastern US. Several products from the NASA SPoRT group are also used by the ENSCO forecaster. In this paper we will provide examples of the ECF products and discuss individual cases of traffic management actions using ECF guidance.

  10. GIS and Transportation Planning

    DOT National Transportation Integrated Search

    1998-09-16

    Two main objectives of transportation planning are to simulate the current : traffic volume and to forecast the future traffic volume on a transportation : network. Traffic demand modeling typically consists of the following : tasks (1)defining traff...

  11. Large Scale Traffic Simulations

    DOT National Transportation Integrated Search

    1997-01-01

    Large scale microscopic (i.e. vehicle-based) traffic simulations pose high demands on computation speed in at least two application areas: (i) real-time traffic forecasting, and (ii) long-term planning applications (where repeated "looping" between t...

  12. An improved car-following model from the perspective of driver’s forecast behavior

    NASA Astrophysics Data System (ADS)

    Liu, Da-Wei; Shi, Zhong-Ke; Ai, Wen-Huan

    In this paper, a new car-following model considering effect of the driver’s forecast behavior is proposed based on the full velocity difference model (FVDM). Using the new model, we investigate the starting process of the vehicle motion under a traffic signal and find that the delay time of vehicle motion is reduced. Then the stability condition of the new model is derived and the modified Korteweg-de Vries (mKdV) equation is constructed to describe the traffic behavior near the critical point. Numerical simulation is compatible with the analysis of theory such as density wave, hysteresis loop, which shows that the new model is reasonable. The results show that considering the effect of driver’s forecast behavior can help to enhance the stability of traffic flow.

  13. Forecasting new product diffusion using both patent citation and web search traffic

    PubMed Central

    Lee, Won Sang; Choi, Hyo Shin

    2018-01-01

    Accurate demand forecasting for new technology products is a key factor in the success of a business. We propose a way to forecasting a new product’s diffusion through technology diffusion and interest diffusion. Technology diffusion and interest diffusion are measured by the volume of patent citations and web search traffic, respectively. We apply the proposed method to forecast the sales of hybrid cars and industrial robots in the US market. The results show that that technology diffusion, as represented by patent citations, can explain long-term sales for hybrid cars and industrial robots. On the other hand, interest diffusion, as represented by web search traffic, can help to improve the predictability of market sales of hybrid cars in the short-term. However, interest diffusion is difficult to explain the sales of industrial robots due to the different market characteristics. Finding indicates our proposed model can relatively well explain the diffusion of consumer goods. PMID:29630616

  14. Satellite provided customer premise services: A forecast of potential domestic demand through the year 2000. Volume 3: Appendices

    NASA Technical Reports Server (NTRS)

    Kratochvil, D.; Bowyer, J.; Bhushan, C.; Steinnagel, K.; Kaushal, D.; Al-Kinani, G.

    1983-01-01

    Voice applications, data applications, video applications, impacted baseline forecasts, market distribution, potential CPS (customers premises services) user classes, net long haul forecasts, CPS cost analysis, overall satellite forecast, CPS satellite market, Ka-band CPS satellite forecast, nationwide traffic distribution model, and intra-urban topology are discussed.

  15. Satellite provided customer premise services: A forecast of potential domestic demand through the year 2000. Volume 3: Appendices

    NASA Astrophysics Data System (ADS)

    Kratochvil, D.; Bowyer, J.; Bhushan, C.; Steinnagel, K.; Kaushal, D.; Al-Kinani, G.

    1983-08-01

    Voice applications, data applications, video applications, impacted baseline forecasts, market distribution, potential CPS (customers premises services) user classes, net long haul forecasts, CPS cost analysis, overall satellite forecast, CPS satellite market, Ka-band CPS satellite forecast, nationwide traffic distribution model, and intra-urban topology are discussed.

  16. A Time Series Model for Assessing the Trend and Forecasting the Road Traffic Accident Mortality

    PubMed Central

    Yousefzadeh-Chabok, Shahrokh; Ranjbar-Taklimie, Fatemeh; Malekpouri, Reza; Razzaghi, Alireza

    2016-01-01

    Background Road traffic accident (RTA) is one of the main causes of trauma and known as a growing public health concern worldwide, especially in developing countries. Assessing the trend of fatalities in the past years and forecasting it enables us to make the appropriate planning for prevention and control. Objectives This study aimed to assess the trend of RTAs and forecast it in the next years by using time series modeling. Materials and Methods In this historical analytical study, the RTA mortalities in Zanjan Province, Iran, were evaluated during 2007 - 2013. The time series analyses including Box-Jenkins models were used to assess the trend of accident fatalities in previous years and forecast it for the next 4 years. Results The mean age of the victims was 37.22 years (SD = 20.01). From a total of 2571 deaths, 77.5% (n = 1992) were males and 22.5% (n = 579) were females. The study models showed a descending trend of fatalities in the study years. The SARIMA (1, 1, 3) (0, 1, 0) 12 model was recognized as a best fit model in forecasting the trend of fatalities. Forecasting model also showed a descending trend of traffic accident mortalities in the next 4 years. Conclusions There was a decreasing trend in the study and the future years. It seems that implementation of some interventions in the recent decade has had a positive effect on the decline of RTA fatalities. Nevertheless, there is still a need to pay more attention in order to prevent the occurrence and the mortalities related to traffic accidents. PMID:27800467

  17. A Time Series Model for Assessing the Trend and Forecasting the Road Traffic Accident Mortality.

    PubMed

    Yousefzadeh-Chabok, Shahrokh; Ranjbar-Taklimie, Fatemeh; Malekpouri, Reza; Razzaghi, Alireza

    2016-09-01

    Road traffic accident (RTA) is one of the main causes of trauma and known as a growing public health concern worldwide, especially in developing countries. Assessing the trend of fatalities in the past years and forecasting it enables us to make the appropriate planning for prevention and control. This study aimed to assess the trend of RTAs and forecast it in the next years by using time series modeling. In this historical analytical study, the RTA mortalities in Zanjan Province, Iran, were evaluated during 2007 - 2013. The time series analyses including Box-Jenkins models were used to assess the trend of accident fatalities in previous years and forecast it for the next 4 years. The mean age of the victims was 37.22 years (SD = 20.01). From a total of 2571 deaths, 77.5% (n = 1992) were males and 22.5% (n = 579) were females. The study models showed a descending trend of fatalities in the study years. The SARIMA (1, 1, 3) (0, 1, 0) 12 model was recognized as a best fit model in forecasting the trend of fatalities. Forecasting model also showed a descending trend of traffic accident mortalities in the next 4 years. There was a decreasing trend in the study and the future years. It seems that implementation of some interventions in the recent decade has had a positive effect on the decline of RTA fatalities. Nevertheless, there is still a need to pay more attention in order to prevent the occurrence and the mortalities related to traffic accidents.

  18. First Coast Guard district traffic model report

    DOT National Transportation Integrated Search

    1997-11-01

    The purpose of this report was to describe the methodology used in developing the First Coast Guard District (CGD1) Traffic Model and to document the potential National Distress System (NDS) voice and data traffic forecasted for the year 2001. The ND...

  19. Forecasting mortality of road traffic injuries in China using seasonal autoregressive integrated moving average model.

    PubMed

    Zhang, Xujun; Pang, Yuanyuan; Cui, Mengjing; Stallones, Lorann; Xiang, Huiyun

    2015-02-01

    Road traffic injuries have become a major public health problem in China. This study aimed to develop statistical models for predicting road traffic deaths and to analyze seasonality of deaths in China. A seasonal autoregressive integrated moving average (SARIMA) model was used to fit the data from 2000 to 2011. Akaike Information Criterion, Bayesian Information Criterion, and mean absolute percentage error were used to evaluate the constructed models. Autocorrelation function and partial autocorrelation function of residuals and Ljung-Box test were used to compare the goodness-of-fit between the different models. The SARIMA model was used to forecast monthly road traffic deaths in 2012. The seasonal pattern of road traffic mortality data was statistically significant in China. SARIMA (1, 1, 1) (0, 1, 1)12 model was the best fitting model among various candidate models; the Akaike Information Criterion, Bayesian Information Criterion, and mean absolute percentage error were -483.679, -475.053, and 4.937, respectively. Goodness-of-fit testing showed nonautocorrelations in the residuals of the model (Ljung-Box test, Q = 4.86, P = .993). The fitted deaths using the SARIMA (1, 1, 1) (0, 1, 1)12 model for years 2000 to 2011 closely followed the observed number of road traffic deaths for the same years. The predicted and observed deaths were also very close for 2012. This study suggests that accurate forecasting of road traffic death incidence is possible using SARIMA model. The SARIMA model applied to historical road traffic deaths data could provide important evidence of burden of road traffic injuries in China. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain.

    PubMed

    Barba, Lida; Rodríguez, Nibaldo

    2017-01-01

    Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT.

  1. A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain

    PubMed Central

    Rodríguez, Nibaldo

    2017-01-01

    Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT. PMID:28261267

  2. Using temporal detrending to observe the spatial correlation of traffic.

    PubMed

    Ermagun, Alireza; Chatterjee, Snigdhansu; Levinson, David

    2017-01-01

    This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis-St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models.

  3. Using temporal detrending to observe the spatial correlation of traffic

    PubMed Central

    2017-01-01

    This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis—St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models. PMID:28472093

  4. Collaborative Aviation Weather Statement - An Impact-based Decision Support Tool

    NASA Astrophysics Data System (ADS)

    Blondin, Debra

    2016-04-01

    Historically, convection causes the highest number of air traffic constraints on the United States National Air Space (NAS). Increased NAS predictability allows traffic flow managers to more effectively initiate, amend or terminate planned or active traffic management initiatives, resulting in more efficient use of available airspace. A Collaborative Aviation Weather Statement (CAWS) is an impact-based decision support tool used for the timely delivery of high-confidence, high-relevance aviation convective weather forecasts to air traffic managers. The CAWS is a graphical and textual forecast produced by a collaborative team of meteorologists from the Aviation Weather Center (AWC), Center Weather Service Units, and airlines to bring attention to high impact areas of thunderstorms. The CAWS addresses thunderstorm initiation or movement into the airports having the highest volume of traffic or into traffic sensitive jet routes. These statements are assessed by planners at the Federal Aviation Administration's (FAA) Air Route Traffic Control Centers and are used for planning traffic management initiatives to balance air traffic flow across the United States. The FAA and the airline industry use the CAWS to plan, manage, and execute operations in the NAS, thereby improving the system efficiency and safety and also saving dollars for industry and the traveling public.

  5. Analysis and Classification of Traffic in Wireless Sensor Network

    DTIC Science & Technology

    2007-03-01

    34 1. Hurst Parameter ................................................................................35 2. Self-Similarity...traffic is self-similar, buffer size can be better designed from the forecasted traffic workload. 1. Hurst Parameter To determine the extent of self...similarity in WSN traffic, the Hurst parameter, H, is used. H also calculates the length of the long range dependence of a stochastic process. If H

  6. The importance of antipersistence for traffic jams

    NASA Astrophysics Data System (ADS)

    Krause, Sebastian M.; Habel, Lars; Guhr, Thomas; Schreckenberg, Michael

    2017-05-01

    Universal characteristics of road networks and traffic patterns can help to forecast and control traffic congestion. The antipersistence of traffic flow time series has been found for many data sets, but its relevance for congestion has been overseen. Based on empirical data from motorways in Germany, we study how antipersistence of traffic flow time-series impacts the duration of traffic congestion on a wide range of time scales. We find a large number of short-lasting traffic jams, which implies a large risk for rear-end collisions.

  7. Air Traffic Forecasting at the Port Authority of New York and New Jersey

    NASA Technical Reports Server (NTRS)

    Augustine, J. G.

    1972-01-01

    Procedures for conducting air traffic forecasts with specific application to the Port Authority of New York and New Jersey are discussed. The procedure relates air travel growth to detailed socio-economic and demographic characteristics of the U.S. population rather than to aggregate economic data such as Gross National Product, personal income, and industrial production. Charts are presented to show the relationship between various selected characteristics and the use of air transportation facilities.

  8. [Development of forecasting models for fatal road traffic injuries].

    PubMed

    Tan, Aichun; Tian, Danping; Huang, Yuanxiu; Gao, Lin; Deng, Xin; Li, Li; He, Qiong; Chen, Tianmu; Hu, Guoqing; Wu, Jing

    2014-02-01

    To develop the forecasting models for fatal road traffic injuries and to provide evidence for predicting the future trends on road traffic injuries. Data on the mortality of road traffic injury including factors as gender and age in different countries, were obtained from the World Health Organization Mortality Database. Other information on GDP per capita, urbanization, motorization and education were collected from online resources of World Bank, WHO, the United Nations Population Division and other agencies. We fitted logarithmic models of road traffic injury mortality by gender and age group, including predictors of GDP per capita, urbanization, motorization and education. Sex- and age-specific forecasting models developed by WHO that including GDP per capita, education and time etc. were also fitted. Coefficient of determination(R(2)) was used to compare the performance between our modes and WHO models. 2 626 sets of data were collected from 153 countries/regions for both genders, between 1965 and 2010. The forecasting models of road traffic injury mortality based on GDP per capita, motorization, urbanization and education appeared to be statistically significant(P < 0.001), and the coefficients of determination for males at the age groups of 0-4, 5-14, 15-24, 25-34, 35-44, 45-54, 55-64, 65+ were 22.7% , 31.1%, 51.8%, 52.3%, 44.9%, 41.8%, 40.1%, 25.5%, respectively while the coefficients for these age groups in women were 22.9%, 32.6%, 51.1%, 49.3%, 41.3%, 35.9%, 30.7%, 20.1%, respectively. The WHO models that were based on the GDP per capita, education and time variables were statistically significant (P < 0.001)and the coefficients of determination were 14.9% , 22.0%, 31.5%, 33.1% , 30.7%, 28.5%, 27.7% and 17.8% for males, but 14.1%, 20.6%, 30.4%, 31.8%, 26.7%, 24.3%, 17.3% and 8.8% for females, respectively. The forecasting models that we developed seemed to be better than those developed by WHO.

  9. Socioeconomic Forecasting : [Technical Summary

    DOT National Transportation Integrated Search

    2012-01-01

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

  10. Air Traffic Demand Estimates for 1995

    DOT National Transportation Integrated Search

    1975-04-01

    The forecasts provide a range of reasonable 1995 activity levels for analyzing and comparing cost and performance characteristics of future air traffic management system concept alternatives. High and low estimates of the various demand measures are ...

  11. Defining the drivers for accepting decision making automation in air traffic management.

    PubMed

    Bekier, Marek; Molesworth, Brett R C; Williamson, Ann

    2011-04-01

    Air Traffic Management (ATM) operators are under increasing pressure to improve the efficiency of their operation to cater for forecasted increases in air traffic movements. One solution involves increasing the utilisation of automation within the ATM system. The success of this approach is contingent on Air Traffic Control Operators' (ATCOs) willingness to accept increased levels of automation. The main aim of the present research was to examine the drivers underpinning ATCOs' willingness to accept increased utilisation of automation within their role. Two fictitious scenarios involving the application of two new automated decision-making tools were created. The results of an online survey revealed traditional predictors of automation acceptance such as age, trust and job satisfaction explain between 4 and 7% of the variance. Furthermore, these predictors varied depending on the purpose in which the automation was to be employed. These results are discussed from an applied and theoretical perspective. STATEMENT OF RELEVANCE: Efficiency improvements in ATM are required to cater for forecasted increases in air traffic movements. One solution is to increase the utilisation of automation within Air Traffic Control. The present research examines the drivers underpinning air traffic controllers' willingness to accept increased levels of automation in their role.

  12. FAA aviation forecasts : fiscal years 1997-2008

    DOT National Transportation Integrated Search

    1997-03-01

    This report contains the Fiscal Years 1997-2008 Federal Aviation Administration (FAA) forecasts of aviation activity at FAA facilities. These include airports with both FAA and contract control towers, air route traffic control centers, and flight se...

  13. Research notes : best practices for traffic impact studies.

    DOT National Transportation Integrated Search

    2006-11-01

    Traffic Impact Studies (TISs) are used by the Oregon Department of Transportation (ODOT) and staff of other transportation agencies to forecast future system effects from proposed development projects and to predict the useful life of a transportatio...

  14. Planning Inmarsat's second generation of spacecraft

    NASA Astrophysics Data System (ADS)

    Williams, W. P.

    1982-09-01

    The next generation of studies of the Inmarsat service are outlined, such as traffic forecasting studies, communications capacity estimates, space segment design, cost estimates, and financial analysis. Traffic forecasting will require future demand estimates, and a computer model has been developed which estimates demand over the Atlantic, Pacific, and Indian ocean regions. Communications estimates are based on traffic estimates, as a model converts traffic demand into a required capacity figure for a given area. The Erlang formula is used, requiring additional data such as peak hour ratios and distribution estimates. Basic space segment technical requirements are outlined (communications payload, transponder arrangements, etc), and further design studies involve such areas as space segment configuration, launcher and spacecraft studies, transmission planning, and earth segment configurations. Cost estimates of proposed design parameters will be performed, but options must be reduced to make construction feasible. Finally, a financial analysis will be carried out in order to calculate financial returns.

  15. Forecast and capacity planning for Nogales' ports of entry : [summary].

    DOT National Transportation Integrated Search

    2009-12-01

    This document provides the final report of the activities performed under the project : Nogales POEs Traffic Study: Forecast and Capacity Planning for Nogales Ports of Entry : sponsored by the Arizona Department of Transportation (ADOT) under Gran...

  16. A model to forecast peak spreading.

    DOT National Transportation Integrated Search

    2012-04-01

    As traffic congestion increases, the K-factor, defined as the proportion of the 24-hour traffic volume that occurs during the peak hour, may decrease. This behavioral response is known as peak spreading: as congestion grows during the peak travel tim...

  17. Holiday effect on traffic fatalities

    DOT National Transportation Integrated Search

    1987-04-01

    The report identifies those holidays that show an increase in traffic fatalities and estimates the size of the increase for each national holiday. A procedure is presented that can be used to forecast the expected fatality count for each upcoming hol...

  18. Evaluation of origin-destination matrix estimation techniques to support aspects of traffic modeling.

    DOT National Transportation Integrated Search

    2014-05-01

    Travel demand forecasting models are used to predict future traffic volumes to evaluate : roadway improvement alternatives. Each of the metropolitan planning organizations (MPO) in : Alabama maintains a travel demand model to support planning efforts...

  19. Seismic vulnerability analysis of bridges in mountainous states.

    DOT National Transportation Integrated Search

    2013-09-01

    Depending on the location, highway bridges can often support considerable amounts of traffic. Due to the limitations on current earthquake forecasting techniques, a normal amount of traffic will also typically remain on a bridge when an earthquake oc...

  20. Traffic-load forecasting using weigh-in-motion data

    DOT National Transportation Integrated Search

    1997-03-01

    Vehicular traffic loading is a crucial consideration for the design and maintenance of pavements. With the help of weigh-in-motion (WIM) systems, the information about date, time, speed, lane of travel, lateral lane position, axle spacing, and wheel ...

  1. Impact of Probabilistic Weather on Flight Routing Decisions

    NASA Technical Reports Server (NTRS)

    Sheth, Kapil; Sridhar, Banavar; Mulfinger, Daniel

    2006-01-01

    Flight delays in the United States have been found to increase year after year, along with the increase in air traffic. During the four-month period from May through August of 2005, weather related delays accounted for roughly 70% of all reported delays, The current weather prediction in tactical (within 2 hours) timeframe is at manageable levels, however, the state of forecasting weather for strategic (2-6 hours) timeframe is still not dependable for long-term planning. In the absence of reliable severe weather forecasts, the decision-making for flights longer than two hours is challenging. This paper deals with an approach of using probabilistic weather prediction for Traffic Flow Management use, and a general method using this prediction for estimating expected values of flight length and delays in the National Airspace System (NAS). The current state-of-the-art convective weather forecasting is employed to aid the decision makers in arriving at decisions for traffic flow and flight planing. The six-agency effort working on the Next Generation Air Transportation System (NGATS) have considered weather-assimilated decision-making as one of the principal foci out of a list of eight. The weather Integrated Product Team has considered integrated weather information and improved aviation weather forecasts as two of the main efforts (Ref. 1, 2). Recently, research has focused on the concept of operations for strategic traffic flow management (Ref. 3) and how weather data can be integrated for improved decision-making for efficient traffic management initiatives (Ref. 4, 5). An overview of the weather data needs and benefits of various participants in the air traffic system along with available products can be found in Ref. 6. Previous work related to use of weather data in identifying and categorizing pilot intrusions into severe weather regions (Ref. 7, 8) has demonstrated a need for better forecasting in the strategic planning timeframes and moving towards a probabilistic description of weather (Ref. 9). This paper focuses on. specified probability in a local region for flight intrusion/deviation decision-making. The process uses a probabilistic weather description, implements that in a air traffic assessment system to study trajectories of aircraft crossing a cut-off probability contour. This value would be useful for meteorologists in creating optimum distribution profiles for severe weather, Once available, the expected values of flight path and aggregate delays are calculated for efficient operations. The current research, however, does not deal with the issue of multiple cell encounters, as well as echo tops, and will be a topic of future work.

  2. Understanding urban travel demand : problems, solutions, and the role of forecasting

    DOT National Transportation Integrated Search

    1999-08-01

    This report is a general examination and critique of transportation policy making, focusing on the role of traffic and land use forecasting. There are four major components: (1) Current, historical, and projected travel behavior in the Twin Cities; (...

  3. Evaluation of TxDOT'S traffic data collection and load forecasting process

    DOT National Transportation Integrated Search

    2001-01-01

    This study had two primary objectives: (1) compare current Texas Department of Transportation (TxDOT) procedures and protocols with the state-of-the-practice and the needs of its data customers; and (2) develop enhanced traffic collection, archival, ...

  4. Next generation air transportation system : issues associated with midterm implementation of capabilities and full system transformation.

    DOT National Transportation Integrated Search

    2009-03-01

    To prepare for forecasted air traffic : growth, the Federal Aviation : Administration (FAA), including its : Joint Planning and Development : Office (JPDO) and Air Traffic : Organization (ATO), is planning for : and implementing the Next : Generation...

  5. Estimation and prediction of origin-destination matrices for I-66.

    DOT National Transportation Integrated Search

    2011-09-01

    This project uses the Box-Jenkins time-series technique to model and forecast the traffic flows and then : uses the flow forecasts to predict the origin-destination matrices. First, a detailed analysis was conducted : to investigate the best data cor...

  6. Origin destination disaggregation using fratar biproportional least squares estimation for truck forecasting.

    DOT National Transportation Integrated Search

    2009-02-01

    This working paper describes a group of techniques for disaggregating origin-destination tables : for truck forecasting that makes explicit use of observed traffic on a network. Six models within : the group are presented, each of which uses nonlinea...

  7. Developing long range traffic projection models for Illinois : final report.

    DOT National Transportation Integrated Search

    2004-06-01

    The project objective was to develop a PC-based tool to assist Illinois Department of Transportation (IDOT) traffic forecasters : to meet FHWA reporting requirements for 2,400 HPMS sections and 27,000 structures in the State of Illinois, and to produ...

  8. Next generation air transportation system : status of transformation and issues associated with midterm implementation of capabilities.

    DOT National Transportation Integrated Search

    2009-03-01

    "To prepare for forecasted air traffic growth, the Federal Aviation Administration (FAA), including its Joint Planning and Development Office (JPDO) and Air Traffic Organization (ATO), is planning for and implementing the Next Generation Air Transpor...

  9. Telecommunication service markets through the year 2000 in relation to millimeter wave satellite systems

    NASA Technical Reports Server (NTRS)

    Stevenson, S. M.

    1979-01-01

    NASA is currently conducting a series of millimeter wave satellite system market studies to develop 30/20 GHz satellite system concepts that have commercial potential. Four contractual efforts were undertaken: two parallel and independent system studies and two parallel and independent market studies. The marketing efforts are focused on forecasting the total domestic demand for long haul telecommunications services for the 1980-2000 period. Work completed to date and reported in this paper include projections of: geographical distribution of traffic; traffic volume as a function of urban area size; and user identification and forecasted demand.

  10. Forecast and capacity planning for Nogales' ports of entry.

    DOT National Transportation Integrated Search

    2009-12-01

    This report documents the findings and the activities performed under ADOT grant JPA 08024T. The overall purpose of this study was to forecast the number of border crossings by mode of traffic at the NogalesMariposa and DeConcini Ports of Entry...

  11. Design/build vs traditional construction user delay modeling : an evaluation of the cost effectiveness of innovative construction methods for new construction. Part 2 : VISUM Online for Salt Lake, Davis, and Utah Counties

    DOT National Transportation Integrated Search

    2007-05-01

    VISUM Online is a traffic management system for processing online traffic data. The system implements both a road network model and a traffic demand model. VISUM Online uses all available real-time and historic data to calculate current and forecaste...

  12. National Waterways Study. Traffic Forecasting Methodology.

    DTIC Science & Technology

    1981-08-01

    non-ferrous). In general , the demand for domestic waterborne metallic ore transportation is projected to grow somewhat faster than iron ore...steady growth in imported tonnages. Industrial chemicals generally exhibit upward trends ranging from 2.5% per year to 4.6% per year for a broad mix...completion of Colonial pipeline system expansions in 1981. Internal traffic generally ex- hibts flat to 1% per year traffic increases, with growth

  13. CG Vessel Traffic Service Program.

    DTIC Science & Technology

    1980-06-01

    Corps of Engineers and the Maritime Administration have forecast that total commercial cargo transported through U.S. ports and waterways will increase... electronic navigation and surveillance equipment since the early 1960’s to evaluate various concepts by which vessel traffic safety could be enhanced...relatively complete data base on vessel traffic. On the other hand, the addition of radar and other electronic surveillance should: --Prevent vessel

  14. Integration of Weather Data into Airspace and Traffic Operations Simulation (ATOS) for Trajectory- Based Operations Research

    NASA Technical Reports Server (NTRS)

    Peters, Mark; Boisvert, Ben; Escala, Diego

    2009-01-01

    Explicit integration of aviation weather forecasts with the National Airspace System (NAS) structure is needed to improve the development and execution of operationally effective weather impact mitigation plans and has become increasingly important due to NAS congestion and associated increases in delay. This article considers several contemporary weather-air traffic management (ATM) integration applications: the use of probabilistic forecasts of visibility at San Francisco, the Route Availability Planning Tool to facilitate departures from the New York airports during thunderstorms, the estimation of en route capacity in convective weather, and the application of mixed-integer optimization techniques to air traffic management when the en route and terminal capacities are varying with time because of convective weather impacts. Our operational experience at San Francisco and New York coupled with very promising initial results of traffic flow optimizations suggests that weather-ATM integrated systems warrant significant research and development investment. However, they will need to be refined through rapid prototyping at facilities with supportive operational users We have discussed key elements of an emerging aviation weather research area: the explicit integration of aviation weather forecasts with NAS structure to improve the effectiveness and timeliness of weather impact mitigation plans. Our insights are based on operational experiences with Lincoln Laboratory-developed integrated weather sensing and processing systems, and derivative early prototypes of explicit ATM decision support tools such as the RAPT in New York City. The technical components of this effort involve improving meteorological forecast skill, tailoring the forecast outputs to the problem of estimating airspace impacts, developing models to quantify airspace impacts, and prototyping automated tools that assist in the development of objective broad-area ATM strategies, given probabilistic weather forecasts. Lincoln Laboratory studies and prototype demonstrations in this area are helping to define the weather-assimilated decision-making system that is envisioned as a key capability for the multi-agency Next Generation Air Transportation System [1]. The Laboratory's work in this area has involved continuing, operations-based evolution of both weather forecasts and models for weather impacts on the NAS. Our experience has been that the development of usable ATM technologies that address weather impacts must proceed via rapid prototyping at facilities whose users are highly motivated to participate in system evolution.

  15. Definition of perspective scheme of organization of traffic using methods of forecasting and modeling

    NASA Astrophysics Data System (ADS)

    Vlasov, V. M.; Novikov, A. N.; Novikov, I. A.; Shevtsova, A. G.

    2018-03-01

    In the environment of highly developed urban agglomerations, one of the main problems arises - inability of the road network to reach a high level of motorization. The introduction of intelligent transport systems allows solving this problem, but the main issue in their implementation remains open: to what extent this or that method of improving the transport network will be effective and whether it is able to solve the problem of vehicle growth especially for the long-term period. The main goal of this work was the development of an approach to forecasting the increase in the intensity of traffic flow for a long-term period using the population and the level of motorization. The developed approach made it possible to determine the projected population and, taking into account the level of motorization, to determine the growth factor of the traffic flow intensity, which allows calculating the intensity value for a long-term period with high accuracy. The analysis of the main methods for predicting the characteristics of the transport stream is performed. The basic values and parameters necessary for their use are established. The analysis of the urban settlement is carried out and the level of motorization characteristic for the given locality is determined. A new approach to predicting the intensity of the traffic flow has been developed, which makes it possible to predict the change in the transport situation in the long term in high accuracy. Calculations of the magnitude of the intensity increase on the basis of the developed forecasting method are made and the errors in the data obtained are determined. The main recommendations on the use of the developed forecasting approach for the long-term functioning of the road network are formulated.

  16. Time Relevance of Convective Weather Forecast for Air Traffic Automation

    NASA Technical Reports Server (NTRS)

    Chan, William N.

    2006-01-01

    The Federal Aviation Administration (FAA) is handling nearly 120,000 flights a day through its Air Traffic Management (ATM) system and air traffic congestion is expected to increse substantially over the next 20 years. Weather-induced impacts to throughput and efficiency are the leading cause of flight delays accounting for 70% of all delays with convective weather accounting for 60% of all weather related delays. To support the Next Generation Air Traffic System goal of operating at 3X current capacity in the NAS, ATC decision support tools are being developed to create advisories to assist controllers in all weather constraints. Initial development of these decision support tools did not integrate information regarding weather constraints such as thunderstorms and relied on an additional system to provide that information. Future Decision Support Tools should move towards an integrated system where weather constraints are factored into the advisory of a Decision Support Tool (DST). Several groups such at NASA-Ames, Lincoln Laboratories, and MITRE are integrating convective weather data with DSTs. A survey of current convective weather forecast and observation data show they span a wide range of temporal and spatial resolutions. Short range convective observations can be obtained every 5 mins with longer range forecasts out to several days updated every 6 hrs. Today, the short range forecasts of less than 2 hours have a temporal resolution of 5 mins. Beyond 2 hours, forecasts have much lower temporal. resolution of typically 1 hour. Spatial resolutions vary from 1km for short range to 40km for longer range forecasts. Improving the accuracy of long range convective forecasts is a major challenge. A report published by the National Research Council states improvements for convective forecasts for the 2 to 6 hour time frame will only be achieved for a limited set of convective phenomena in the next 5 to 10 years. Improved longer range forecasts will be probabilistic as opposed to the deterministic shorter range forecasts. Despite the known low level of confidence with respect to long range convective forecasts, these data are still useful to a DST routing algorithm. It is better to develop an aircraft route using the best information available than no information. The temporally coarse long range forecast data needs to be interpolated to be useful to a DST. A DST uses aircraft trajectory predictions that need to be evaluated for impacts by convective storms. Each time-step of a trajectory prediction n&s to be checked against weather data. For the case of coarse temporal data, there needs to be a method fill in weather data where there is none. Simply using the coarse weather data without any interpolation can result in DST routes that are impacted by regions of strong convection. Increasing the temporal resolution of these data can be achieved but result in a large dataset that may prove to be an operational challenge in transmission and loading by a DST. Currently, it takes about 7mins retrieve a 7mb RUC2 forecast file from NOAA at NASA-Ames Research Center. A prototype NCWF6 1 hour forecast is about 3mb in size. A Six hour NCWFG forecast with a 1hr forecast time-step will be about l8mb (6 x 3mb). A 6 hour NCWF6 forecast with a l5min forecast time-step will be about 7mb (24 x 3mb). Based on the time it takes to retrieve a 7mb RUC2 forecast, it will take approximately 70mins to retrieve a 6 hour NCWF forecast with 15min time steps. Until those issues are addressed, there is a need to develop an algorithm that interpolates between these temporally coarse long range forecasts. This paper describes a method of how to use low temporal resolution probabilistic weather forecasts in a DST. The beginning of this paper is a description of some convective weather forecast and observation products followed by an example of how weather data are used by a DST. The subsequent sections will describe probabilistic forecasts followed by a descrtion of a method to use low temporal resolution probabilistic weather forecasts by providing a relevance value to these data outside of their valid times.

  17. Traffic Flow Management Wrap-Up

    NASA Technical Reports Server (NTRS)

    Grabbe, Shon

    2011-01-01

    Traffic Flow Management involves the scheduling and routing of air traffic subject to airport and airspace capacity constraints, and the efficient use of available airspace. Significant challenges in this area include: (1) weather integration and forecasting, (2) accounting for user preferences in the Traffic Flow Management decision making process, and (3) understanding and mitigating the environmental impacts of air traffic on the environment. To address these challenges, researchers in the Traffic Flow Management area are developing modeling, simulation and optimization techniques to route and schedule air traffic flights and flows while accommodating user preferences, accounting for system uncertainties and considering the environmental impacts of aviation. This presentation will highlight some of the major challenges facing researchers in this domain, while also showcasing recent innovations designed to address these challenges.

  18. Smoothing strategies combined with ARIMA and neural networks to improve the forecasting of traffic accidents.

    PubMed

    Barba, Lida; Rodríguez, Nibaldo; Montt, Cecilia

    2014-01-01

    Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. The strategy of forecasting is implemented using two stages. In the first stage the time series is smoothed using either, 3-point moving average smoothing, or singular value Decomposition of the Hankel matrix (HSVD). In the second stage, an ARIMA model and two ANNs for one-step-ahead time series forecasting are used. The coefficients of the first ANN are estimated through the particle swarm optimization (PSO) learning algorithm, while the coefficients of the second ANN are estimated with the resilient backpropagation (RPROP) learning algorithm. The proposed models are evaluated using a weekly time series of traffic accidents of Valparaíso, Chilean region, from 2003 to 2012. The best result is given by the combination HSVD-ARIMA, with a MAPE of 0:26%, followed by MA-ARIMA with a MAPE of 1:12%; the worst result is given by the MA-ANN based on PSO with a MAPE of 15:51%.

  19. Assessment of the contribution of traffic emissions to the mobile vehicle measured PM2.5 concentration by means of WRF-CMAQ simulations.

    DOT National Transportation Integrated Search

    2012-03-01

    The Alaska adapted version of the Weather Research and Forecasting and the Community Modeling and Analysis Quality (WRF-CMAQ) modeling : systems was used to assess the contribution of traffic to the PM2.5-concentration in the Fairbanks nonattainment ...

  20. Contrail Tracking and ARM Data Product Development

    NASA Technical Reports Server (NTRS)

    Duda, David P.; Russell, James, III

    2005-01-01

    A contrail tracking system was developed to help in the assessment of the effect of commercial jet contrails on the Earth's radiative budget. The tracking system was built by combining meteorological data from the Rapid Update Cycle (RUC) numerical weather prediction model with commercial air traffic flight track data and satellite imagery. A statistical contrail-forecasting model was created a combination of surface-based contrail observations and numerical weather analyses and forecasts. This model allows predictions of widespread contrail occurrences for contrail research on either a real-time basis or for long-term time scales. Satellite-derived cirrus cloud properties in polluted and unpolluted regions were compared to determine the impact of air traffic on cirrus.

  1. Road traffic accidents prediction modelling: An analysis of Anambra State, Nigeria.

    PubMed

    Ihueze, Chukwutoo C; Onwurah, Uchendu O

    2018-03-01

    One of the major problems in the world today is the rate of road traffic crashes and deaths on our roads. Majority of these deaths occur in low-and-middle income countries including Nigeria. This study analyzed road traffic crashes in Anambra State, Nigeria with the intention of developing accurate predictive models for forecasting crash frequency in the State using autoregressive integrated moving average (ARIMA) and autoregressive integrated moving average with explanatory variables (ARIMAX) modelling techniques. The result showed that ARIMAX model outperformed the ARIMA (1,1,1) model generated when their performances were compared using the lower Bayesian information criterion, mean absolute percentage error, root mean square error; and higher coefficient of determination (R-Squared) as accuracy measures. The findings of this study reveal that incorporating human, vehicle and environmental related factors in time series analysis of crash dataset produces a more robust predictive model than solely using aggregated crash count. This study contributes to the body of knowledge on road traffic safety and provides an approach to forecasting using many human, vehicle and environmental factors. The recommendations made in this study if applied will help in reducing the number of road traffic crashes in Nigeria. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Smoothing Strategies Combined with ARIMA and Neural Networks to Improve the Forecasting of Traffic Accidents

    PubMed Central

    Rodríguez, Nibaldo

    2014-01-01

    Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. The strategy of forecasting is implemented using two stages. In the first stage the time series is smoothed using either, 3-point moving average smoothing, or singular value Decomposition of the Hankel matrix (HSVD). In the second stage, an ARIMA model and two ANNs for one-step-ahead time series forecasting are used. The coefficients of the first ANN are estimated through the particle swarm optimization (PSO) learning algorithm, while the coefficients of the second ANN are estimated with the resilient backpropagation (RPROP) learning algorithm. The proposed models are evaluated using a weekly time series of traffic accidents of Valparaíso, Chilean region, from 2003 to 2012. The best result is given by the combination HSVD-ARIMA, with a MAPE of 0 : 26%, followed by MA-ARIMA with a MAPE of 1 : 12%; the worst result is given by the MA-ANN based on PSO with a MAPE of 15 : 51%. PMID:25243200

  3. A quantitative analysis of inter-island telephony traffic in the Pacific Basin Region (PBR)

    NASA Technical Reports Server (NTRS)

    Evans, D. D.; Arth, C. H.

    1980-01-01

    As part of NASA's continuing assessment of future communication satellite requirements, a study was conducted to quantitatively scope current and future telecommunication traffic demand in the South Pacific Archipelagos. This demand was then converted to equivalent satellite transponder capacities. Only inter-island telephony traffic for the Pacific Basin Region was included. The results show that if all this traffic were carried by a satellite system, one-third of a satellite transponder would be needed to satisfy the base-year (1976-1977) requirement and about two-thirds of a satellite transponder would be needed to satisfy the forecasted 1985 requirement.

  4. Key Technology of Real-Time Road Navigation Method Based on Intelligent Data Research

    PubMed Central

    Tang, Haijing; Liang, Yu; Huang, Zhongnan; Wang, Taoyi; He, Lin; Du, Yicong; Ding, Gangyi

    2016-01-01

    The effect of traffic flow prediction plays an important role in routing selection. Traditional traffic flow forecasting methods mainly include linear, nonlinear, neural network, and Time Series Analysis method. However, all of them have some shortcomings. This paper analyzes the existing algorithms on traffic flow prediction and characteristics of city traffic flow and proposes a road traffic flow prediction method based on transfer probability. This method first analyzes the transfer probability of upstream of the target road and then makes the prediction of the traffic flow at the next time by using the traffic flow equation. Newton Interior-Point Method is used to obtain the optimal value of parameters. Finally, it uses the proposed model to predict the traffic flow at the next time. By comparing the existing prediction methods, the proposed model has proven to have good performance. It can fast get the optimal value of parameters faster and has higher prediction accuracy, which can be used to make real-time traffic flow prediction. PMID:27872637

  5. 46 CFR 185.304 - Navigation underway.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... direction of the transiting area; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused...

  6. 46 CFR 185.304 - Navigation underway.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... direction of the transiting area; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused...

  7. 46 CFR 185.304 - Navigation underway.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... direction of the transiting area; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused...

  8. 46 CFR 185.304 - Navigation underway.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... direction of the transiting area; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused...

  9. A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

    NASA Astrophysics Data System (ADS)

    Huang, Darong; Bai, Xing-Rong

    Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.

  10. 46 CFR 122.304 - Navigation underway.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused by own wake; (6) The danger...

  11. 46 CFR 122.304 - Navigation underway.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused by own wake; (6) The danger...

  12. 46 CFR 122.304 - Navigation underway.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused by own wake; (6) The danger...

  13. 46 CFR 122.304 - Navigation underway.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...; (2) Tidal state; (3) Prevailing and forecasted visibility and environmental conditions, including wind and waves; (4) Density of marine traffic; (5) Potential damage caused by own wake; (6) The danger...

  14. Objective Lightning Probability Forecasts for East-Central Florida Airports

    NASA Technical Reports Server (NTRS)

    Crawford, Winfred C.

    2013-01-01

    The forecasters at the National Weather Service in Melbourne, FL, (NWS MLB) identified a need to make more accurate lightning forecasts to help alleviate delays due to thunderstorms in the vicinity of several commercial airports in central Florida at which they are responsible for issuing terminal aerodrome forecasts. Such forecasts would also provide safer ground operations around terminals, and would be of value to Center Weather Service Units serving air traffic controllers in Florida. To improve the forecast, the AMU was tasked to develop an objective lightning probability forecast tool for the airports using data from the National Lightning Detection Network (NLDN). The resulting forecast tool is similar to that developed by the AMU to support space launch operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) for use by the 45th Weather Squadron (45 WS) in previous tasks (Lambert and Wheeler 2005, Lambert 2007). The lightning probability forecasts are valid for the time periods and areas needed by the NWS MLB forecasters in the warm season months, defined in this task as May-September.

  15. Data Mining for Understanding and Impriving Decision-Making Affecting Ground Delay Programs

    NASA Technical Reports Server (NTRS)

    Kulkarni, Deepak; Wang, Yao Xun; Sridhar, Banavar

    2013-01-01

    The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions. The work reported in this paper is focused on ground delay programs. Data mining algorithms have the potential to develop associations between weather patterns and the corresponding ground delay program responses. If successful, they can be used to improve and standardize TFM decision resulting in better predictability of traffic flows on days with reliable weather forecasts. The approach here seeks to develop a set of data mining and machine learning models and apply them to historical archives of weather observations and forecasts and TFM initiatives to determine the extent to which the theory can predict and explain the observed traffic flow behaviors.

  16. The Impact of Trajectory Prediction Uncertainty on Air Traffic Controller Performance and Acceptability

    NASA Technical Reports Server (NTRS)

    Mercer, Joey S.; Bienert, Nancy; Gomez, Ashley; Hunt, Sarah; Kraut, Joshua; Martin, Lynne; Morey, Susan; Green, Steven M.; Prevot, Thomas; Wu, Minghong G.

    2013-01-01

    A Human-In-The-Loop air traffic control simulation investigated the impact of uncertainties in trajectory predictions on NextGen Trajectory-Based Operations concepts, seeking to understand when the automation would become unacceptable to controllers or when performance targets could no longer be met. Retired air traffic controllers staffed two en route transition sectors, delivering arrival traffic to the northwest corner-post of Atlanta approach control under time-based metering operations. Using trajectory-based decision-support tools, the participants worked the traffic under varying levels of wind forecast error and aircraft performance model error, impacting the ground automations ability to make accurate predictions. Results suggest that the controllers were able to maintain high levels of performance, despite even the highest levels of trajectory prediction errors.

  17. Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

    PubMed Central

    Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei

    2017-01-01

    Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction. PMID:28672867

  18. Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks.

    PubMed

    Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei

    2017-06-26

    Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.

  19. Flight Deck Weather Avoidance Decision Support: Implementation and Evaluation

    NASA Technical Reports Server (NTRS)

    Wu, Shu-Chieh; Luna, Rocio; Johnson, Walter W.

    2013-01-01

    Weather related disruptions account for seventy percent of the delays in the National Airspace System (NAS). A key component in the weather plan of the Next Generation of Air Transportation System (NextGen) is to assimilate observed weather information and probabilistic forecasts into the decision process of flight crews and air traffic controllers. In this research we explore supporting flight crew weather decision making through the development of a flight deck predicted weather display system that utilizes weather predictions generated by ground-based radar. This system integrates and presents this weather information, together with in-flight trajectory modification tools, within a cockpit display of traffic information (CDTI) prototype. that the CDTI features 2D and perspective 3D visualization models of weather. The weather forecast products that we implemented were the Corridor Integrated Weather System (CIWS) and the Convective Weather Avoidance Model (CWAM), both developed by MIT Lincoln Lab. We evaluated the use of CIWS and CWAM for flight deck weather avoidance in two part-task experiments. Experiment 1 compared pilots' en route weather avoidance performance in four weather information conditions that differed in the type and amount of predicted forecast (CIWS current weather only, CIWS current and historical weather, CIWS current and forecast weather, CIWS current and forecast weather and CWAM predictions). Experiment 2 compared the use of perspective 3D and 21/2D presentations of weather for flight deck weather avoidance. Results showed that pilots could take advantage of longer range predicted weather forecasts in performing en route weather avoidance but more research will be needed to determine what combinations of information are optimal and how best to present them.

  20. Capacity-constrained traffic assignment in networks with residual queues

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lam, W.H.K.; Zhang, Y.

    2000-04-01

    This paper proposes a capacity-constrained traffic assignment model for strategic transport planning in which the steady-state user equilibrium principle is extended for road networks with residual queues. Therefore, the road-exit capacity and the queuing effects can be incorporated into the strategic transport model for traffic forecasting. The proposed model is applicable to the congested network particularly when the traffic demands exceeds the capacity of the network during the peak period. An efficient solution method is proposed for solving the steady-state traffic assignment problem with residual queues. Then a simple numerical example is employed to demonstrate the application of the proposedmore » model and solution method, while an example of a medium-sized arterial highway network in Sioux Falls, South Dakota, is used to test the applicability of the proposed solution to real problems.« less

  1. Convective Weather Avoidance with Uncertain Weather Forecasts

    NASA Technical Reports Server (NTRS)

    Karahan, Sinan; Windhorst, Robert D.

    2009-01-01

    Convective weather events have a disruptive impact on air traffic both in terminal area and in en-route airspaces. In order to make sure that the national air transportation system is safe and efficient, it is essential to respond to convective weather events effectively. Traffic flow control initiatives in response to convective weather include ground delay, airborne delay, miles-in-trail restrictions as well as tactical and strategic rerouting. The rerouting initiatives can potentially increase traffic density and complexity in regions neighboring the convective weather activity. There is a need to perform rerouting in an intelligent and efficient way such that the disruptive effects of rerouting are minimized. An important area of research is to study the interaction of in-flight rerouting with traffic congestion or complexity and developing methods that quantitatively measure this interaction. Furthermore, it is necessary to find rerouting solutions that account for uncertainties in weather forecasts. These are important steps toward managing complexity during rerouting operations, and the paper is motivated by these research questions. An automated system is developed for rerouting air traffic in order to avoid convective weather regions during the 20- minute - 2-hour time horizon. Such a system is envisioned to work in concert with separation assurance (0 - 20-minute time horizon), and longer term air traffic management (2-hours and beyond) to provide a more comprehensive solution to complexity and safety management. In this study, weather is dynamic and uncertain; it is represented as regions of airspace that pilots are likely to avoid. Algorithms are implemented in an air traffic simulation environment to support the research study. The algorithms used are deterministic but periodically revise reroutes to account for weather forecast updates. In contrast to previous studies, in this study convective weather is represented as regions of airspace that pilots are likely to avoid. The automated system periodically updates forecasts and reassesses rerouting decisions in order to account for changing weather predictions. The main objectives are to reroute flights to avoid convective weather regions and determine the resulting complexity due to rerouting. The eventual goal is to control and reduce complexity while rerouting flights during the 20 minute - 2 hour planning period. A three-hour simulation is conducted using 4800 flights in the national airspace. The study compares several metrics against a baseline scenario using the same traffic and weather but with rerouting disabled. The results show that rerouting can have a negative impact on congestion in some sectors, as expected. The rerouting system provides accurate measurements of the resulting complexity in the congested sectors. Furthermore, although rerouting is performed only in the 20-minute - 2-hour range, it results in a 30% reduction in encounters with nowcast weather polygons (100% being the ideal for perfectly predictable and accurate weather). In the simulations, rerouting was performed for the 20-minute - 2-hour flight time horizon, and for the en-route segment of air traffic. The implementation uses CWAM, a set of polygons that represent probabilities of pilot deviation around weather. The algorithms were implemented in a software-based air traffic simulation system. Initial results of the system's performance and effectiveness were encouraging. Simulation results showed that when flights were rerouted in the 20-minute - 2-hour flight time horizon of air traffic, there were fewer weather encounters in the first 20 minutes than for flights that were not rerouted. Some preliminary results were also obtained that showed that rerouting will also increase complexity. More simulations will be conducted in order to report conclusive results on the effects of rerouting on complexity. Thus, the use of the 20-minute - 2-hour flight time horizon weather avoidance teniques performed in the simulation is expected to provide benefits for short-term weather avoidance.

  2. TRANPLAN and GIS support for agencies in Alabama

    DOT National Transportation Integrated Search

    2001-08-06

    Travel demand models are computerized programs intended to forecast future roadway traffic volumes for a community based on selected socioeconomic variables and travel behavior algorithms. Software to operate these travel demand models is currently a...

  3. FAA Aviation Forecasts Fiscal Years 1988-1999.

    DTIC Science & Technology

    1988-02-01

    in the 48 contiguous States, Hawaii, Puerto Rico, and the U.S. Virgin Islands. Excluded fromn the data base is activity in Alaska, other U.S...passengerl miles increased b%-’"’. 17.2 percent. Traffic in Hawaii, Puerto Rico, and the U.S. Virgin Islands, ., Ihio wevr, haid slower growth with passenger...trip length for Hawaii/Puerto Rico/ Virgin Islands is expected to remain constant at 98.0 miles over the forecast period. The average industry load

  4. Super Ensemble-based Aviation Turbulence Guidance (SEATG) for Air Traffic Management (ATM)

    NASA Astrophysics Data System (ADS)

    Kim, Jung-Hoon; Chan, William; Sridhar, Banavar; Sharman, Robert

    2014-05-01

    Super Ensemble (ensemble of ten turbulence metrics from time-lagged ensemble members of weather forecast data)-based Aviation Turbulence Guidance (SEATG) is developed using Weather Research and Forecasting (WRF) model and in-situ eddy dissipation rate (EDR) observations equipped on commercial aircraft over the contiguous United States. SEATG is a sequence of five procedures including weather modeling, calculating turbulence metrics, mapping EDR-scale, evaluating metrics, and producing final SEATG forecast. This uses similar methodology to the operational Graphic Turbulence Guidance (GTG) with three major improvements. First, SEATG use a higher resolution (3-km) WRF model to capture cloud-resolving scale phenomena. Second, SEATG computes turbulence metrics for multiple forecasts that are combined at the same valid time resulting in an time-lagged ensemble of multiple turbulence metrics. Third, SEATG provides both deterministic and probabilistic turbulence forecasts to take into account weather uncertainties and user demands. It is found that the SEATG forecasts match well with observed radar reflectivity along a surface front as well as convectively induced turbulence outside the clouds on 7-8 Sep 2012. And, overall performance skill of deterministic SEATG against the observed EDR data during this period is superior to any single turbulence metrics. Finally, probabilistic SEATG is used as an example application of turbulence forecast for air-traffic management. In this study, a simple Wind-Optimal Route (WOR) passing through the potential areas of probabilistic SEATG and Lateral Turbulence Avoidance Route (LTAR) taking into account the SEATG are calculated at z = 35000 ft (z = 12 km) from Los Angeles to John F. Kennedy international airports. As a result, WOR takes total of 239 minutes with 16 minutes of SEATG areas for 40% of moderate turbulence potential, while LTAR takes total of 252 minutes travel time that 5% of fuel would be additionally consumed to entirely avoid the moderate SEATG regions.

  5. Non-urban mobile radio market demand forecast

    NASA Technical Reports Server (NTRS)

    Castruccio, P. A.; Cooper, J.

    1982-01-01

    A national nonmetropolitan land mobile traffic model for 1990-2000 addresses user classes, density classes, traffic mix statistics, distance distribution, geographic distribution, price elasticity, and service quality elasticity. Traffic demands for business, special industrial, and police were determined on the basis of surveys in 73 randomly selected nonurban counties. The selected services represent 69% of total demand. The results were extrapolated to all services in the non-SMSA areas of the contiguous United States. Radiotelephone services were considered separately. Total non-SMSA mobile radio demand (one way) estimates are given. General functional requirements include: hand portability, privacy, reduction of blind spots, two way data transmission, position location, slow scan imagery.

  6. Fast and optimized methodology to generate road traffic emission inventories and their uncertainties

    NASA Astrophysics Data System (ADS)

    Blond, N.; Ho, B. Q.; Clappier, A.

    2012-04-01

    Road traffic emissions are one of the main sources of air pollution in the cities. They are also the main sources of uncertainties in the air quality numerical models used to forecast and define abatement strategies. Until now, the available models for generating road traffic emission always required a big effort, money and time. This inhibits decisions to preserve air quality, especially in developing countries where road traffic emissions are changing very fast. In this research, we developed a new model designed to fast produce road traffic emission inventories. This model, called EMISENS, combines the well-known top-down and bottom-up approaches to force them to be coherent. A Monte Carlo methodology is included for computing emission uncertainties and the uncertainty rate due to each input parameters. This paper presents the EMISENS model and a demonstration of its capabilities through an application over Strasbourg region (Alsace), France. Same input data as collected for Circul'air model (using bottom-up approach) which has been applied for many years to forecast and study air pollution by the Alsatian air quality agency, ASPA, are used to evaluate the impact of several simplifications that a user could operate . These experiments give the possibility to review older methodologies and evaluate EMISENS results when few input data are available to produce emission inventories, as in developing countries and assumptions need to be done. We show that same average fraction of mileage driven with a cold engine can be used for all the cells of the study domain and one emission factor could replace both cold and hot emission factors.

  7. An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management.

    PubMed

    Bongiorno, Christian; Miccichè, Salvatore; Mantegna, Rosario N

    2017-01-01

    We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers' operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i) in the presence of perfect forecast ability of controllers, and (ii) in the presence of some degree of uncertainty in flight trajectory forecast.

  8. An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management

    PubMed Central

    Bongiorno, Christian; Mantegna, Rosario N.

    2017-01-01

    We present an agent based model of the Air Traffic Management socio-technical complex system aiming at modeling the interactions between aircraft and air traffic controllers at a tactical level. The core of the model is given by the conflict detection and resolution module and by the directs module. Directs are flight shortcuts that are given by air controllers to speed up the passage of an aircraft within a certain airspace and therefore to facilitate airline operations. Conflicts between flight trajectories can occur for two main reasons: either the planning of the flight trajectory was not sufficiently detailed to rule out all potential conflicts or unforeseen events during the flight require modifications of the flight plan that can conflict with other flight trajectories. Our model performs a local conflict detection and resolution procedure. Once a flight trajectory has been made conflict-free, the model searches for possible improvements of the system efficiency by issuing directs. We give an example of model calibration based on real data. We then provide an illustration of the capability of our model in generating scenario simulations able to give insights about the air traffic management system. We show that the calibrated model is able to reproduce the existence of a geographical localization of air traffic controllers’ operations. Finally, we use the model to investigate the relationship between directs and conflict resolutions (i) in the presence of perfect forecast ability of controllers, and (ii) in the presence of some degree of uncertainty in flight trajectory forecast. PMID:28419160

  9. Enhanced Framework for Modeling Urban Truck Trips

    DOT National Transportation Integrated Search

    1998-09-16

    Recently there has been renewed interest in modeling urban truck movements. : This is potentially important for improving traffic forecasts as well as for a : host of other applications including ITS. There are unique aspects of urban : freight movem...

  10. Small city synthesis of transportation planning and economic development : user's guide

    DOT National Transportation Integrated Search

    1999-10-01

    Using Alice, Texas, as a model, a template has been developed to increase the cooperation and communication between transportation planning and economic development groups. The template establishes a foundation for coordinating traffic forecasts with...

  11. Air pollution forecasting in Ankara, Turkey using air pollution index and its relation to assimilative capacity of the atmosphere.

    PubMed

    Genc, D Deniz; Yesilyurt, Canan; Tuncel, Gurdal

    2010-07-01

    Spatial and temporal variations in concentrations of CO, NO, NO(2), SO(2), and PM(10), measured between 1999 and 2000, at traffic-impacted and residential stations in Ankara were investigated. Air quality in residential areas was found to be influenced by traffic activities in the city. Pollutant ratios were proven to be reliable tracers to differentiate between different sources. Air pollution index (API) of the whole city was calculated to evaluate the level of air quality in Ankara. Multiple linear regression model was developed for forecasting API in Ankara. The correlation coefficients were found to be 0.79 and 0.63 for different time periods. The assimilative capacity of Ankara atmosphere was calculated in terms of ventilation coefficient (VC). The relation between API and VC was investigated and found that the air quality in Ankara was determined by meteorology rather than emissions.

  12. Future Air Traffic Growth and Schedule Model, Supplement

    NASA Technical Reports Server (NTRS)

    Kimmel, William M. (Technical Monitor); Smith, Jeremy C.; Dollyhigh, Samuel M.

    2004-01-01

    The Future Air Traffic Growth and Schedule Model was developed as an implementation of the Fratar algorithm to project future traffic flow between airports in a system and of then scheduling the additional flights to reflect current passenger time-of-travel preferences. The methodology produces an unconstrained future schedule from a current (or baseline) schedule and the airport operations growth rates. As an example of the use of the model, future schedules are projected for 2010 and 2022 for all flights arriving at, departing from, or flying between all continental United States airports that had commercial scheduled service for May 17, 2002. Inter-continental US traffic and airports are included and the traffic is also grown with the Fratar methodology to account for their arrivals and departures to the continental US airports. Input data sets derived from the Official Airline Guide (OAG) data and FAA Terminal Area Forecast (TAF) are included in the examples of the computer code execution.

  13. Expanding Regional Airport Usage to Accommodate Increased Air Traffic Demand

    NASA Technical Reports Server (NTRS)

    Russell, Carl R.

    2009-01-01

    Small regional airports present an underutilized source of capacity in the national air transportation system. This study sought to determine whether a 50 percent increase in national operations could be achieved by limiting demand growth at large hub airports and instead growing traffic levels at the surrounding regional airports. This demand scenario for future air traffic in the United States was generated and used as input to a 24-hour simulation of the national airspace system. Results of the demand generation process and metrics predicting the simulation results are presented, in addition to the actual simulation results. The demand generation process showed that sufficient runway capacity exists at regional airports to offload a significant portion of traffic from hub airports. Predictive metrics forecast a large reduction of delays at most major airports when demand is shifted. The simulation results then show that offloading hub traffic can significantly reduce nationwide delays.

  14. Military, Charter, Unreported Domestic Traffic and General Aviation 1976, 1984, 1992, and 2015 Emission Scenarios

    NASA Technical Reports Server (NTRS)

    Mortlock, Alan; VanAlstyne, Richard

    1998-01-01

    The report describes development of databases estimating aircraft engine exhaust emissions for the years 1976 and 1984 from global operations of Military, Charter, historic Soviet and Chinese, Unreported Domestic traffic, and General Aviation (GA). These databases were developed under the National Aeronautics and Space Administration's (NASA) Advanced Subsonic Assessment (AST). McDonnell Douglas Corporation's (MDC), now part of the Boeing Company has previously estimated engine exhaust emissions' databases for the baseline year of 1992 and a 2015 forecast year scenario. Since their original creation, (Ward, 1994 and Metwally, 1995) revised technology algorithms have been developed. Additionally, GA databases have been created and all past NIDC emission inventories have been updated to reflect the new technology algorithms. Revised data (Baughcum, 1996 and Baughcum, 1997) for the scheduled inventories have been used in this report to provide a comparison of the total aviation emission forecasts from various components. Global results of two historic years (1976 and 1984), a baseline year (1992) and a forecast year (2015) are presented. Since engine emissions are directly related to fuel usage, an overview of individual aviation annual global fuel use for each inventory component is also given in this report.

  15. Analyzing the evolutionary mechanisms of the Air Transportation System-of-Systems using network theory and machine learning algorithms

    NASA Astrophysics Data System (ADS)

    Kotegawa, Tatsuya

    Complexity in the Air Transportation System (ATS) arises from the intermingling of many independent physical resources, operational paradigms, and stakeholder interests, as well as the dynamic variation of these interactions over time. Currently, trade-offs and cost benefit analyses of new ATS concepts are carried out on system-wide evaluation simulations driven by air traffic forecasts that assume fixed airline routes. However, this does not well reflect reality as airlines regularly add and remove routes. A airline service route network evolution model that projects route addition and removal was created and combined with state-of-the-art air traffic forecast methods to better reflect the dynamic properties of the ATS in system-wide simulations. Guided by a system-of-systems framework, network theory metrics and machine learning algorithms were applied to develop the route network evolution models based on patterns extracted from historical data. Constructing the route addition section of the model posed the greatest challenge due to the large pool of new link candidates compared to the actual number of routes historically added to the network. Of the models explored, algorithms based on logistic regression, random forests, and support vector machines showed best route addition and removal forecast accuracies at approximately 20% and 40%, respectively, when validated with historical data. The combination of network evolution models and a system-wide evaluation tool quantified the impact of airline route network evolution on air traffic delay. The expected delay minutes when considering network evolution increased approximately 5% for a forecasted schedule on 3/19/2020. Performance trade-off studies between several airline route network topologies from the perspectives of passenger travel efficiency, fuel burn, and robustness were also conducted to provide bounds that could serve as targets for ATS transformation efforts. The series of analysis revealed that high robustness is achievable only in exchange of lower passenger travel and fuel burn efficiency. However, increase in the network density can mitigate this trade-off.

  16. Economic development, mobility and traffic accidents in Algeria.

    PubMed

    Bougueroua, M; Carnis, L

    2016-07-01

    The aim of this contribution is to estimate the impact of road economic conditions and mobility on traffic accidents for the case of Algeria. Using the cointegration approach and vector error correction model (VECM), we will examine simultaneously short term and long-term impacts between the number of traffic accidents, fuel consumption and gross domestic product (GDP) per capital, over the period 1970-2013. The main results of the estimation show that the number of traffic accidents in Algeria is positively influenced by the GDP per capita in the short and long term. It implies that a higher economic development worsens the road safety situation. However, the new traffic rules adopted in 2009 have an impact on the forecast trend of traffic accidents, meaning efficient public policy could improve the situation. This result calls for a strong political commitment with effective countermeasures for avoiding the further deterioration of road safety record in Algeria. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Domestic & International Air Cargo Activity: National and Selected Hub Forecasts.

    DTIC Science & Technology

    1979-11-01

    111371 1991 1887811 2?. 768 :297968 Forecast utilizes 1972 dollar GNP from Wharton’s annual model, December 6, 1978, Post-Meeting Control Solution...mile based on 1973 revenue ton-miles reported in the DOT/CAB, Air Carrier Traffic Statistics. South America - RSA - simple average of American (Latin...9518 F (2/11) = 129.347 DW = 1.41 (b) South America (ESA) 4 = 11.8926 + 18.2908* (GDPSA.C) - 8.94307* ( RSA ) 4 (0.14) (6.08) (-0.46) R2 .8717 F (2/11

  18. Forecasting the clearance time of freeway accidents

    DOT National Transportation Integrated Search

    2002-01-01

    Freeway congestion is a major and costly problem in many U.S. metropolitan areas. From a traveler's perspective, congestion has costs in terms of longer travel times and lost productivity. From the traffic manager's perspective, congestion causes a f...

  19. The 30/20 GHz fixed communications systems service demand assessment. Volume 3: Appendices

    NASA Technical Reports Server (NTRS)

    Gabriszeski, T.; Reiner, P.; Rogers, J.; Terbo, W.

    1979-01-01

    The market analysis of voice, video, and data 18/30 GHz communications systems services and satellite transmission services is discussed. Detail calculations, computer displays of traffic, survey questionnaires, and detailed service forecasts are presented.

  20. Large-Scale Traffic Microsimulation From An MPO Perspective

    DOT National Transportation Integrated Search

    1997-01-01

    One potential advancement of the four-step travel model process is the forecasting and simulation of individual activities and travel. A common concern with such an approach is that the data and computational requirements for a large-scale, regional ...

  1. 23 CFR 973.104 - Definitions.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... cost-effective pavement reconstruction, rehabilitation, and preventive maintenance programs and policies, and that results in pavement designed to accommodate current and forecasted traffic in a safe... goods to levels that meet Federal, State and local needs. Indian lands pavement management system (PMS...

  2. 23 CFR 973.104 - Definitions.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... cost-effective pavement reconstruction, rehabilitation, and preventive maintenance programs and policies, and that results in pavement designed to accommodate current and forecasted traffic in a safe... goods to levels that meet Federal, State and local needs. Indian lands pavement management system (PMS...

  3. 23 CFR 973.104 - Definitions.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... cost-effective pavement reconstruction, rehabilitation, and preventive maintenance programs and policies, and that results in pavement designed to accommodate current and forecasted traffic in a safe... goods to levels that meet Federal, State and local needs. Indian lands pavement management system (PMS...

  4. 23 CFR 973.104 - Definitions.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... cost-effective pavement reconstruction, rehabilitation, and preventive maintenance programs and policies, and that results in pavement designed to accommodate current and forecasted traffic in a safe... goods to levels that meet Federal, State and local needs. Indian lands pavement management system (PMS...

  5. 23 CFR 973.104 - Definitions.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... cost-effective pavement reconstruction, rehabilitation, and preventive maintenance programs and policies, and that results in pavement designed to accommodate current and forecasted traffic in a safe... goods to levels that meet Federal, State and local needs. Indian lands pavement management system (PMS...

  6. Freeway travel-time estimation and forecasting.

    DOT National Transportation Integrated Search

    2013-03-01

    Real-time traffic information provided by GDOT has proven invaluable for commuters in the : Georgia freeway network. The increasing number of Variable Message Signs, addition of : services such as My-NaviGAtor, NaviGAtor-to-go etc. and the advancemen...

  7. Geostationary platform systems concepts definition study. Volume 2A: Appendixes, book 1

    NASA Technical Reports Server (NTRS)

    1980-01-01

    Appendixes addressing various aspects of a geostationary platform concepts definition study are given. Communication platform traffic requirements, video conferencing forecast, intersatellite link capacity requirements, link budgets, payload data, payload assignments, and platform synthesis are addressed.

  8. Traffic flow forecasting using approximate nearest neighbor nonparametric regression

    DOT National Transportation Integrated Search

    2000-12-01

    The purpose of this research is to enhance nonparametric regression (NPR) for use in real-time systems by first reducing execution time using advanced data structures and imprecise computations and then developing a methodology for applying NPR. Due ...

  9. Framework for multi-resolution analyses of advanced traffic management strategies.

    DOT National Transportation Integrated Search

    2016-11-01

    Demand forecasting models and simulation models have been developed, calibrated, and used in isolation of each other. However, the advancement of transportation system technologies and strategies, the increase in the availability of data, and the unc...

  10. Increasing accuracy of vehicle speed measurement in congested traffic over dual-loop sensors.

    DOT National Transportation Integrated Search

    2014-09-01

    Classified vehicle counts are a critical measure for forecasting the health of the roadway infrastructure : and for planning future improvements to the transportation network. Balancing the cost of data : collection with the fidelity of the measureme...

  11. Development of a prototype land use model for statewide transportation planning activities.

    DOT National Transportation Integrated Search

    2011-11-30

    Future land use forecasting is an important input to transportation planning modeling. Traditionally, land use is allocated to individual : traffic analysis zones (TAZ) based on variables such as the amount of vacant land, zoning restriction, land us...

  12. A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs.

    PubMed

    Mo, Yuanfu; Yu, Dexin; Song, Jun; Zheng, Kun; Guo, Yajuan

    2015-01-01

    In a vehicular ad hoc network (VANET), the periodic exchange of single-hop status information broadcasts (beacon frames) produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network.

  13. A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs

    PubMed Central

    Mo, Yuanfu; Yu, Dexin; Song, Jun; Zheng, Kun; Guo, Yajuan

    2015-01-01

    In a vehicular ad hoc network (VANET), the periodic exchange of single-hop status information broadcasts (beacon frames) produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network. PMID:26571042

  14. Dynamic Transportation Navigation

    NASA Astrophysics Data System (ADS)

    Meng, Xiaofeng; Chen, Jidong

    Miniaturization of computing devices, and advances in wireless communication and sensor technology are some of the forces that are propagating computing from the stationary desktop to the mobile outdoors. Some important classes of new applications that will be enabled by this revolutionary development include intelligent traffic management, location-based services, tourist services, mobile electronic commerce, and digital battlefield. Some existing application classes that will benefit from the development include transportation and air traffic control, weather forecasting, emergency response, mobile resource management, and mobile workforce. Location management, i.e., the management of transient location information, is an enabling technology for all these applications. In this chapter, we present the applications of moving objects management and their functionalities, in particular, the application of dynamic traffic navigation, which is a challenge due to the highly variable traffic state and the requirement of fast, on-line computations.

  15. Market capture by 30/20 GHz satellite systems, volume 2

    NASA Technical Reports Server (NTRS)

    Gamble, R. B.; Saporta, L.

    1981-01-01

    Results of a telecommunications demand study are presented. Forecasts of demand for 30/20 GHz satellite systems, and the expected build up of traffic on these systems are given as a function of time for each of several operational scenarios.

  16. February 11, 2009, Subcommittee on Aviation Hearing on FAA Reauthorization Act of 2009 questions for the record.

    DOT National Transportation Integrated Search

    2009-02-01

    The next generation air transportation system (NextGen) includes the : policies, procedures, and equipment that will allow satellite-based navigation in the : national airspace system. However, this systems ability to meet forecasted traffic : vol...

  17. MAG traffic generator study : survey data from Arizona State University

    DOT National Transportation Integrated Search

    1994-12-01

    The Maricopa Association of Governments (MAG) is responsible for the travel demand models used to forecast multi-modal travel behavior in the Phoenix metropolitan area. The main campus of Arizona State University (ASU), located in Tempe, is one of th...

  18. Market capture by 30/20 GHz satellite systems, volume 2

    NASA Astrophysics Data System (ADS)

    Gamble, R. B.; Saporta, L.

    1981-04-01

    Results of a telecommunications demand study are presented. Forecasts of demand for 30/20 GHz satellite systems, and the expected build up of traffic on these systems are given as a function of time for each of several operational scenarios.

  19. Information Requirements for Supervisory Air Traffic Controllers in Support of a Wake Vortex Departure System

    NASA Technical Reports Server (NTRS)

    Lohr, Gary W.; Williams, Daniel M.; Trujillo, Anna C.

    2008-01-01

    Closely Space Parallel Runway (CSPR) configurations are capacity limited for departures due to the requirement to apply wake vortex separation standards from traffic departing on the adjacent parallel runway. To mitigate the effects of this constraint, a concept focusing on wind dependent departure operations has been developed, known as the Wake Turbulence Mitigation for Departures (WTMD). This concept takes advantage of the fact that crosswinds of sufficient velocity blow wakes generated by aircraft departing from the downwind runway away from the upwind runway. Consequently, under certain conditions, wake separations on the upwind runway would not be required based on wakes generated by aircraft on the downwind runway, as is currently the case. It follows that information requirements, and sources for this information, would need to be determined for airport traffic control tower (ATCT) supervisory personnel who would be charged with decisions regarding use of the procedure. To determine the information requirements, data were collected from ATCT supervisors and controller-in-charge qualified individuals at Lambert-St. Louis International Airport (STL) and George Bush Houston Intercontinental Airport (IAH). STL and IAH were chosen as data collection sites based on the implementation of a WTMD prototype system, operating in shadow mode, at these locations. The 17 total subjects (STL: 5, IAH: 12) represented a broad-base of air traffic experience. Results indicated that the following information was required to support the conduct of WTMD operations: current and forecast weather information, current and forecast traffic demand and traffic flow restrictions, and WTMD System status information and alerting. Subjects further indicated that the requisite information is currently available in the tower cab with the exception of the WTMD status and alerting. Subjects were given a demonstration of a display supporting the prototype systems and unanimously stated that the WTMD status information they felt important was represented. Overwhelmingly, subjects felt that approving, monitoring and terminating the WTMD procedure could be integrated into their supervisory workload.

  20. A state of the art regarding urban air quality prediction models

    NASA Astrophysics Data System (ADS)

    Croitoru, Cristiana; Nastase, Ilinca

    2018-02-01

    Urban pollution represents an increasing risk to residents of urban regions, particularly in large, over-industrialized cities knowing that the traffic is responsible for more than 25% of air gaseous pollutants and dust particles. Air quality modelling plays an important role in addressing air pollution control and management approaches by providing guidelines for better and more efficient air quality forecasting, along with smart monitoring sensor networks. The advances in technology regarding simulations, forecasting and monitoring are part of the new smart cities which offers a healthy environment for their occupants.

  1. Assessment of historical and projected segments of US and world civil and military rotorcraft markets, 1960 - 1990

    NASA Technical Reports Server (NTRS)

    Yates, W. J.

    1981-01-01

    The geographic climatic, political, economic and demographic environment of 75 countries was analyzed with respect to helicopter procurement history and usage. Key environmental indicators which are variables were projected into strengths and weaknesses of U.S. technology are reviewed. The civil market sensitivity to new technology is forecast with selected premises as to vehicle life, noise standards, fuel costs, GNP expansion and traffic growth. The forecast is based on a scenario of helicopter technology improvements resulting in increased size and performance.

  2. Future Air Traffic Growth and Schedule Model User's Guide

    NASA Technical Reports Server (NTRS)

    Kimmel, William M. (Technical Monitor); Smith, Jeremy C.; Dollyhigh, Samuel M.

    2004-01-01

    The Future Air Traffic Growth and Schedule Model was developed as an implementation of the Fratar algorithm to project future traffic flow between airports in a system and of then scheduling the additional flights to reflect current passenger time-of-travel preferences. The methodology produces an unconstrained future schedule from a current (or baseline) schedule and the airport operations growth rates. As an example of the use of the model, future schedules are projected for 2010 and 2022 for all flights arriving at, departing from, or flying between all continental United States airports that had commercial scheduled service for May 17, 2002. Inter-continental US traffic and airports are included and the traffic is also grown with the Fratar methodology to account for their arrivals and departures to the continental US airports. Input data sets derived from the Official Airline Guide (OAG) data and FAA Terminal Area Forecast (TAF) are included in the examples of the computer code execution.

  3. State criminal justice telecommunications (STACOM). Volume 1: Executive summary

    NASA Technical Reports Server (NTRS)

    Fielding, J. E.; Frewing, H. K.; Lee, J. J.; Leflang, W. G.; Reilly, N. B.

    1977-01-01

    Techniques for identifying user requirements and network designs for criminal justice networks on a state wide basis are discussed. Topics covered include: methods for determining data required; data collection and survey; data organization procedures, and methods for forecasting network traffic volumes. Developed network design techniques center around a computerized topology program which enables the user to generate least cost network topologies that satisfy network traffic requirements, response time requirements and other specified functional requirements. The developed techniques were applied in Texas and Ohio, and results of these studies are presented.

  4. Final research findings on traffic-load forecasting using weigh-in-motion data

    DOT National Transportation Integrated Search

    1998-09-01

    The overall objective of Project 7-987 was to develop a long-range pavement rehabilitation plan for a segment of US 59, a four-lane divided principal arterial highway in TxDOT's Lufkin District. To identify feasible pavement : structures, test sectio...

  5. Developing a stochastic traffic volume prediction model for public-private partnership projects

    NASA Astrophysics Data System (ADS)

    Phong, Nguyen Thanh; Likhitruangsilp, Veerasak; Onishi, Masamitsu

    2017-11-01

    Transportation projects require an enormous amount of capital investment resulting from their tremendous size, complexity, and risk. Due to the limitation of public finances, the private sector is invited to participate in transportation project development. The private sector can entirely or partially invest in transportation projects in the form of Public-Private Partnership (PPP) scheme, which has been an attractive option for several developing countries, including Vietnam. There are many factors affecting the success of PPP projects. The accurate prediction of traffic volume is considered one of the key success factors of PPP transportation projects. However, only few research works investigated how to predict traffic volume over a long period of time. Moreover, conventional traffic volume forecasting methods are usually based on deterministic models which predict a single value of traffic volume but do not consider risk and uncertainty. This knowledge gap makes it difficult for concessionaires to estimate PPP transportation project revenues accurately. The objective of this paper is to develop a probabilistic traffic volume prediction model. First, traffic volumes were estimated following the Geometric Brownian Motion (GBM) process. Monte Carlo technique is then applied to simulate different scenarios. The results show that this stochastic approach can systematically analyze variations in the traffic volume and yield more reliable estimates for PPP projects.

  6. A maritime decision support system to assess risk in the presence of environmental uncertainties: the REP10 experiment

    NASA Astrophysics Data System (ADS)

    Grasso, Raffaele; Cococcioni, Marco; Mourre, Baptiste; Chiggiato, Jacopo; Rixen, Michel

    2012-03-01

    The aim of this work is to report on an activity carried out during the 2010 Recognized Environmental Picture experiment, held in the Ligurian Sea during summer 2010. The activity was the first at-sea test of the recently developed decision support system (DSS) for operation planning, which had previously been tested in an artificial experiment. The DSS assesses the impact of both environmental conditions (meteorological and oceanographic) and non-environmental conditions (such as traffic density maps) on people and assets involved in the operation and helps in deciding a course of action that allows safer operation. More precisely, the environmental variables (such as wind speed, current speed and significant wave height) taken as input by the DSS are the ones forecasted by a super-ensemble model, which fuses the forecasts provided by multiple forecasting centres. The uncertainties associated with the DSS's inputs (generally due to disagreement between forecasts) are propagated through the DSS's output by using the unscented transform. In this way, the system is not only able to provide a traffic light map ( run/ not run the operation), but also to specify the confidence level associated with each action. This feature was tested on a particular type of operation with underwater gliders: the glider surfacing for data transmission. It is also shown how the availability of a glider path prediction tool provides surfacing options along the predicted path. The applicability to different operations is demonstrated by applying the same system to support diver operations.

  7. A SPATIOTEMPORAL APPROACH FOR HIGH RESOLUTION TRAFFIC FLOW IMPUTATION

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Han, Lee; Chin, Shih-Miao; Hwang, Ho-Ling

    Along with the rapid development of Intelligent Transportation Systems (ITS), traffic data collection technologies have been evolving dramatically. The emergence of innovative data collection technologies such as Remote Traffic Microwave Sensor (RTMS), Bluetooth sensor, GPS-based Floating Car method, automated license plate recognition (ALPR) (1), etc., creates an explosion of traffic data, which brings transportation engineering into the new era of Big Data. However, despite the advance of technologies, the missing data issue is still inevitable and has posed great challenges for research such as traffic forecasting, real-time incident detection and management, dynamic route guidance, and massive evacuation optimization, because themore » degree of success of these endeavors depends on the timely availability of relatively complete and reasonably accurate traffic data. A thorough literature review suggests most current imputation models, if not all, focus largely on the temporal nature of the traffic data and fail to consider the fact that traffic stream characteristics at a certain location are closely related to those at neighboring locations and utilize these correlations for data imputation. To this end, this paper presents a Kriging based spatiotemporal data imputation approach that is able to fully utilize the spatiotemporal information underlying in traffic data. Imputation performance of the proposed approach was tested using simulated scenarios and achieved stable imputation accuracy. Moreover, the proposed Kriging imputation model is more flexible compared to current models.« less

  8. The 30/20 GHZ net market assessment

    NASA Technical Reports Server (NTRS)

    Rogers, J. C.; Reiner, P.

    1980-01-01

    By creating a number of market scenarios variations dealing with network types, network sizes, and service price levels were analyzed for their impact on market demand. Each market scenario represents a market demand forecast with results for voice, data, and video service traffic expressed in peak load megabits per second.

  9. Operational wind shear detection and warning - The 'CLAWS' experience at Denver and future objectives

    NASA Technical Reports Server (NTRS)

    Mccarthy, John; Wilson, James W.; Hjelmfelt, Mark R.

    1986-01-01

    An operational wind shear detection and warning experiment was conducted at Denver's Stapleton International Airport in summer 1984. Based on meteorological interpretation of scope displays from a Doppler weather radar, warnings were transmitted to the air traffic control tower via voice radio. Analyses of results indicated real skill in daily microburst forecasts and very short-term (less than 5-min) warnings. Wind shift advisories with 15-30 min forecasts, permitted more efficient runway reconfigurations. Potential fuel savings were estimated at $875,000/yr at Stapleton. The philosophy of future development toward an automated, operational system is discussed.

  10. Studies in short haul air transportation in the California corridor: Effects of design runway length; community acceptance; impact of return on investment and fuel cost increases. Volume 2: Appendices

    NASA Technical Reports Server (NTRS)

    Shevell, R. S.; Jones, D. W., Jr.

    1973-01-01

    The development of a forecast model for short haul air transportation systems in the California Corridor is discussed. The factors which determine the level of air traffic demand are identified. A forecast equation for use in airport utilization analysis is developed. A mathematical model is submitted to show the relationship between population, employment, and income for indicating future air transportation utilization. Diagrams and tables of data are included to support the conclusions reached regarding air transportation economic factors.

  11. Long-term forecasting of internet backbone traffic.

    PubMed

    Papagiannaki, Konstantina; Taft, Nina; Zhang, Zhi-Li; Diot, Christophe

    2005-09-01

    We introduce a methodology to predict when and where link additions/upgrades have to take place in an Internet protocol (IP) backbone network. Using simple network management protocol (SNMP) statistics, collected continuously since 1999, we compute aggregate demand between any two adjacent points of presence (PoPs) and look at its evolution at time scales larger than 1 h. We show that IP backbone traffic exhibits visible long term trends, strong periodicities, and variability at multiple time scales. Our methodology relies on the wavelet multiresolution analysis (MRA) and linear time series models. Using wavelet MRA, we smooth the collected measurements until we identify the overall long-term trend. The fluctuations around the obtained trend are further analyzed at multiple time scales. We show that the largest amount of variability in the original signal is due to its fluctuations at the 12-h time scale. We model inter-PoP aggregate demand as a multiple linear regression model, consisting of the two identified components. We show that this model accounts for 98% of the total energy in the original signal, while explaining 90% of its variance. Weekly approximations of those components can be accurately modeled with low-order autoregressive integrated moving average (ARIMA) models. We show that forecasting the long term trend and the fluctuations of the traffic at the 12-h time scale yields accurate estimates for at least 6 months in the future.

  12. The THOR Project-Reducing the Impact of Thunderstorms on Aviation and the General Public Through a Multi-Agency Effect

    NASA Technical Reports Server (NTRS)

    Smith, Stephan B.; Pace, David; Goodman, Steven J.; Burgess, Donald W.; Smarsh, David; Roberts, Rita D.; Wolfson, Marilyn M.; Goodman, H. Michael (Technical Monitor)

    2001-01-01

    Thunderstorms are high impact weather phenomena. They also pose an extremely challenging forecast problem. The National Oceanic and Atmospheric Administration (NOAA), the Federal Aviation Administration (FAA), the National Aeronautic and Space Administration (NASA), and the Air Force Weather Agency (AFWA), have decided to pool technology and scientific expertise into an unprecedented effort to better observe, diagnose, and forecast thunderstorms. This paper describes plans for an operational field test called the THunderstorm Operational Research (THOR) Project beginning in 2002, the primary goals of which are to: 1) Reduce the number of Thunderstorm-related Air Traffic Delays with in the National Airspace System (NAS) and, 2) Improve severe thunderstorm, tornado and airport thunderstorm warning accuracy and lead time. Aviation field operations will be focused on the prime air traffic bottleneck in the NAS, the airspace bounded roughly by Chicago, New York City and Washington D.C., sometimes called the Northeast Corridor. A variety of new automated thunderstorm forecasting applications will be tested here that, when implemented into FAA-NWS operations, will allow for better tactical decision making and NAS management during thunderstorm days. Severe thunderstorm operations will be centered on Northern Alabama. NWS meteorologists from the forecast office in Birmingham will test the utility of experimental lightning, radar, and profiler data from a mesoscale observing network being established by NASA's Marshall Space Flight Center. In addition, new tornado detection and thunderstorm nowcasting algorithms will be examined for their potential for improving warning accuracy. The Alabama THOR site will also serve as a test bed for new gridded, digital thunderstorm and flash flood warning products.

  13. A cross impact methodology for the assessment of US telecommunications system with application to fiber optics development: Executive summary

    NASA Technical Reports Server (NTRS)

    Martino, J. P.; Lenz, R. C., Jr.; Chen, K. L.

    1979-01-01

    A cross impact model of the U.S. telecommunications system was developed. For this model, it was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impacts). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics, throughout the telecommunications system.

  14. A cross impact methodology for the assessment of US telecommunications system with application to fiber optics development, volume 1

    NASA Technical Reports Server (NTRS)

    Martino, J. P.; Lenz, R. C., Jr.; Chen, K. L.; Kahut, P.; Sekely, R.; Weiler, J.

    1979-01-01

    A cross impact model of the U.S. telecommunications system was developed. It was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impact). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics throughout the telecommunications system.

  15. Effect of advanced aircraft noise reduction technology on the 1990 projected noise environment around Patrick Henry Airport. [development of noise exposure forecast contours for projected traffic volume and aircraft types

    NASA Technical Reports Server (NTRS)

    Cawthorn, J. M.; Brown, C. G.

    1974-01-01

    A study has been conducted of the future noise environment of Patric Henry Airport and its neighboring communities projected for the year 1990. An assessment was made of the impact of advanced noise reduction technologies which are currently being considered. These advanced technologies include a two-segment landing approach procedure and aircraft hardware modifications or retrofits which would add sound absorbent material in the nacelles of the engines or which would replace the present two- and three-stage fans with a single-stage fan of larger diameter. Noise Exposure Forecast (NEF) contours were computed for the baseline (nonretrofitted) aircraft for the projected traffic volume and fleet mix for the year 1990. These NEF contours are presented along with contours for a variety of retrofit options. Comparisons of the baseline with the noise reduction options are given in terms of total land area exposed to 30 and 40 NEF levels. Results are also presented of the effects on noise exposure area of the total number of daily operations.

  16. Introduction of the Mobile Platform for the Meteorological Observations in Seoul Metropolitan City of Korea

    NASA Astrophysics Data System (ADS)

    Baek, K. T.; Lee, S.; Kang, M.; Lee, G.

    2016-12-01

    Traffic accidents due to adverse weather such as fog, heavy rainfall, flooding and road surface freezing have been increasing in Korea. To reduce damages caused by the severe weather on the road, a forecast service of combined real-time road-wise weather and the traffic situation is required. Conventional stationary meteorological observations in sparse location system are limited to observe the detailed road environment. For this reason, a mobile meteorological observation platform has been coupled in Weather Information Service Engine (WISE) which is the prototype of urban-scale high resolution weather prediction system in Seoul metropolitan area of Korea in early August 2016. The instruments onboard are designed to measure 15 meteorological parameters; pressure, temperature, relative humidity, precipitation, up/down net radiation, up/down longwave radiation, up/down shortwave radiation, road surface condition, friction coefficient, water depth, wind direction and speed. The observations from mobile platform show a distinctive advantage of data collection in need for road conditions and inputs for the numerical forecast model. In this study, we introduce and examine the feasibility of mobile observations in urban weather prediction and applications.

  17. Analysis and forecast of railway coal transportation volume based on BP neural network combined forecasting model

    NASA Astrophysics Data System (ADS)

    Xu, Yongbin; Xie, Haihong; Wu, Liuyi

    2018-05-01

    The share of coal transportation in the total railway freight volume is about 50%. As is widely acknowledged, coal industry is vulnerable to the economic situation and national policies. Coal transportation volume fluctuates significantly under the new economic normal. Grasp the overall development trend of railway coal transportation market, have important reference and guidance significance to the railway and coal industry decision-making. By analyzing the economic indicators and policy implications, this paper expounds the trend of the coal transportation volume, and further combines the economic indicators with the high correlation with the coal transportation volume with the traditional traffic prediction model to establish a combined forecasting model based on the back propagation neural network. The error of the prediction results is tested, which proves that the method has higher accuracy and has practical application.

  18. Forecast of the general aviation air traffic control environment for the 1980's

    NASA Technical Reports Server (NTRS)

    Hoffman, W. C.; Hollister, W. M.

    1976-01-01

    The critical information required for the design of a reliable, low cost, advanced avionics system which would enhance the safety and utility of general aviation is stipulated. Sufficient data is accumulated upon which industry can base the design of a reasonably priced system having the capability required by general aviation in and beyond the 1980's. The key features of the Air Traffic Control (ATC) system are: a discrete address beacon system, a separation assurance system, area navigation, a microwave landing system, upgraded ATC automation, airport surface traffic control, a wake vortex avoidance system, flight service stations, and aeronautical satellites. The critical parameters that are necessary for component design are identified. The four primary functions of ATC (control, surveillance, navigation, and communication) and their impact on the onboard avionics system design are assessed.

  19. Passenger Flow Forecasting Research for Airport Terminal Based on SARIMA Time Series Model

    NASA Astrophysics Data System (ADS)

    Li, Ziyu; Bi, Jun; Li, Zhiyin

    2017-12-01

    Based on the data of practical operating of Kunming Changshui International Airport during2016, this paper proposes Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict the passenger flow. This article not only considers the non-stationary and autocorrelation of the sequence, but also considers the daily periodicity of the sequence. The prediction results can accurately describe the change trend of airport passenger flow and provide scientific decision support for the optimal allocation of airport resources and optimization of departure process. The result shows that this model is applicable to the short-term prediction of airport terminal departure passenger traffic and the average error ranges from 1% to 3%. The difference between the predicted and the true values of passenger traffic flow is quite small, which indicates that the model has fairly good passenger traffic flow prediction ability.

  20. WSN system design by using an innovative neural network model to perform thermals forecasting in a urban canyon scenario

    NASA Astrophysics Data System (ADS)

    Giuseppina, Nicolosi; Salvatore, Tirrito

    2015-12-01

    Wireless Sensor Networks (WSNs) were studied by researchers in order to manage Heating, Ventilating and Air-Conditioning (HVAC) indoor systems. WSN can be useful specially to regulate indoor confort in a urban canyon scenario, where the thermal parameters vary rapidly, influenced by outdoor climate changing. This paper shows an innovative neural network approach, by using WSN data collected, in order to forecast the indoor temperature to varying the outdoor conditions based on climate parameters and boundary conditions typically of urban canyon. In this work more attention will be done to influence of traffic jam and number of vehicles in queue.

  1. Initial Evaluation of a Conflict Detection Tool in the Terminal Area

    NASA Technical Reports Server (NTRS)

    Verma Savita Arora; Tang, Huabin; Ballinger, Deborah S.; Kozon, Thomas E.; Farrahi, Amir Hossein

    2012-01-01

    Despite the recent economic recession and its adverse impact on air travel, the Federal Aviation Administration (FAA) continues to forecast an increase in air traffic demand that may see traffic double or triple by the year 2025. Increases in air traffic will burden the air traffic management system, and higher levels of safety and efficiency will be required. The air traffic controllers primary task is to ensure separation between aircraft in their airspace and keep the skies safe. As air traffic is forecasted to increase in volume and complexity [1], there is an increased likelihood of conflicts between aircraft, which adds risk and inefficiency to air traffic management and increases controller workload. To attenuate these factors, recent ATM research has shown that air and ground-based automation tools could reduce controller workload, especially if the automation is focused on conflict detection and resolution. Conflict Alert is a short time horizon conflict detection tool deployed in the Terminal Radar Approach Control (TRACON), which has limited utility due to the high number of false alerts generated and its use of dead reckoning to predict loss of separation between aircraft. Terminal Tactical Separation Assurance Flight Environment (T-TSAFE) is a short time horizon conflict detection tool that uses both flight intent and dead reckoning to detect conflicts. Results of a fast time simulation experiment indicated that TTSAFE provided a more effective alert lead-time and generated less false alerts than Conflict Alert [2]. TSAFE was previously tested in a Human-In-The-Loop (HITL) simulation study that focused on the en route phase of flight [3]. The current study tested the T-TSAFE tool in an HITL simulation study, focusing on the terminal environment with current day operations. The study identified procedures, roles, responsibilities, information requirements and usability, with the help of TRACON controllers who participated in the experiment. Metrics such as lead alert time, alert response time, workload, situation awareness and other measures were statistically analyzed. These metrics were examined from an overall perspective and comparisons between conditions (altitude resolutions via keyboard entry vs. ADS-B entry) and controller positions (two final approach sectors and two feeder sectors) were also examined. Results of these analyses and controller feedback provided evidence of T-TSAFE s potential promise as a useful air traffic controller tool. Heuristic analysis also provided information on ways in which the T-TSAFE tool can be improved. Details of analyses results will be presented in the full paper.

  2. Traffic model for the satellite component of UMTS

    NASA Technical Reports Server (NTRS)

    Hu, Y. F.; Sheriff, R. E.

    1995-01-01

    An algorithm for traffic volume estimation for satellite mobile communications systems has been developed. This algorithm makes use of worldwide databases for demographic and economic data. In order to provide for such an estimation, the effects of competing services have been considered so that likely market demand can be forecasted. Different user groups of the predicted market have been identified according to expectations in the quality of services and mobility requirement. The number of users for different user groups are calculated taking into account the gross potential market, the penetration rate of the identified services and the profitability to provide such services via satellite.

  3. Terminal Area Forecasts, Fiscal Years 1980-1991,

    DTIC Science & Technology

    1979-11-01

    REGION REGIONS ASW NONTOWERED STATE: AR LOCID: JbR CITY: JONESBORO AIRPORT: JONESBORO NUNI BASE AIRCRAFT: b8 (---ENPLANEMENTS i000...TABLES Page 1 FAA Air Traffic Control Towers, National Summary by State and Region, June 1979 ...... .. ...................... 12 2 Ranking of Air...39 19 Based Aircraft, National Summary by State and Region, June 1979 .......... .. ........................ 41 ALASKAN SUMMARY BY STATE

  4. Predicting the impacts of new technology aircraft on international air transportation demand

    NASA Technical Reports Server (NTRS)

    Ausrotas, R. A.

    1981-01-01

    International air transportation to and from the United States was analyzed. Long term and short term effects and causes of travel are described. The applicability of econometric methods to forecast passenger travel is discussed. A nomograph is developed which shows the interaction of economic growth, airline yields, and quality of service in producing international traffic.

  5. A comparison of the domestic satellite communications forecast to the year 2000

    NASA Technical Reports Server (NTRS)

    Poley, W. A.; Lekan, J. F.; Salzman, J. A.; Stevenson, S. M.

    1983-01-01

    The methodologies and results of three NASA-sponsored market demand assessment studies are presented and compared. Forecasts of future satellite addressable traffic (both trunking and customer premises services) were developed for the three main service categories of voice, data and video and subcategories thereof for the benchmark years of 1980, 1990 and 2000. The contractor results are presented on a service by service basis in two formats: equivalent 36 MHz transponders and basic transmission units (voice: half-voice circuits, data: megabits per second and video: video channels). It is shown that while considerable differences exist at the service category level, the overall forecasts by the two contractors are quite similar. ITT estimates the total potential satellite market to be 3594 transponders in the year 2000 with data service comprising 54 percent of this total. The WU outlook for the same time period is 2779 transponders with voice services accounting for 66 percent of the total.

  6. Examination of simplified travel demand model. [Internal volume forecasting model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Smith, R.L. Jr.; McFarlane, W.J.

    1978-01-01

    A simplified travel demand model, the Internal Volume Forecasting (IVF) model, proposed by Low in 1972 is evaluated as an alternative to the conventional urban travel demand modeling process. The calibration of the IVF model for a county-level study area in Central Wisconsin results in what appears to be a reasonable model; however, analysis of the structure of the model reveals two primary mis-specifications. Correction of the mis-specifications leads to a simplified gravity model version of the conventional urban travel demand models. Application of the original IVF model to ''forecast'' 1960 traffic volumes based on the model calibrated for 1970more » produces accurate estimates. Shortcut and ad hoc models may appear to provide reasonable results in both the base and horizon years; however, as shown by the IVF mode, such models will not always provide a reliable basis for transportation planning and investment decisions.« less

  7. Ice and AIS: ship speed data and sea ice forecasts in the Baltic Sea

    NASA Astrophysics Data System (ADS)

    Löptien, U.; Axell, L.

    2014-12-01

    The Baltic Sea is a seasonally ice-covered marginal sea located in a densely populated area in northern Europe. Severe sea ice conditions have the potential to hinder the intense ship traffic considerably. Thus, sea ice fore- and nowcasts are regularly provided by the national weather services. Typically, the forecast comprises several ice properties that are distributed as prognostic variables, but their actual usefulness is difficult to measure, and the ship captains must determine their relative importance and relevance for optimal ship speed and safety ad hoc. The present study provides a more objective approach by comparing the ship speeds, obtained by the automatic identification system (AIS), with the respective forecasted ice conditions. We find that, despite an unavoidable random component, this information is useful to constrain and rate fore- and nowcasts. More precisely, 62-67% of ship speed variations can be explained by the forecasted ice properties when fitting a mixed-effect model. This statistical fit is based on a test region in the Bothnian Sea during the severe winter 2011 and employs 15 to 25 min averages of ship speed.

  8. Ship speeds and sea ice forecasts - how are they related?

    NASA Astrophysics Data System (ADS)

    Loeptien, Ulrike; Axell, Lars

    2014-05-01

    The Baltic Sea is a shallow marginal sea, located in northern Europe. A seasonally occurring sea ice cover has the potential to hinder the intense ship traffic substantially. There are thus considerable efforts to fore- and nowcast ice conditions. Here we take a somewhat opposite approach and relate ship speeds, as observed via the Automatic Identification System (AIS) network, back to the prevailing sea ice conditions. We show that these information are useful to constrain fore- and nowcasts. More specifically we find, by fitting a statistical model (mixed effect model) for a test region in the Bothnian Bay, that the forecasted ice properties can explain 60-65% of the ship speed variations (based on 25 minute averages).

  9. Cb-LIKE - Thunderstorm forecasts up to six hours with fuzzy logic

    NASA Astrophysics Data System (ADS)

    Köhler, Martin; Tafferner, Arnold

    2016-04-01

    Thunderstorms with their accompanying effects like heavy rain, hail, or downdrafts cause delays and flight cancellations and therefore high additional cost for airlines and airport operators. A reliable thunderstorm forecast up to several hours could provide more time for decision makers in air traffic for an appropriate reaction on possible storm cells and initiation of adequate counteractions. To provide the required forecasts Cb-LIKE (Cumulonimbus-LIKElihood) has been developed at the DLR (Deutsches Zentrum für Luft- und Raumfahrt) Institute of Atmospheric Physics. The new algorithm is an automated system which designates areas with possible thunderstorm development by using model data of the COSMO-DE weather model, which is driven by the German Meteorological Service (DWD). A newly developed "Best-Member- Selection" method allows the automatic selection of that particular model run of a time-lagged COSMO- DE model ensemble, which matches best the current thunderstorm situation. Thereby the application of the best available data basis for the calculation of the thunderstorm forecasts by Cb-LIKE is ensured. Altogether there are four different modes for the selection of the best member. Four atmospheric parameters (CAPE, vertical wind velocity, radar reflectivity and cloud top temperature) of the model output are used within the algorithm. A newly developed fuzzy logic system enables the subsequent combination of the model parameters and the calculation of a thunderstorm indicator within a value range of 12 up to 88 for each grid point of the model domain for the following six hours in one hour intervals. The higher the indicator value the more the model parameters imply the development of thunderstorms. The quality of the Cb-LIKE thunderstorm forecasts was evaluated by a substantial verification using a neighborhood verification approach and multi-event contingency tables. The verification was performed for the whole summer period of 2012. On the basis of a deterministic object comparison with heavy precipitation cells observed by the radar-based thunderstorm tracking algorithm Rad-TRAM, several verification scores like BIAS, POD, FAR and CSI were calculated to identify possible advantages of the new algorithm. The presentation illustrates in detail the concept of the Cb-LIKE algorithm with regard to the fuzzy logic system and the Best-Member-Selection. Additionally some case studies and the most important results of the verification will be shown. The implementation of the forecasts into the DLR WxFUSION system, an user oriented forecasting system for air traffic, will also be included.

  10. Forecasting Trafficability of Soils. Report Number 4. Information for Predicting Moisture in the Surface Foot of Various Soils

    DTIC Science & Technology

    1957-02-01

    this report is acknowledged: Northeastern Forest Experiment Station, Southeastern Forest and Range Experiment Station, and California Forest Sand Range...Washington ........... ................. .... A7 Tanbark Flat, California ....... ................. .... A8 Madera County, California ...Mississippi, Pennsylvania, California , South Carolina, South Dakota, Nebraska, and Indiana were ob- tained and analyzed. 8. The method developed for prediction

  11. The US aviation system to the year 2000

    NASA Technical Reports Server (NTRS)

    Austrotas, R. A.

    1982-01-01

    The aviation system of the U.S. is described. Growth of the system over the past twenty years is analyzed. Long term and short term causes of air travel are discussed. The interaction of economic growth, airline yields, and quality of service in producing domestic traffic is shown. Forecasts are made for airline and general aviation growth. Potential airline scenarios are presented.

  12. Visualization and Nowcasting for Aviation using online verified ensemble weather radar extrapolation.

    NASA Astrophysics Data System (ADS)

    Kaltenboeck, Rudolf; Kerschbaum, Markus; Hennermann, Karin; Mayer, Stefan

    2013-04-01

    Nowcasting of precipitation events, especially thunderstorm events or winter storms, has high impact on flight safety and efficiency for air traffic management. Future strategic planning by air traffic control will result in circumnavigation of potential hazardous areas, reduction of load around efficiency hot spots by offering alternatives, increase of handling capacity, anticipation of avoidance manoeuvres and increase of awareness before dangerous areas are entered by aircraft. To facilitate this rapid update forecasts of location, intensity, size, movement and development of local storms are necessary. Weather radar data deliver precipitation analysis of high temporal and spatial resolution close to real time by using clever scanning strategies. These data are the basis to generate rapid update forecasts in a time frame up to 2 hours and more for applications in aviation meteorological service provision, such as optimizing safety and economic impact in the context of sub-scale phenomena. On the basis of tracking radar echoes by correlation the movement vectors of successive weather radar images are calculated. For every new successive radar image a set of ensemble precipitation fields is collected by using different parameter sets like pattern match size, different time steps, filter methods and an implementation of history of tracking vectors and plausibility checks. This method considers the uncertainty in rain field displacement and different scales in time and space. By validating manually a set of case studies, the best verification method and skill score is defined and implemented into an online-verification scheme which calculates the optimized forecasts for different time steps and different areas by using different extrapolation ensemble members. To get information about the quality and reliability of the extrapolation process additional information of data quality (e.g. shielding in Alpine areas) is extrapolated and combined with an extrapolation-quality-index. Subsequently the probability and quality information of the forecast ensemble is available and flexible blending to numerical prediction model for each subarea is possible. Simultaneously with automatic processing the ensemble nowcasting product is visualized in a new innovative way which combines the intensity, probability and quality information for different subareas in one forecast image.

  13. Convective Weather Forecast Accuracy Analysis at Center and Sector Levels

    NASA Technical Reports Server (NTRS)

    Wang, Yao; Sridhar, Banavar

    2010-01-01

    This paper presents a detailed convective forecast accuracy analysis at center and sector levels. The study is aimed to provide more meaningful forecast verification measures to aviation community, as well as to obtain useful information leading to the improvements in the weather translation capacity models. In general, the vast majority of forecast verification efforts over past decades have been on the calculation of traditional standard verification measure scores over forecast and observation data analyses onto grids. These verification measures based on the binary classification have been applied in quality assurance of weather forecast products at the national level for many years. Our research focuses on the forecast at the center and sector levels. We calculate the standard forecast verification measure scores for en-route air traffic centers and sectors first, followed by conducting the forecast validation analysis and related verification measures for weather intensities and locations at centers and sectors levels. An approach to improve the prediction of sector weather coverage by multiple sector forecasts is then developed. The weather severe intensity assessment was carried out by using the correlations between forecast and actual weather observation airspace coverage. The weather forecast accuracy on horizontal location was assessed by examining the forecast errors. The improvement in prediction of weather coverage was determined by the correlation between actual sector weather coverage and prediction. observed and forecasted Convective Weather Avoidance Model (CWAM) data collected from June to September in 2007. CWAM zero-minute forecast data with aircraft avoidance probability of 60% and 80% are used as the actual weather observation. All forecast measurements are based on 30-minute, 60- minute, 90-minute, and 120-minute forecasts with the same avoidance probabilities. The forecast accuracy analysis for times under one-hour showed that the errors in intensity and location for center forecast are relatively low. For example, 1-hour forecast intensity and horizontal location errors for ZDC center were about 0.12 and 0.13. However, the correlation between sector 1-hour forecast and actual weather coverage was weak, for sector ZDC32, about 32% of the total variation of observation weather intensity was unexplained by forecast; the sector horizontal location error was about 0.10. The paper also introduces an approach to estimate the sector three-dimensional actual weather coverage by using multiple sector forecasts, which turned out to produce better predictions. Using Multiple Linear Regression (MLR) model for this approach, the correlations between actual observation and the multiple sector forecast model prediction improved by several percents at 95% confidence level in comparison with single sector forecast.

  14. A Kriging based spatiotemporal approach for traffic volume data imputation

    PubMed Central

    Han, Lee D.; Liu, Xiaohan; Pu, Li; Chin, Shih-miao; Hwang, Ho-ling

    2018-01-01

    Along with the rapid development of Intelligent Transportation Systems, traffic data collection technologies have progressed fast. The emergence of innovative data collection technologies such as remote traffic microwave sensor, Bluetooth sensor, GPS-based floating car method, and automated license plate recognition, has significantly increased the variety and volume of traffic data. Despite the development of these technologies, the missing data issue is still a problem that poses great challenge for data based applications such as traffic forecasting, real-time incident detection, dynamic route guidance, and massive evacuation optimization. A thorough literature review suggests most current imputation models either focus on the temporal nature of the traffic data and fail to consider the spatial information of neighboring locations or assume the data follow a certain distribution. These two issues reduce the imputation accuracy and limit the use of the corresponding imputation methods respectively. As a result, this paper presents a Kriging based data imputation approach that is able to fully utilize the spatiotemporal correlation in the traffic data and that does not assume the data follow any distribution. A set of scenarios with different missing rates are used to evaluate the performance of the proposed method. The performance of the proposed method was compared with that of two other widely used methods, historical average and K-nearest neighborhood. Comparison results indicate that the proposed method has the highest imputation accuracy and is more flexible compared to other methods. PMID:29664928

  15. Optimal Time Advance In Terminal Area Arrivals: Throughput vs. Fuel Savings

    NASA Technical Reports Server (NTRS)

    Sadovsky, Alexander V .; Swenson, Harry N.; Haskell, William B.; Rakas, Jasenka

    2011-01-01

    The current operational practice in scheduling air traffic arriving at an airport is to adjust flight schedules by delay, i.e. a postponement of an aircrafts arrival at a scheduled location, to manage safely the FAA-mandated separation constraints between aircraft. To meet the observed and forecast growth in traffic demand, however, the practice of time advance (speeding up an aircraft toward a scheduled location) is envisioned for future operations as a practice additional to delay. Time advance has two potential advantages. The first is the capability to minimize, or at least reduce, the excess separation (the distances between pairs of aircraft immediately in-trail) and thereby to increase the throughput of the arriving traffic. The second is to reduce the total traffic delay when the traffic sample is below saturation density. A cost associated with time advance is the fuel expenditure required by an aircraft to speed up. We present an optimal control model of air traffic arriving in a terminal area and solve it using the Pontryagin Maximum Principle. The admissible controls allow time advance, as well as delay, some of the way. The cost function reflects the trade-off between minimizing two competing objectives: excess separation (negatively correlated with throughput) and fuel burn. A number of instances are solved using three different methods, to demonstrate consistency of solutions.

  16. Interaction of Airspace Partitions and Traffic Flow Management Delay

    NASA Technical Reports Server (NTRS)

    Palopo, Kee; Chatterji, Gano B.; Lee, Hak-Tae

    2010-01-01

    To ensure that air traffic demand does not exceed airport and airspace capacities, traffic management restrictions, such as delaying aircraft on the ground, assigning them different routes and metering them in the airspace, are implemented. To reduce the delays resulting from these restrictions, revising the partitioning of airspace has been proposed to distribute capacity to yield a more efficient airspace configuration. The capacity of an airspace partition, commonly referred to as a sector, is limited by the number of flights that an air traffic controller can safely manage within the sector. Where viable, re-partitioning of the airspace distributes the flights over more efficient sectors and reduces individual sector demand. This increases the overall airspace efficiency, but requires additional resources in some sectors in terms of controllers and equipment, which is undesirable. This study examines the tradeoff of the number of sectors designed for a specified amount of traffic in a clear-weather day and the delays needed for accommodating the traffic demand. Results show that most of the delays are caused by airport arrival and departure capacity constraints. Some delays caused by airspace capacity constraints can be eliminated by re-partitioning the airspace. Analyses show that about 360 high-altitude sectors, which are approximately today s operational number of sectors of 373, are adequate for delays to be driven solely by airport capacity constraints for the current daily air traffic demand. For a marginal increase of 15 seconds of average delay, the number of sectors can be reduced to 283. In addition, simulations of traffic growths of 15% and 20% with forecasted airport capacities in the years 2018 and 2025 show that delays will continue to be governed by airport capacities. In clear-weather days, for small increases in traffic demand, increasing sector capacities will have almost no effect on delays.

  17. Validating induced seismicity forecast models—Induced Seismicity Test Bench

    NASA Astrophysics Data System (ADS)

    Király-Proag, Eszter; Zechar, J. Douglas; Gischig, Valentin; Wiemer, Stefan; Karvounis, Dimitrios; Doetsch, Joseph

    2016-08-01

    Induced earthquakes often accompany fluid injection, and the seismic hazard they pose threatens various underground engineering projects. Models to monitor and control induced seismic hazard with traffic light systems should be probabilistic, forward-looking, and updated as new data arrive. In this study, we propose an Induced Seismicity Test Bench to test and rank such models; this test bench can be used for model development, model selection, and ensemble model building. We apply the test bench to data from the Basel 2006 and Soultz-sous-Forêts 2004 geothermal stimulation projects, and we assess forecasts from two models: Shapiro and Smoothed Seismicity (SaSS) and Hydraulics and Seismics (HySei). These models incorporate a different mix of physics-based elements and stochastic representation of the induced sequences. Our results show that neither model is fully superior to the other. Generally, HySei forecasts the seismicity rate better after shut-in but is only mediocre at forecasting the spatial distribution. On the other hand, SaSS forecasts the spatial distribution better and gives better seismicity rate estimates before shut-in. The shut-in phase is a difficult moment for both models in both reservoirs: the models tend to underpredict the seismicity rate around, and shortly after, shut-in.

  18. Case study of PM pollution in playgrounds in Istanbul

    NASA Astrophysics Data System (ADS)

    Ozdemir, Huseyin; Mertoglu, Bulent; Demir, Goksel; Deniz, Ali; Toros, Hüseyin

    2012-05-01

    In a world where at least 50% of the population is living in urban environments, air pollution and specifically particulate matter (PM) have become one of the most critical issues for human health. Children are more susceptible than adults to air pollution and its adverse effects because they inhale and retain larger amounts of air pollutants per unit of body weight. In this study, PM pollution, particularly PM10 and PM2.5, at selected playgrounds were investigated in Istanbul city. Istanbul is a megacity of over 15 million inhabitants, and on-road traffic is increasing rapidly (over 3 million vehicles on the road). To estimate the effect of traffic emissions on children, the location of the playgrounds were selected according to traffic density. Measurements were carried out at five different playgrounds throughout the city in 2009. Field results show that the values of PM10 and PM2.5 have reached critical limits at the playgrounds close to the main roads, especially at P-1. Thus, we focused on this location and investigated a source other than traffic emissions. One of the episode days has been observed on 5-7 March 2009. Evaluations of meteorological events are very important to determine air pollution sources and their long-range transport. Therefore, the Weather Research and Forecasting model (WRF) was used to simulate and forecast meteorological parameters and the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) applied to investigate long-range transport. According to the WRF model outputs, there was a low-pressure system over Geneva gulf on the 500-hPa level, and its core had been located over Britain on 5 March 2009 00UTC. The system had been sweeping dust from the Sahara Desert and carrying the air particles over Istanbul. Similarly, backward HYSPLIT analysis showed that air particles had moved through Istanbul from Northern Africa.

  19. High-Speed Civil Transport Forecast: Simulated Airlines Scenarios for Mach 1.6, Mach 2.0, and Mach 2.4 Configurations for Year 2015

    NASA Technical Reports Server (NTRS)

    Metwally, Munir

    1996-01-01

    The report describes the development of a database of fuel burn and emissions from projected High Speed Civil Transport (HSCT) fleets that reflect actual airlines' networks, operational requirement, and traffic flow as operated by simulated world wide airlines for Mach 1.6, 2.0, and 2.4 HSCT configurations. For the year 2015, McDonnell Douglas Corporation created two supersonic commercial air traffic networks consisting of origin-destination city pair routes and associated traffic levels. The first scenario represented a manufacturing upper limit producible HSCT fleet availability by year 2015. The fleet projection of the Mach 2.4 configuration for this scenario was 1059 units with a traffic capture of 70 percent. The second scenario focused on the number of units that can minimally be produced by the year 2015. Using realistic production rates, the HSCT fleet projection amounts to 565 units. The traffic capture associated with this fleet was estimated at 40 percent. The airlines network was extracted from the actual networks of 21 major world airlines. All the routes were screened for suitability for HSCT operations. The route selection criteria included great circle distance, difference between flight path distance and great circle distance to avoid overland operations, and potential flight frequency.

  20. Forecast of Future Ohio River Basin, Waterway Traffic Based on Shippers Surveys.

    DTIC Science & Technology

    1979-09-01

    pattern. Analytic Tool: SPSS KAll of the editing, generation of tables, graphing, and other com- putational activities were carried out through the use...00O’s) 1976-1g90 Group 1971 1990 (%) 1976 190 (9) Coal & Coke 0 0 0 1,617 3,231 +100 Petroleum Fuels 705 779 +10 509 509 +0 Aggregates 0 0 0 450 688

  1. The Move to Mobile: Where Is a Campus's Place in the Mobile Space?

    ERIC Educational Resources Information Center

    Lum, Lydia

    2012-01-01

    At the end of 2010, for the first time ever, smartphones outsold PCs. Mobile device adoption rates continue to rise rapidly around the world. A recent forecast by Cisco found that global mobile data traffic more than doubled last year, and by the end of 2012, the number of mobile devices in use will outnumber the world's population. In the United…

  2. Multicomponent ensemble models to forecast induced seismicity

    NASA Astrophysics Data System (ADS)

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

    2018-01-01

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

  3. Towards spatially distributed flood forecasts in flash flood prone areas: application to the supervision of a road network in the South of France

    NASA Astrophysics Data System (ADS)

    Naulin, Jean-Philippe; Payrastre, Olivier; Gaume, Eric; Delrieu, Guy

    2013-04-01

    Accurate flood forecasts are crucial for an efficient flood event management. Until now, hydro-meteorological forecasts have been mainly used for early-warnings in France (Meteorological and flood vigilance maps) or over the world (Flash-flood guidances). These forecasts are generally limited to the main streams covered by the flood forecasting services or to specific watersheds with particular assets like check dams which are in most cases well gauged river sections, leaving aside large parts of the territory. A distributed hydro-meteorological forecasting approach will be presented, able to take advantage of the high spatial and temporal resolution rainfall estimates that are now available to provide information at ungauged sites. The proposed system aiming at detecting road inundation risks had been initially developed and tested in areas of limited size. Its extension to a whole region (the Gard region in the South of France) will be presented, including over 2000 crossing points between rivers and roads and its validation against a large data set of actually reported road inundations observed during recent flash-flood events. These first validation results appear promising. Such a tool would provide the necessary information for flood event management services to identify the areas at risk and to take the appropriate safety and rescue measures: pre-positioning of rescue means, stopping of the traffic on exposed roads, determination of safe accesses or evacuation routes. Moreover, beyond the specific application to the supervision of a road network, this work provides also results concerning the performances of hydro-meteorological forecasts for ungauged headwaters.

  4. Evaluation of induced seismicity forecast models in the Induced Seismicity Test Bench

    NASA Astrophysics Data System (ADS)

    Király, Eszter; Gischig, Valentin; Zechar, Jeremy; Doetsch, Joseph; Karvounis, Dimitrios; Wiemer, Stefan

    2016-04-01

    Induced earthquakes often accompany fluid injection, and the seismic hazard they pose threatens various underground engineering projects. Models to monitor and control induced seismic hazard with traffic light systems should be probabilistic, forward-looking, and updated as new data arrive. Here, we propose an Induced Seismicity Test Bench to test and rank such models. We apply the test bench to data from the Basel 2006 and Soultz-sous-Forêts 2004 geothermal stimulation projects, and we assess forecasts from two models that incorporate a different mix of physical understanding and stochastic representation of the induced sequences: Shapiro in Space (SiS) and Hydraulics and Seismics (HySei). SiS is based on three pillars: the seismicity rate is computed with help of the seismogenic index and a simple exponential decay of the seismicity; the magnitude distribution follows the Gutenberg-Richter relation; and seismicity is distributed in space based on smoothing seismicity during the learning period with 3D Gaussian kernels. The HySei model describes seismicity triggered by pressure diffusion with irreversible permeability enhancement. Our results show that neither model is fully superior to the other. HySei forecasts the seismicity rate well, but is only mediocre at forecasting the spatial distribution. On the other hand, SiS forecasts the spatial distribution well but not the seismicity rate. The shut-in phase is a difficult moment for both models in both reservoirs: the models tend to underpredict the seismicity rate around, and shortly after, shut-in. Ensemble models that combine HySei's rate forecast with SiS's spatial forecast outperform each individual model.

  5. A Method for Forecasting the Commercial Air Traffic Schedule in the Future

    NASA Technical Reports Server (NTRS)

    Long, Dou; Lee, David; Gaier, Eric; Johnson, Jesse; Kostiuk, Peter

    1999-01-01

    This report presents an integrated set of models that forecasts air carriers' future operations when delays due to limited terminal-area capacity are considered. This report models the industry as a whole, avoiding unnecessary details of competition among the carriers. To develop the schedule outputs, we first present a model to forecast the unconstrained flight schedules in the future, based on the assumption of rational behavior of the carriers. Then we develop a method to modify the unconstrained schedules, accounting for effects of congestion due to limited NAS capacities. Our underlying assumption is that carriers will modify their operations to keep mean delays within certain limits. We estimate values for those limits from changes in planned block times reflected in the OAG. Our method for modifying schedules takes many means of reducing the delays into considerations, albeit some of them indirectly. The direct actions include depeaking, operating in off-hours, and reducing hub airports'operations. Indirect actions include using secondary airports, using larger aircraft, and selecting new hub airports, which, we assume, have already been modeled in the FAA's TAF. Users of our suite of models can substitute an alternative forecast for the TAF.

  6. Visibility Modeling and Forecasting for Abu Dhabi using Time Series Analysis Method

    NASA Astrophysics Data System (ADS)

    Eibedingil, I. G.; Abula, B.; Afshari, A.; Temimi, M.

    2015-12-01

    Land-Atmosphere interactions-their strength, directionality and evolution-are one of the main sources of uncertainty in contemporary climate modeling. A particularly crucial role in sustaining and modulating land-atmosphere interaction is the one of aerosols and dusts. Aerosols are tiny particles suspended in the air ranging from a few nanometers to a few hundred micrometers in diameter. Furthermore, the amount of dust and fog in the atmosphere is an important measure of visibility, which is another dimension of land-atmosphere interactions. Visibility affects all form of traffic, aviation, land and sailing. Being able to predict the change of visibility in the air in advance enables relevant authorities to take necessary actions before the disaster falls. Time Series Analysis (TAS) method is an emerging technique for modeling and forecasting the behavior of land-atmosphere interactions, including visibility. This research assess the dynamics and evolution of visibility around Abu Dhabi International Airport (+24.4320 latitude, +54.6510 longitude, and 27m elevation) using mean daily visibility and mean daily wind speed. TAS has been first used to model and forecast the visibility, and then the Transfer Function Model has been applied, considering the wind speed as an exogenous variable. By considering the Akaike Information Criterion (AIC) and Mean Absolute Percentage Error (MAPE) as a statistical criteria, two forecasting models namely univarite time series model and transfer function model, were developed to forecast the visibility around Abu Dhabi International Airport for three weeks. Transfer function model improved the MAPE of the forecast significantly.

  7. Algorithms for constructing optimal paths and statistical analysis of passenger traffic

    NASA Astrophysics Data System (ADS)

    Trofimov, S. P.; Druzhinina, N. G.; Trofimova, O. G.

    2018-01-01

    Several existing information systems of urban passenger transport (UPT) are considered. Author’s UPT network model is presented. To a passenger a new service is offered that is the best path from one stop to another stop at a specified time. The algorithm and software implementation for finding the optimal path are presented. The algorithm uses the current UPT schedule. The article also describes the algorithm of statistical analysis of trip payments by the electronic E-cards. The algorithm allows obtaining the density of passenger traffic during the day. This density is independent of the network topology and UPT schedules. The resulting density of the traffic flow can solve a number of practical problems. In particular, the forecast for the overflow of passenger transport in the «rush» hours, the quantitative comparison of different topologies transport networks, constructing of the best UPT timetable. The efficiency of the proposed integrated approach is demonstrated by the example of the model town with arbitrary dimensions.

  8. Building statistical associations to forecast ethylbenzene levels in European urban-traffic environments.

    PubMed

    Vlachokostas, Ch; Michailidou, A V; Spyridi, D; Moussiopoulos, N

    2013-06-01

    Emission from road traffic has become the most important source of local air pollution in numerous European cities. Epidemiological research community has established consistent associations between traffic-related substances and various health outcomes. Nevertheless, the vast majority of urban areas are characterised by infrastructure's absence to routinely monitor chemical health stressors, such as ethylbenzene. This paper aims at developing and presenting a tractable approach to reliably - and inexpensively - predict ethylbenzene trends in EU urban environments. The establishment of empirical relationships between rarely monitored pollutants such as ethylbenzene and more frequently or usually monitored, such as benzene and CO respectively, may cover the infrastructure's absence and support decision-making. Multiple regression analysis is adopted and the resulting statistical associations are applied to EU cities with available data for validation purposes. The results demonstrate that this approach is capable of capturing ethylbenzene concentration trends and should be considered as complementary to air quality monitoring. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. Integrated risk/cost planning models for the US Air Traffic system

    NASA Technical Reports Server (NTRS)

    Mulvey, J. M.; Zenios, S. A.

    1985-01-01

    A prototype network planning model for the U.S. Air Traffic control system is described. The model encompasses the dual objectives of managing collision risks and transportation costs where traffic flows can be related to these objectives. The underlying structure is a network graph with nonseparable convex costs; the model is solved efficiently by capitalizing on its intrinsic characteristics. Two specialized algorithms for solving the resulting problems are described: (1) truncated Newton, and (2) simplicial decomposition. The feasibility of the approach is demonstrated using data collected from a control center in the Midwest. Computational results with different computer systems are presented, including a vector supercomputer (CRAY-XMP). The risk/cost model has two primary uses: (1) as a strategic planning tool using aggregate flight information, and (2) as an integrated operational system for forecasting congestion and monitoring (controlling) flow throughout the U.S. In the latter case, access to a supercomputer is required due to the model's enormous size.

  10. Civil Tiltrotor Feasibility Study for the New York and Washington Terminal Areas

    NASA Technical Reports Server (NTRS)

    Stouffer, Virginia; Johnson, Jesse; Gribko, Joana; Yackovetsky, Robert (Technical Monitor)

    2001-01-01

    NASA tasked LMI to assess the potential contributions of a yet-undeveloped Civil Tiltrotor aircraft (CTR) in improving capacity in the National Airspace System in all weather conditions. The CTRs studied have assumed operating parameters beyond current CTR capabilities. LMI analyzed CTRs three ways: in fast-time terminal area modeling simulations of New York and Washington to determine delay and throughput impacts; in the Integrated Noise Model, to determine local environmental impact; and with an economic model, to determine the price viability of a CTR. The fast-time models encompassed a 250 nmi range and included traffic interactions from local airports. Both the fast-time simulation and the noise model assessed impacts from traffic levels projected for 1999, 2007, and 2017. Results: CTRs can reduce terminal area delays due to concrete congestion in all time frames. The maximum effect, the ratio of CTRs to jets and turboprop aircraft at a subject airport should be optimized. The economic model considered US traffic only and forecasted CTR sales beginning in 2010.

  11. The impact of traffic emissions on air quality in the Berlin-Brandenburg region - a case study on cycling scenarios

    NASA Astrophysics Data System (ADS)

    Kuik, F.; Lauer, A.; von Schneidemesser, E.; Butler, T. M.

    2016-12-01

    Many European cities continue to struggle with exceedances of NO2 limit values at measurement sites near roads, of which a large contribution is attributed to emissions from traffic. In this study, we explore how urban air quality can be improved with different traffic measures using the example of the Berlin-Brandenburg region. In order to simulate urban background air quality we use the Weather Research and Forecasting model with chemistry (WRF-Chem) at a horizontal resolution of 1km. We use emission input data at a horizontal resolution of 1km obtained by downscaling TNO-MACC III emissions based on local proxy data including population and traffic densities. In addition we use a statistical approach combining the simulated urban background concentrations with information on traffic densities to estimate NO2 at street level. This helps assessing whether the emission scenarios studied here can lead to significant reductions in NO2 concentrations at street level. The emission scenarios in this study represent a range of scenarios in which car traffic is replaced with bicycle traffic. Part of this study was an initial discussion phase with stakeholders, including policy makers and NGOs. The discussions have shown that the different stakeholders are interested in a scientific assessment of the impact of replacing car traffic with bicycle traffic in the Berlin-Brandenburg urban area. Local policy makers responsible for city planning and implementing traffic measures can make best use of scientific modeling results if input data and scenarios are as realistic as possible. For these reasons, the scenarios cover very idealized optimistic ("all passenger cars are replaced by bicycles") and pessimistic ("all cyclists are replaced by cars") scenarios to explore the sensitivity of simulated urban background air quality to these changes, as well as additional scenarios based on city-specific data to analyze more realistic situations. Of particular interest is how these impact street level NO2 concentrations.

  12. Socioeconomic Impact Assessment: Communications Industry. Phase III. Technology Forecast.

    DTIC Science & Technology

    1979-02-02

    8217. Some add-on devices , such as automatic answering systems, have already penetrated the home market substantially. In the future, however, ( major changes ...equipment. This class includes garage door openers, wireless micro- phones , cordless telephones, and radio and TV receivers. These -( devices can...ACUMENICS 1-9 1.2.2 Switching Devices The first automatic switching devices which began to replace operator-switched telephone traffic in the early

  13. Spatially distributed flood forecasting in flash flood prone areas: Application to road network supervision in Southern France

    NASA Astrophysics Data System (ADS)

    Naulin, J.-P.; Payrastre, O.; Gaume, E.

    2013-04-01

    SummaryAccurate flood forecasts are critical to an efficient flood event management strategy. Until now, hydro-meteorological forecasts have mainly been used to establish early-warnings in France (meteorological and flood vigilance maps) or over the world (flash-flood guidances). These forecasts are typically limited either to the main streams covered by the flood forecasting services or to watersheds with specific assets like check dams, which in most cases are well gauged river sections, thus leaving aside large parts of the territory. This paper presents a distributed hydro-meteorological forecasting approach, which makes use of the high spatial and temporal resolution rainfall estimates that are now available, to provide information at ungauged sites. The proposed system intended to detect road inundation risks had initially been developed and tested in areas of limited size. This paper presents the extension of such a system to an entire region (i.e. the Gard region in Southern France), including over 2000 crossing points between rivers and roads and its validation with respect to a large data set of actual reported road inundations observed during recent flash flood events. These initial validation results appear to be most promising. The eventual proposed tool would provide the necessary information for flood event management services to identify the areas at risk and adopt appropriate safety and rescue measures: i.e. pre-positioning of rescue equipment, interruption of the traffic on the exposed roads and determination of safe access or evacuation routes. Moreover, beyond the specific application to the supervision of a road network, the research undertaken herein also provides results for the performance of hydro-meteorological forecasts on ungauged headwaters.

  14. Improvement forecasting of volcanic activity by applying a Kalman filter to the SSEM signal. The case of the El Hierro Island eruption (October 2011)

    NASA Astrophysics Data System (ADS)

    Garcia, A.; Berrocoso, M.; Marrero, J. M.; Ortiz, R.

    2012-04-01

    The FFM (Failure Forecast Method) is developed from the eruption of St. Helens, being repeatedly applied to forecast eruptions and recently to the prediction of seismic activity in active volcanic areas. The underwater eruption of El Hierro Island has been monitored from three months before starting (October 10, 2011). This allowed a large catalogue of seismic events (over 11000) and continuous recording seismic signals that cover the entire period. Since the beginning of the seismic-volcanic crisis (July 2011), the FFM was applied to the SSEM signal of seismic records. Mainly because El Hierro is a very small island, the SSEM has a high noise (traffic and oceanic noise). To improve the signal / noise ratio has been used a Kalman filter. The Kalman filter coefficients are adjusted using an inversion process based on forecasting errors occurred in the twenty days preceding. The application of this filter has been a significant improvement in the reliability of forecasts. The analysis of the results shows, before the start of the eruption, that 90% of the forecasts are obtained with errors less than 10 minutes with more than 24 hours in advance. It is noteworthy that the method predicts the events of greater magnitude and especially the beginning of each swarm of seismic events. At the time the eruption starts reducing the efficiency of the forecast 50% with a dispersion of more than one hour. This fact is probably due to decreased detectability by saturation of some of the seismic stations and decreased the average magnitude. However, the events of magnitude greater than 4 were predicted with an error less than 20 minutes.

  15. Predicting Road Conditions with Internet Search

    PubMed Central

    2016-01-01

    Traffic congestion is an important problem both on an individual and on a societal level and much research has been done to explain and prevent their emergence. There are currently many systems which provide a reasonably good picture of actual road traffic by employing either fixed measurement points on highways or so called “floating car data” i.e. by using velocity and location data from roaming, networked, GPS enabled members of traffic. Some of these systems also offer forecasting of road conditions based on such historical data. To my knowledge there is as yet no system which offers advance notice on road conditions based on a signal which is guaranteed to occur in advance of these conditions and this is the novelty of this paper. Google Search intensity for the German word stau (i.e. traffic jam) peaks 2 hours ahead of the number of traffic jam reports as reported by the ADAC, a well known German automobile club and the largest of its kind in Europe. This is true both in the morning (7 am to 9 am) and in the evening (4 pm to 6 pm). The main result of this paper is then that after controlling for time-of-day and day-of-week effects we can still explain a significant additional portion of the variation of the number of traffic jam reports with Google Trends and we can thus explain well over 80% of the variation of road conditions using Google search activity. A one percent increase in Google stau searches implies a .4 percent increase of traffic jams. Our paper is a proof of concept that aggregate, timely delivered behavioural data can help fine tune modern societies and prompts for more research with better, more disaggregated data in order to also achieve practical solutions. PMID:27571518

  16. Complexity analysis of the Next Gen Air Traffic Management System: trajectory based operations.

    PubMed

    Lyons, Rhonda

    2012-01-01

    According to Federal Aviation Administration traffic predictions currently our Air Traffic Management (ATM) system is operating at 150 percent capacity; forecasting that within the next two decades, the traffic with increase to a staggering 250 percent [17]. This will require a major redesign of our system. Today's ATM system is complex. It is designed to safely, economically, and efficiently provide air traffic services through the cost-effective provision of facilities and seamless services in collaboration with multiple agents however, contrary the vision, the system is loosely integrated and is suffering tremendously from antiquated equipment and saturated airways. The new Next Generation (Next Gen) ATM system is designed to transform the current system into an agile, robust and responsive set of operations that are designed to safely manage the growing needs of the projected increasingly complex, diverse set of air transportation system users and massive projected worldwide traffic rates. This new revolutionary technology-centric system is dynamically complex and is much more sophisticated than it's soon to be predecessor. ATM system failures could yield large scale catastrophic consequences as it is a safety critical system. This work will attempt to describe complexity and the complex nature of the NextGen ATM system and Trajectory Based Operational. Complex human factors interactions within Next Gen will be analyzed using a proposed dual experimental approach designed to identify hazards, gaps and elicit emergent hazards that would not be visible if conducted in isolation. Suggestions will be made along with a proposal for future human factors research in the TBO safety critical Next Gen environment.

  17. On the forecasting the unfavorable periods in the technosphere by the space weather factors

    NASA Astrophysics Data System (ADS)

    Lyakhov, N. N.

    2002-12-01

    There is the considerable progress in development of geomagnetic disturbances forecast technique, in the necessary time, by solar activity phenomena last years. The possible relationship between violations of the traffic safety terms (VTS) in East Siberian Railway during 1986-1999 and the space weather factors was investigated. The overall number of cases under consideration is equal to 11575. By methods of correlation and spectral analysis it was shown, that statistics of VTS has not a random and it's character is probably caused by space weather factors. The principal difference between rhythmic of VTS by purely technical reasons (MECH) (failures in mechanical systems) and, that of VTS caused by wrong operations of a personnel (MAN), is noted. Increase of sudden storm commencements number results in increase of probability of mistakable actions of an operator. Probability of violations in mechanical systems increases with increase of number of quiet geomagnetic conditions. This, in its turn, dictate different approach to the ordered rows of MECH and MAN data when forecasting the unfavourable periods as the priods of increased risk in working out a wrong decision by technological process participants. The advances in forecasting of geomagnetic environment technique made possible to start construction of systems of the operative informing about unfavourable factors of space weather for the interested organizations.

  18. Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Sensor Development

    NASA Technical Reports Server (NTRS)

    Daniels, Taumi S.; Tsoucalas, George; Anderson, Mark; Mulally, Daniel; Moninger, William; Mamrosh, Richard

    2004-01-01

    One of the recommendations of the National Aviation Weather Program Council was to expand and institutionalize the generation, dissemination, and use of automated pilot reports (PIREPS) to the full spectrum of the aviation community, including general aviation. In response to this and other similar recommendations, NASA initiated cooperative research into the development of an electronic pilot reporting capability (Daniels 2002). The ultimate goal is to develop a small low-cost sensor, collect useful meteorological observations below 25,000 ft., downlink the data in near real time, and use the data to improve weather forecasts. Primary users of the data include pilots, who are one targeted audience for the improved weather information that will result from the TAMDAR data. The weather data will be disseminated and used to improve aviation safety by providing pilots with enhanced weather situational awareness. In addition, the data will be used to improve the accuracy and timeliness of weather forecasts. Other users include air traffic controllers, flight service stations, and airline weather centers. Additionally, the meteorological data collected by TAMDAR is expected to have a significant positive impact on forecast accuracy for ground based applications.

  19. Ice and AIS: ship speed data and sea ice forecasts in the Baltic Sea

    NASA Astrophysics Data System (ADS)

    Löptien, U.; Axell, L.

    2014-07-01

    The Baltic Sea is a seasonally ice covered marginal sea located in a densely populated area in northern Europe. Severe sea ice conditions have the potential to hinder the intense ship traffic considerably. Thus, sea ice fore- and nowcasts are regularly provided by the national weather services. Typically, several ice properties are allocated, but their actual usefulness is difficult to measure and the ship captains must determine their relative importance and relevance for optimal ship speed and safety ad hoc. The present study provides a more objective approach by comparing the ship speeds, obtained by the Automatic Identification System (AIS), with the respective forecasted ice conditions. We find that, despite an unavoidable random component, this information is useful to constrain and rate fore- and nowcasts. More precisely, 62-67% of ship speed variations can be explained by the forecasted ice properties when fitting a mixed effect model. This statistical fit is based on a test region in the Bothnian Bay during the severe winter 2011 and employes 15 to 25 min averages of ship speed.

  20. Sources and dynamics of turbulence in the upper troposphere and lower stratosphere: A review

    NASA Astrophysics Data System (ADS)

    Sharman, R. D.; Trier, S. B.; Lane, T. P.; Doyle, J. D.

    2012-06-01

    Turbulence is a well-known hazard to aviation that is responsible for numerous injuries each year, with occasional fatalities, and is the underlying cause of many people's fear of air travel. Not only are turbulence encounters a safety issue, they also result in millions of dollars of operational costs to airlines, leading to increased costs passed on to the consumer. For these reasons, pilots, dispatchers, and air traffic controllers attempt to avoid turbulence wherever possible. Accurate forecasting of aviation-scale turbulence has been hampered in part by a lack of understanding of the underlying dynamical processes. However, more precise observations of turbulence encounters together with recent research into turbulence generation processes is helping to elucidate the detailed dynamical processes involved and is laying the foundation for improved turbulence forecasting and avoidance. In this paper we briefly review some of the more important recent observational, theoretical, and modeling results related to turbulence at cruise altitudes for commercial aircraft (i.e., the upper troposphere and lower stratosphere), and their implications for aviation turbulence forecasting.

  1. Using total precipitable water anomaly as a forecast aid for heavy precipitation events

    NASA Astrophysics Data System (ADS)

    VandenBoogart, Lance M.

    Heavy precipitation events are of interest to weather forecasters, local government officials, and the Department of Defense. These events can cause flooding which endangers lives and property. Military concerns include decreased trafficability for military vehicles, which hinders both war- and peace-time missions. Even in data-rich areas such as the United States, it is difficult to determine when and where a heavy precipitation event will occur. The challenges are compounded in data-denied regions. The hypothesis that total precipitable water anomaly (TPWA) will be positive and increasing preceding heavy precipitation events is tested in order to establish an understanding of TPWA evolution. Results are then used to create a precipitation forecast aid. The operational, 16 km-gridded, 6-hourly TPWA product developed at the Cooperative Institute for Research in the Atmosphere (CIRA) compares a blended TPW product with a TPW climatology to give a percent of normal TPWA value. TPWA evolution is examined for 84 heavy precipitation events which occurred between August 2010 and November 2011. An algorithm which uses various TPWA thresholds derived from the 84 events is then developed and tested using dichotomous contingency table verification statistics to determine the extent to which satellite-based TPWA might be used to aid in forecasting precipitation over mesoscale domains. The hypothesis of positive and increasing TPWA preceding heavy precipitation events is supported by the analysis. Event-average TPWA rises for 36 hours and peaks at 154% of normal at the event time. The average precipitation event detected by the forecast algorithm is not of sufficient magnitude to be termed a "heavy" precipitation event; however, the algorithm adds skill to a climatological precipitation forecast. Probability of detection is low and false alarm ratios are large, thus qualifying the algorithm's current use as an aid rather than a deterministic forecast tool. The algorithm's ability to be easily modified and quickly run gives it potential for future use in precipitation forecasting.

  2. Long-path measurements of pollutants and micrometeorology over Highway 401 in Toronto

    NASA Astrophysics Data System (ADS)

    You, Yuan; Staebler, Ralf M.; Moussa, Samar G.; Su, Yushan; Munoz, Tony; Stroud, Craig; Zhang, Junhua; Moran, Michael D.

    2017-11-01

    Traffic emissions contribute significantly to urban air pollution. Measurements were conducted over Highway 401 in Toronto, Canada, with a long-path Fourier transform infrared (FTIR) spectrometer combined with a suite of micrometeorological instruments to identify and quantify a range of air pollutants. Results were compared with simultaneous in situ observations at a roadside monitoring station, and with output from a special version of the operational Canadian air quality forecast model (GEM-MACH). Elevated mixing ratios of ammonia (0-23 ppb) were observed, of which 76 % were associated with traffic emissions. Hydrogen cyanide was identified at mixing ratios between 0 and 4 ppb. Using a simple dispersion model, an integrated emission factor of on average 2.6 g km-1 carbon monoxide was calculated for this defined section of Highway 401, which agreed well with estimates based on vehicular emission factors and observed traffic volumes. Based on the same dispersion calculations, vehicular average emission factors of 0.04, 0.36, and 0.15 g km-1 were calculated for ammonia, nitrogen oxide, and methanol, respectively.

  3. Using random forests to diagnose aviation turbulence.

    PubMed

    Williams, John K

    Atmospheric turbulence poses a significant hazard to aviation, with severe encounters costing airlines millions of dollars per year in compensation, aircraft damage, and delays due to required post-event inspections and repairs. Moreover, attempts to avoid turbulent airspace cause flight delays and en route deviations that increase air traffic controller workload, disrupt schedules of air crews and passengers and use extra fuel. For these reasons, the Federal Aviation Administration and the National Aeronautics and Space Administration have funded the development of automated turbulence detection, diagnosis and forecasting products. This paper describes a methodology for fusing data from diverse sources and producing a real-time diagnosis of turbulence associated with thunderstorms, a significant cause of weather delays and turbulence encounters that is not well-addressed by current turbulence forecasts. The data fusion algorithm is trained using a retrospective dataset that includes objective turbulence reports from commercial aircraft and collocated predictor data. It is evaluated on an independent test set using several performance metrics including receiver operating characteristic curves, which are used for FAA turbulence product evaluations prior to their deployment. A prototype implementation fuses data from Doppler radar, geostationary satellites, a lightning detection network and a numerical weather prediction model to produce deterministic and probabilistic turbulence assessments suitable for use by air traffic managers, dispatchers and pilots. The algorithm is scheduled to be operationally implemented at the National Weather Service's Aviation Weather Center in 2014.

  4. Cloud-based large-scale air traffic flow optimization

    NASA Astrophysics Data System (ADS)

    Cao, Yi

    The ever-increasing traffic demand makes the efficient use of airspace an imperative mission, and this paper presents an effort in response to this call. Firstly, a new aggregate model, called Link Transmission Model (LTM), is proposed, which models the nationwide traffic as a network of flight routes identified by origin-destination pairs. The traversal time of a flight route is assumed to be the mode of distribution of historical flight records, and the mode is estimated by using Kernel Density Estimation. As this simplification abstracts away physical trajectory details, the complexity of modeling is drastically decreased, resulting in efficient traffic forecasting. The predicative capability of LTM is validated against recorded traffic data. Secondly, a nationwide traffic flow optimization problem with airport and en route capacity constraints is formulated based on LTM. The optimization problem aims at alleviating traffic congestions with minimal global delays. This problem is intractable due to millions of variables. A dual decomposition method is applied to decompose the large-scale problem such that the subproblems are solvable. However, the whole problem is still computational expensive to solve since each subproblem is an smaller integer programming problem that pursues integer solutions. Solving an integer programing problem is known to be far more time-consuming than solving its linear relaxation. In addition, sequential execution on a standalone computer leads to linear runtime increase when the problem size increases. To address the computational efficiency problem, a parallel computing framework is designed which accommodates concurrent executions via multithreading programming. The multithreaded version is compared with its monolithic version to show decreased runtime. Finally, an open-source cloud computing framework, Hadoop MapReduce, is employed for better scalability and reliability. This framework is an "off-the-shelf" parallel computing model that can be used for both offline historical traffic data analysis and online traffic flow optimization. It provides an efficient and robust platform for easy deployment and implementation. A small cloud consisting of five workstations was configured and used to demonstrate the advantages of cloud computing in dealing with large-scale parallelizable traffic problems.

  5. Research on strategy and optimization method of PRT empty vehicles resource allocation based on traffic demand forecast

    NASA Astrophysics Data System (ADS)

    Xiang, Yu; Tao, Cheng

    2018-05-01

    During the operation of the personal rapid transit system(PRT), the empty vehicle resources is distributed unevenly because of different passenger demand. In order to maintain the balance between supply and demand, and to meet the passenger needs of the ride, PRT empty vehicle resource allocation model is constructed based on the future demand forecasted by historical demand in this paper. The improved genetic algorithm is implied in distribution of the empty vehicle which can reduce the customers waiting time and improve the operation efficiency of the PRT system so that all passengers can take the PRT vehicles in the shortest time. The experimental result shows that the improved genetic algorithm can allocate the empty vehicle from the system level optimally, and realize the distribution of the empty vehicle resources reasonably in the system.

  6. Cockpit automation - In need of a philosophy

    NASA Technical Reports Server (NTRS)

    Wiener, E. L.

    1985-01-01

    Concern has been expressed over the rapid development and deployment of automatic devices in transport aircraft, due mainly to the human interface and particularly the role of automation in inducing human error. The paper discusses the need for coherent philosophies of automation, and proposes several approaches: (1) flight management by exception, which states that as long as a crew stays within the bounds of regulations, air traffic control and flight safety, it may fly as it sees fit; (2) exceptions by forecasting, where the use of forecasting models would predict boundary penetration, rather than waiting for it to happen; (3) goal-sharing, where a computer is informed of overall goals, and subsequently has the capability of checking inputs and aircraft position for consistency with the overall goal or intentions; and (4) artificial intelligence and expert systems, where intelligent machines could mimic human reason.

  7. Optimal Control of Hybrid Systems in Air Traffic Applications

    NASA Astrophysics Data System (ADS)

    Kamgarpour, Maryam

    Growing concerns over the scalability of air traffic operations, air transportation fuel emissions and prices, as well as the advent of communication and sensing technologies motivate improvements to the air traffic management system. To address such improvements, in this thesis a hybrid dynamical model as an abstraction of the air traffic system is considered. Wind and hazardous weather impacts are included using a stochastic model. This thesis focuses on the design of algorithms for verification and control of hybrid and stochastic dynamical systems and the application of these algorithms to air traffic management problems. In the deterministic setting, a numerically efficient algorithm for optimal control of hybrid systems is proposed based on extensions of classical optimal control techniques. This algorithm is applied to optimize the trajectory of an Airbus 320 aircraft in the presence of wind and storms. In the stochastic setting, the verification problem of reaching a target set while avoiding obstacles (reach-avoid) is formulated as a two-player game to account for external agents' influence on system dynamics. The solution approach is applied to air traffic conflict prediction in the presence of stochastic wind. Due to the uncertainty in forecasts of the hazardous weather, and hence the unsafe regions of airspace for aircraft flight, the reach-avoid framework is extended to account for stochastic target and safe sets. This methodology is used to maximize the probability of the safety of aircraft paths through hazardous weather. Finally, the problem of modeling and optimization of arrival air traffic and runway configuration in dense airspace subject to stochastic weather data is addressed. This problem is formulated as a hybrid optimal control problem and is solved with a hierarchical approach that decouples safety and performance. As illustrated with this problem, the large scale of air traffic operations motivates future work on the efficient implementation of the proposed algorithms.

  8. Modeling when and where a secondary accident occurs.

    PubMed

    Wang, Junhua; Liu, Boya; Fu, Ting; Liu, Shuo; Stipancic, Joshua

    2018-01-31

    The occurrence of secondary accidents leads to traffic congestion and road safety issues. Secondary accident prevention has become a major consideration in traffic incident management. This paper investigates the location and time of a potential secondary accident after the occurrence of an initial traffic accident. With accident data and traffic loop data collected over three years from California interstate freeways, a shock wave-based method was introduced to identify secondary accidents. A linear regression model and two machine learning algorithms, including a back-propagation neural network (BPNN) and a least squares support vector machine (LSSVM), were implemented to explore the distance and time gap between the initial and secondary accidents using inputs of crash severity, violation category, weather condition, tow away, road surface condition, lighting, parties involved, traffic volume, duration, and shock wave speed generated by the primary accident. From the results, the linear regression model was inadequate in describing the effect of most variables and its goodness-of-fit and accuracy in prediction was relatively poor. In the training programs, the BPNN and LSSVM demonstrated adequate goodness-of-fit, though the BPNN was superior with a higher CORR and lower MSE. The BPNN model also outperformed the LSSVM in time prediction, while both failed to provide adequate distance prediction. Therefore, the BPNN model could be used to forecast the time gap between initial and secondary accidents, which could be used by decision makers and incident management agencies to prevent or reduce secondary collisions. Copyright © 2018 Elsevier Ltd. All rights reserved.

  9. Public Response to Hurricane Rita Forecasts Along the Texas Coast: An Undergraduate Research Study Linking Science and Society

    NASA Astrophysics Data System (ADS)

    Morss, R. E.; Zhang, F.

    2006-12-01

    One mechanism for creating more usable science is familiarizing scientists with societal use of and needs for scientific information. We will describe an effort to so in the university educational system, through a semester-long class for meteorology students that involved a research project on public perception and use of hurricane forecasts. Hurricane Rita made landfall near the Texas-Louisiana border in September 2005, causing major damage and disruption. As Rita approached the Gulf Coast, significant uncertainties in the track and intensity forecasts, combined with the aftermath of Hurricane Katrina, led to major evacuations along the Texas coast and significant traffic jams in the broader Houston area. In the spring semester of 2006, seven undergraduate and three graduate meteorology students at Texas A&M University participated in a student research project to investigate the societal impacts of Hurricane Rita and its forecasts. The research team, including the students, developed a structured interview questionnaire to explore coastal residents' hurricane preparation and evacuation decisions and their use and perception of Hurricane Rita forecasts. The students then conducted 120 in-person interviews in the Texas Gulf Coast cities of Galveston, Port Arthur, and Houston. The study was designed to both answer key research questions and provide students with first- hand knowledge about how the public perceives hurricane risk and uses weather forecasts. We will report findings from the survey, as well as the educational benefits described by the students. We hope that the project can serve as a model for classroom-based student research projects at other universities, to give more science students opportunities to learn first-hand about people's perceptions and use of scientific information.

  10. The Insertion of Human Factors Concerns into NextGen Programmatic Decisions

    NASA Technical Reports Server (NTRS)

    Beard, Bettina L.; Holbrook, Jon Brian; Seely, Rachel

    2013-01-01

    Since the costs of proposed improvements in air traffic management exceed available funding, FAA decision makers must select and prioritize what actually gets implemented. We discuss a set of methods to help forecast operational and human performance issues and benefits before new automation is introduced. This strategy could minimize the impact of politics, assist decision makers in selecting and prioritizing potential improvements, make the process more transparent and strengthen the link between the engineering and human factors domains.

  11. Space Shuttle capabilities, constraints, and cost

    NASA Technical Reports Server (NTRS)

    Lee, C. M.

    1980-01-01

    The capabilities, constraints, and costs of the Space Transportation System (STS), which combines reusable and expendable components, are reviewed, and an overview of the current planning activities for operating the STS in an efficient and cost-effective manner is presented. Traffic forecasts, performance constraints and enhancements, and potential new applications are discussed. Attention is given to operating costs, pricing policies, and the steps involved in 'getting on board', which includes all the interfaces between NASA and the users necessary to come to launch service agreements.

  12. Advance Technology Satellites in the Commercial Environment. Volume 2: Final Report

    NASA Technical Reports Server (NTRS)

    1984-01-01

    A forecast of transponder requirements was obtained. Certain assumptions about system configurations are implicit in this process. The factors included are interpolation of baseline year values to produce yearly figures, estimation of satellite capture, effects of peak-hours and the time-zone staggering of peak hours, circuit requirements for acceptable grade of service capacity of satellite transponders, including various compression methods where applicable, and requirements for spare transponders in orbit. The graphical distribution of traffic requirements was estimated.

  13. An Airborne Conflict Resolution Approach Using a Genetic Algorithm

    NASA Technical Reports Server (NTRS)

    Mondoloni, Stephane; Conway, Sheila

    2001-01-01

    An airborne conflict resolution approach is presented that is capable of providing flight plans forecast to be conflict-free with both area and traffic hazards. This approach is capable of meeting constraints on the flight plan such as required times of arrival (RTA) at a fix. The conflict resolution algorithm is based upon a genetic algorithm, and can thus seek conflict-free flight plans meeting broader flight planning objectives such as minimum time, fuel or total cost. The method has been applied to conflicts occurring 6 to 25 minutes in the future in climb, cruise and descent phases of flight. The conflict resolution approach separates the detection, trajectory generation and flight rules function from the resolution algorithm. The method is capable of supporting pilot-constructed resolutions, cooperative and non-cooperative maneuvers, and also providing conflict resolution on trajectories forecast by an onboard FMC.

  14. Prediction of Weather Impacted Airport Capacity using Ensemble Learning

    NASA Technical Reports Server (NTRS)

    Wang, Yao Xun

    2011-01-01

    Ensemble learning with the Bagging Decision Tree (BDT) model was used to assess the impact of weather on airport capacities at selected high-demand airports in the United States. The ensemble bagging decision tree models were developed and validated using the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) data and weather forecast at these airports. The study examines the performance of BDT, along with traditional single Support Vector Machines (SVM), for airport runway configuration selection and airport arrival rates (AAR) prediction during weather impacts. Testing of these models was accomplished using observed weather, weather forecast, and airport operation information at the chosen airports. The experimental results show that ensemble methods are more accurate than a single SVM classifier. The airport capacity ensemble method presented here can be used as a decision support model that supports air traffic flow management to meet the weather impacted airport capacity in order to reduce costs and increase safety.

  15. Real Time Volcanic Cloud Products and Predictions for Aviation Alerts

    NASA Technical Reports Server (NTRS)

    Krotkov, Nickolay A.; Habib, Shahid; da Silva, Arlindo; Hughes, Eric; Yang, Kai; Brentzel, Kelvin; Seftor, Colin; Li, Jason Y.; Schneider, David; Guffanti, Marianne; hide

    2014-01-01

    Volcanic eruptions can inject significant amounts of sulfur dioxide (SO2) and volcanic ash into the atmosphere, posing a substantial risk to aviation safety. Ingesting near-real time and Direct Readout satellite volcanic cloud data is vital for improving reliability of volcanic ash forecasts and mitigating the effects of volcanic eruptions on aviation and the economy. NASA volcanic products from the Ozone Monitoring Insrument (OMI) aboard the Aura satellite have been incorporated into Decision Support Systems of many operational agencies. With the Aura mission approaching its 10th anniversary, there is an urgent need to replace OMI data with those from the next generation operational NASA/NOAA Suomi National Polar Partnership (SNPP) satellite. The data provided from these instruments are being incorporated into forecasting models to provide quantitative ash forecasts for air traffic management. This study demonstrates the feasibility of the volcanic near-real time and Direct Readout data products from the new Ozone Monitoring and Profiling Suite (OMPS) ultraviolet sensor onboard SNPP for monitoring and forecasting volcanic clouds. The transition of NASA data production to our operational partners is outlined. Satellite observations are used to constrain volcanic cloud simulations and improve estimates of eruption parameters, resulting in more accurate forecasts. This is demonstrated for the 2012 eruption of Copahue. Volcanic eruptions are modeled using the Goddard Earth Observing System, Version 5 (GEOS-5) and the Goddard Chemistry Aerosol and Radiation Transport (GOCART) model. A hindcast of the disruptive eruption from Iceland's Eyjafjallajokull is used to estimate aviation re-routing costs using Metron Aviation's ATM Tools.

  16. Network Performance Evaluation Model for assessing the impacts of high-occupancy vehicle facilities

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Janson, B.N.; Zozaya-Gorostiza, C.; Southworth, F.

    1986-09-01

    A model to assess the impacts of major high-occupancy vehicle (HOV) facilities on regional levels of energy consumption and vehicle air pollution emissions in urban aeas is developed and applied. This model can be used to forecast and compare the impacts of alternative HOV facility design and operation plans on traffic patterns, travel costs, model choice, travel demand, energy consumption and vehicle emissions. The model is designed to show differences in the overall impacts of alternative HOV facility types, locations and operation plans rather than to serve as a tool for detailed engineering design and traffic planning studies. The Networkmore » Performance Evaluation Model (NETPEM) combines several urban transportation planning models within a multi-modal network equilibrium framework including modules with which to define the type, location and use policy of the HOV facility to be tested, and to assess the impacts of this facility.« less

  17. Future satellite systems - Market demand assessment

    NASA Technical Reports Server (NTRS)

    Reiner, P. S.

    1981-01-01

    During 1979-80, a market study was performed regarding the future total demand for communications services, and satellite transmission service at the 4/6 GHz, 12/14 GHz, and 20/30 GHz frequencies. Included in the study were a variety of communications traffic characteristics as well as projections of the cost of C and Ku band satellite systems through the year 2000. In connection with the considered study, a total of 15 major study tasks and subtasks were undertaken and were all interrelated in various ways. The telecommunications service forecasts were concerned with a total of 21 data services, 5 voice services, and 5 video services. The traffic volumes within the U.S. for the three basic services were projected for three time periods. It is found that the fixed frequency allocation for domestic satellites combined with potential interference from adjacent satellites means a near term lack of orbital positions above the U.S.

  18. Alternative method of highway traffic safety analysis for developing countries using delphi technique and Bayesian network.

    PubMed

    Mbakwe, Anthony C; Saka, Anthony A; Choi, Keechoo; Lee, Young-Jae

    2016-08-01

    Highway traffic accidents all over the world result in more than 1.3 million fatalities annually. An alarming number of these fatalities occurs in developing countries. There are many risk factors that are associated with frequent accidents, heavy loss of lives, and property damage in developing countries. Unfortunately, poor record keeping practices are very difficult obstacle to overcome in striving to obtain a near accurate casualty and safety data. In light of the fact that there are numerous accident causes, any attempts to curb the escalating death and injury rates in developing countries must include the identification of the primary accident causes. This paper, therefore, seeks to show that the Delphi Technique is a suitable alternative method that can be exploited in generating highway traffic accident data through which the major accident causes can be identified. In order to authenticate the technique used, Korea, a country that underwent similar problems when it was in its early stages of development in addition to the availability of excellent highway safety records in its database, is chosen and utilized for this purpose. Validation of the methodology confirms the technique is suitable for application in developing countries. Furthermore, the Delphi Technique, in combination with the Bayesian Network Model, is utilized in modeling highway traffic accidents and forecasting accident rates in the countries of research. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Environmental consequences of Pollution and its Impact on climate Using Geospatial Technology

    NASA Astrophysics Data System (ADS)

    Kumar, Amit; Vandana, Vandana

    2016-07-01

    Modern transportation is an indispensable ingredient for development, allowing the pressure group of labor, supplies and goods, and enabling general public to access key resources and services. Climate change is a most important threat to sustainable development in any developing or developed country. Urban air pollution is on the rise, due to rapid economic and inhabitants growth and an increase in motorization. Modern transport is fundamental for improvement, allowing the movement of goods and enabling general public to access key resources and services. Travel today is relatively faster and people across the world are travelling more than ever before. Its stipulate regarding forecast is an indispensable part of transportation development in order to evaluate future needs of an urban area. Over increasing traffic concentration posed continued threat to ambient air quality and responsible for producing agents of physical condition hazards. Geospatial technology provides the smartest approach to resolve these inconvenience as it can cover a large area in a fraction of time. The research work focuses on the recognition of traffic intensities with increasing of SO2, NO2 and noise level considered at particular traffic sites in the Varanasi, Uttar Pradesh, India. SO2, NO2 and Noise levels recorded in the city, are much higher than the permissible level and are likely to causes associated health and psychological illnesses to nearby inhabitant. Keywords: Population growth; Traffic; Transportation

  20. Contrail Cirrus Forecasts for the ML-CIRRUS Experiment and Some Comparison Results

    NASA Astrophysics Data System (ADS)

    Schumann, Ulrich; Graf, Kaspar; Bugliaro, Luca; Dörnbrack, Andreas; Giez, Andreas; Jurkat, Tina; Kaufmann, Stefan; Krämer, Martina; Minikin, Andreas; Schäfler, Andreas; Voigt, Christiane; Wirth, Martin; Zahn, Andreas; Ziereis, Helmut

    2015-04-01

    Model simulations with the contrail cirrus prediction model CoCiP driven by numerical weather prediction (NWP) data provided from the European Centre for Medium Range Forecasts (ECMWF) and global aircraft waypoint data show a mean computed cover (for optical depth larger than 0.1) of 0.23% globally, and 5.4% over mid Europe (Schumann and Graf, JGR, 2013). The computed mean longwave radiative forcing (RF) reaches 3 W m-2 over mid Europe (10°W-20°E and 40°N-55°N), and 0.13 W m-2 globally. The global net RF is about 40-60% smaller because of compensating shortwave cooling induced by contrails during daytime. The results depend on several model details such as the number of ice particles forming from aircraft soot emissions, the contrail plume dispersion, ice particle sedimentation etc., all influencing contrail life time and their optical properties. The quantitative results depend also strongly on ambient relative humidity, vertical motion and on ice water content of other cirrus predicted by the NWP model. In order to test and possibly improve this and other contrail models, high-quality observations are needed to which multi-parameter model output can be compared. The Mid-Latitude Cirrus Experiment ML-CIRRUS was performed (see C. Voigt et al., this conference) with a suite of in-situ and Lidar instruments for airborne measurements on the research aircraft HALO. Before and during the mission, CoCiP was run daily to provide 3-days forecasts of contrail cover using operational ECMWF forecasts and historical traffic data. CoCiP forecast output was made available in an internet tool twice a day for experiment planning. The one-day and two-day contrail forecasts often showed only small differences. Still, most recent forecasts and detailed satellite observations results were transmitted via satellite link to the crew for onboard campaign optimization. After the campaign, a data base of realistic air traffic data has been setup from various sources, and CoCiP was rerun with improved ECMWF-NWP data (at one-hour time resolution). The model results are included in the HALO mission data bank, and the results are available for comparison to in-situ data. The data are useful for identifying aircraft and other sources for measured air properties. The joint analysis of observations and model result has basically just started. Preliminary results from comparisons with lidar-measured extinction profiles, in-situ measured humidity, nitrogen oxides, and aerosol and ice particle concentrations, and with meteorological observations (wind, temperature etc.) illustrate the expected gain in insight. The contrail forecasts have been checked by comparison to available data including satellite data and HALO observations. During the campaign, it became obvious that predicted contrail cirrus cover compared qualitatively mostly well with what was found when HALO reached predicted cirrus regions. From the analysis of the measured data, some examples of significant correlation between model results and observations have been found. However, the quantitative agreement is not uniform. As expected, nature is far more variable than a model can predict. The observed optical properties of cirrus and contrails vary far more in time and space than predicted. Local values were often far higher or lower than mean values. A one-to-one correlation between local observations and model results is not to be expected. This inhomogeneity may have consequences for the climate impact of aviation induced cloud changes.

  1. Interval Management Display Design Study

    NASA Technical Reports Server (NTRS)

    Baxley, Brian T.; Beyer, Timothy M.; Cooke, Stuart D.; Grant, Karlus A.

    2014-01-01

    In 2012, the Federal Aviation Administration (FAA) estimated that U.S. commercial air carriers moved 736.7 million passengers over 822.3 billion revenue-passenger miles. The FAA also forecasts, in that same report, an average annual increase in passenger traffic of 2.2 percent per year for the next 20 years, which approximates to one-and-a-half times the number of today's aircraft operations and passengers by the year 2033. If airspace capacity and throughput remain unchanged, then flight delays will increase, particularly at those airports already operating near or at capacity. Therefore it is critical to create new and improved technologies, communications, and procedures to be used by air traffic controllers and pilots. National Aeronautics and Space Administration (NASA), the FAA, and the aviation industry are working together to improve the efficiency of the National Airspace System and the cost to operate in it in several ways, one of which is through the creation of the Next Generation Air Transportation System (NextGen). NextGen is intended to provide airspace users with more precise information about traffic, routing, and weather, as well as improve the control mechanisms within the air traffic system. NASA's Air Traffic Management Technology Demonstration-1 (ATD-1) Project is designed to contribute to the goals of NextGen, and accomplishes this by integrating three NASA technologies to enable fuel-efficient arrival operations into high-density airports. The three NASA technologies and procedures combined in the ATD-1 concept are advanced arrival scheduling, controller decision support tools, and aircraft avionics to enable multiple time deconflicted and fuel efficient arrival streams in high-density terminal airspace.

  2. Comparative analysis of zonal systems for macro-level crash modeling.

    PubMed

    Cai, Qing; Abdel-Aty, Mohamed; Lee, Jaeyoung; Eluru, Naveen

    2017-06-01

    Macro-level traffic safety analysis has been undertaken at different spatial configurations. However, clear guidelines for the appropriate zonal system selection for safety analysis are unavailable. In this study, a comparative analysis was conducted to determine the optimal zonal system for macroscopic crash modeling considering census tracts (CTs), state-wide traffic analysis zones (STAZs), and a newly developed traffic-related zone system labeled traffic analysis districts (TADs). Poisson lognormal models for three crash types (i.e., total, severe, and non-motorized mode crashes) are developed based on the three zonal systems without and with consideration of spatial autocorrelation. The study proposes a method to compare the modeling performance of the three types of geographic units at different spatial configurations through a grid based framework. Specifically, the study region is partitioned to grids of various sizes and the model prediction accuracy of the various macro models is considered within these grids of various sizes. These model comparison results for all crash types indicated that the models based on TADs consistently offer a better performance compared to the others. Besides, the models considering spatial autocorrelation outperform the ones that do not consider it. Based on the modeling results and motivation for developing the different zonal systems, it is recommended using CTs for socio-demographic data collection, employing TAZs for transportation demand forecasting, and adopting TADs for transportation safety planning. The findings from this study can help practitioners select appropriate zonal systems for traffic crash modeling, which leads to develop more efficient policies to enhance transportation safety. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.

  3. The transport forecast - an important stage of transport management

    NASA Astrophysics Data System (ADS)

    Dragu, Vasile; Dinu, Oana; Oprea, Cristina; Alina Roman, Eugenia

    2017-10-01

    The transport system is a powerful system with varying loads in operation coming from changes in freight and passenger traffic in different time periods. The variations are due to the specific conditions of organization and development of socio-economic activities. The causes of varying loads can be included in three groups: economic, technical and organizational. The assessing of transport demand variability leads to proper forecast and development of the transport system, knowing that the market price is determined on equilibrium between supply and demand. The reduction of transport demand variability through different technical solutions, organizational, administrative, legislative leads to an increase in the efficiency and effectiveness of transport. The paper presents a new way of assessing the future needs of transport through dynamic series. Both researchers and practitioners in transport planning can benefit from the research results. This paper aims to analyze in an original approach how a good transport forecast can lead to a better management in transport, with significant effects on transport demand full meeting in quality terms. The case study shows how dynamic series of statistics can be used to identify the size of future demand addressed to the transport system.

  4. Models for Train Passenger Forecasting of Java and Sumatra

    NASA Astrophysics Data System (ADS)

    Sartono

    2017-04-01

    People tend to take public transportation to avoid high traffic, especially in Java. In Jakarta, the number of railway passengers is over than the capacity of the train at peak time. This is an opportunity as well as a challenge. If it is managed well then the company can get high profit. Otherwise, it may lead to disaster. This article discusses models for the train passengers, hence, finding the reasonable models to make a prediction overtimes. The Box-Jenkins method is occupied to develop a basic model. Then, this model is compared to models obtained using exponential smoothing method and regression method. The result shows that Holt-Winters model is better to predict for one-month, three-month, and six-month ahead for the passenger in Java. In addition, SARIMA(1,1,0)(2,0,0) is more accurate for nine-month and twelve-month oversee. On the other hand, for Sumatra passenger forecasting, SARIMA(1,1,1)(0,0,2) gives a better approximation for one-month ahead, and ARIMA model is best for three-month ahead prediction. The rest, Trend Seasonal and Liner Model has the least of RMSE to forecast for six-month, nine-month, and twelve-month ahead.

  5. Comprehensive Software Eases Air Traffic Management

    NASA Technical Reports Server (NTRS)

    2007-01-01

    To help air traffic control centers improve the safety and the efficiency of the National Airspace System, Ames Research Center developed the Future Air Traffic Management Concepts Evaluation Tool (FACET) software, which won NASA's 2006 "Software of the Year" competition. In 2005, Ames licensed FACET to Flight Explorer Inc., for integration into its Flight Explorer (version 6.0) software. The primary FACET features incorporated in the Flight Explorer software system alert airspace users to forecasted demand and capacity imbalances. Advance access to this information helps dispatchers anticipate congested sectors (airspace) and delays at airports, and decide if they need to reroute flights. FACET is now a fully integrated feature in the Flight Explorer Professional Edition (version 7.0). Flight Explorer Professional offers end-users other benefits, including ease of operation; automatic alerts to inform users of important events such as weather conditions and potential airport delays; and international, real-time flight coverage over Canada, the United Kingdom, New Zealand, and sections of the Atlantic and Pacific Oceans. Flight Explorer Inc. recently broadened coverage by partnering with Honeywell International Inc.'s Global Data Center, Blue Sky Network, Sky Connect LLC, SITA, ARINC Incorporated, Latitude Technologies Corporation, and Wingspeed Corporation, to track their aircraft anywhere in the world.

  6. A Small Aircraft Transportation System (SATS) Demand Model

    NASA Technical Reports Server (NTRS)

    Long, Dou; Lee, David; Johnson, Jesse; Kostiuk, Peter; Yackovetsky, Robert (Technical Monitor)

    2001-01-01

    The Small Aircraft Transportation System (SATS) demand modeling is a tool that will be useful for decision-makers to analyze SATS demands in both airport and airspace. We constructed a series of models following the general top-down, modular principles in systems engineering. There are three principal models, SATS Airport Demand Model (SATS-ADM), SATS Flight Demand Model (SATS-FDM), and LMINET-SATS. SATS-ADM models SATS operations, by aircraft type, from the forecasts in fleet, configuration and performance, utilization, and traffic mixture. Given the SATS airport operations such as the ones generated by SATS-ADM, SATS-FDM constructs the SATS origin and destination (O&D) traffic flow based on the solution of the gravity model, from which it then generates SATS flights using the Monte Carlo simulation based on the departure time-of-day profile. LMINET-SATS, an extension of LMINET, models SATS demands at airspace and airport by all aircraft operations in US The models use parameters to provide the user with flexibility and ease of use to generate SATS demand for different scenarios. Several case studies are included to illustrate the use of the models, which are useful to identify the need for a new air traffic management system to cope with SATS.

  7. An open-terrain line source model coupled with street-canyon effects to forecast carbon monoxide at traffic roundabout.

    PubMed

    Pandian, Suresh; Gokhale, Sharad; Ghoshal, Aloke Kumar

    2011-02-15

    A double-lane four-arm roundabout, where traffic movement is continuous in opposite directions and at different speeds, produces a zone responsible for recirculation of emissions within a road section creating canyon-type effect. In this zone, an effect of thermally induced turbulence together with vehicle wake dominates over wind driven turbulence causing pollutant emission to flow within, resulting into more or less equal amount of pollutants upwind and downwind particularly during low winds. Beyond this region, however, the effect of winds becomes stronger, causing downwind movement of pollutants. Pollutant dispersion caused by such phenomenon cannot be described accurately by open-terrain line source model alone. This is demonstrated by estimating one-minute average carbon monoxide concentration by coupling an open-terrain line source model with a street canyon model which captures the combine effect to describe the dispersion at non-signalized roundabout. The results of the modeling matched well with the measurements compared with the line source model alone and the prediction error reduced by about 50%. The study further demonstrated this with traffic emissions calculated by field and semi-empirical methods. Copyright © 2010 Elsevier B.V. All rights reserved.

  8. Analysis and Prediction of Weather Impacted Ground Stop Operations

    NASA Technical Reports Server (NTRS)

    Wang, Yao Xun

    2014-01-01

    When the air traffic demand is expected to exceed the available airport's capacity for a short period of time, Ground Stop (GS) operations are implemented by Federal Aviation Administration (FAA) Traffic Flow Management (TFM). The GS requires departing aircraft meeting specific criteria to remain on the ground to achieve reduced demands at the constrained destination airport until the end of the GS. This paper provides a high-level overview of the statistical distributions as well as causal factors for the GSs at the major airports in the United States. The GS's character, the weather impact on GSs, GS variations with delays, and the interaction between GSs and Ground Delay Programs (GDPs) at Newark Liberty International Airport (EWR) are investigated. The machine learning methods are used to generate classification models that map the historical airport weather forecast, schedule traffic, and other airport conditions to implemented GS/GDP operations and the models are evaluated using the cross-validations. This modeling approach produced promising results as it yielded an 85% overall classification accuracy to distinguish the implemented GS days from the normal days without GS and GDP operations and a 71% accuracy to differentiate the GS and GDP implemented days from the GDP only days.

  9. Automated turbulence forecasts for aviation hazards

    NASA Astrophysics Data System (ADS)

    Sharman, R.; Frehlich, R.; Vandenberghe, F.

    2010-09-01

    An operational turbulence forecast system for commercial and aviation use is described that is based on an ensemble of turbulence diagnostics derived from standard NWP model outputs. In the U. S. this forecast product is named GTG (Graphical Turbulence Guidance) and has been described in detail in Sharman et al., WAF 2006. Since turbulence has many sources in the atmosphere, the ensemble approach of combining diagnostics has been shown to provide greater statistical accuracy than the use of a single diagnostic, or of a subgrid tke parameterization. GTG is sponsored by the FAA, and has undergone rigorous accuracy, safety, and usability evaluations. The GTG product is now hosted on NOAA's Aviation Data Service (ADDS), web site (http://aviationweather.gov/), for access by pilots, air traffic controllers, and dispatchers. During this talk the various turbulence diagnostics, their statistical properties, and their relative performance (based on comparisons to observations) will be presented. Importantly, the model output is ɛ1/3 (where ɛ is the eddy dissipation rate), so is aircraft independent. The diagnostics are individually and collectively calibrated so that their PDFs satisfy the expected log normal distribution of ɛ^1/3. Some of the diagnostics try to take into account the role of gravity waves and inertia-gravity waves in the turbulence generation process. Although the current GTG product is based on the RUC forecast model running over the CONUS, it is transitioning to a WRF based product, and in fact WRF-based versions are currently running operationally over Taiwan and has also been implemented for use by the French Navy in climatological studies. Yet another version has been developed which uses GFS model output to provide global turbulence forecasts. Thus the forecast product is available as a postprocessing program for WRF or other model output and provides 3D maps of turbulence likelihood of any region where NWP model data is available. Although the current GTG has been used mainly for large commercial aircraft, since the output is aircraft independent it could readily be scaled to smaller aircraft such as UAVs. Further, the ensemble technique allows the diagnostics to be used to form probabilistic forecasts, in a manner similar to ensemble NWP forecasts.

  10. Subject Matter Expert Evaluation of Multi-Flight Common Route Advisories

    NASA Technical Reports Server (NTRS)

    Bilimoria, Karl; Hayashi, Miwa; Sheth, Kapil S.

    2017-01-01

    Traffic flow management seeks to balance the demand for National Airspace System (NAS) flight resources, such as airspace and airports, with the available supply. When forecasted weather blocks nominal air traffic routes, traffic managers must re-route affected flights for weather avoidance. Depending on the nature and scope of the weather, traffic managers may use pre-coordinated re-routes such as Playbook Routes or Coded Departure Routes, or may design ad hoc local re-routes. The routes of affected flights are modified accordingly. These weather avoidance routes will, of course, be less efficient than the nominal routes due to increased flight time and fuel burn. In current traffic management operations, the transition into a weather avoidance re-routing initiative is typically implemented more aggressively than the transition out of that initiative after the weather has dissipated or moved away. For example, strategic large-scale Playbook re-routes are sometimes left in place (as initially implemented) for many hours before being lifted entirely when the weather dissipates. There is an opportunity to periodically modify the re-routing plan as weather evolves, thereby attenuating its adverse impact on flight time and fuel consumption; this is called delay recovery. Multi-Flight Common Routes (MFCR) is a NASA-developed operational concept and associated decision support tool for delay recovery, designed to assist traffic managers to efficiently update weather avoidance traffic routes after the original re-routes have become stale due to subsequent evolution of the convective weather system. MFCR groups multiple flights to reduce the number of advisories that the traffic manager needs to evaluate, and also merges these flights on a common route segment to provide an orderly flow of re-routed traffic. The advisory is presented to the appropriate traffic manager who evaluates it and has the option to modify it using MFCRs graphical user interface. If the traffic manager finds the advisory to be operationally appropriate, he or she would coordinate with the Area Supervisor(s) of the sectors that currently control the flights in the advisory. When the traffic manager accepts the MFCR advisory via the user interface, the corresponding flight plan amendments would be sent to the displays of the appropriate sector controllers, using the Airborne Re-Routing (ABRR) capability which is scheduled for nationwide operation in 2017. The sector controllers would then offer this time-saving route modification to the pilots of the affected flights via datalink (or voice), and implement the corresponding flight plan amendment if the pilots accept it. MFCR is implemented as an application in the software environment of the Future Air traffic management Concepts Evaluation Tool (FACET). This paper focuses on an initial subject matter expert (SME) evaluation of MFCR. The evaluation covers MFCRs operational concept, algorithm, and user interface.

  11. Forecasting Cause-Specific Mortality in Korea up to Year 2032.

    PubMed

    Yun, Jae-Won; Son, Mia

    2016-08-01

    Forecasting cause-specific mortality can help estimate the future burden of diseases and provide a clue for preventing diseases. Our objective was to forecast the mortality for causes of death in the future (2013-2032) based on the past trends (1983-2012) in Korea. The death data consisted of 12 major causes of death from 1983 to 2012 and the population data consisted of the observed and estimated populations (1983-2032) in Korea. The modified age-period-cohort model with an R-based program, nordpred software, was used to forecast future mortality. Although the age-standardized rates for the world standard population for both sexes are expected to decrease from 2008-2012 to 2028-2032 (males: -31.4%, females: -32.3%), the crude rates are expected to increase (males: 46.3%, females: 33.4%). The total number of deaths is also estimated to increase (males: 52.7%, females: 41.9%). Additionally, the largest contribution to the overall change in deaths was the change in the age structures. Several causes of death are projected to increase in both sexes (cancer, suicide, heart diseases, pneumonia and Alzheimer's disease), while others are projected to decrease (cerebrovascular diseases, liver diseases, diabetes mellitus, traffic accidents, chronic lower respiratory diseases, and pulmonary tuberculosis). Cancer is expected to be the highest cause of death for both the 2008-2012 and 2028-2032 time periods in Korea. To reduce the disease burden, projections of the future cause-specific mortality should be used as fundamental data for developing public health policies.

  12. An oceanographic survey for oil spill monitoring and model forecasting validation using remote sensing and in situ data in the Mediterranean Sea

    NASA Astrophysics Data System (ADS)

    Pisano, A.; De Dominicis, M.; Biamino, W.; Bignami, F.; Gherardi, S.; Colao, F.; Coppini, G.; Marullo, S.; Sprovieri, M.; Trivero, P.; Zambianchi, E.; Santoleri, R.

    2016-11-01

    A research cruise was organized on board the Italian National Research Council (CNR) R/V Urania to test the oil spill monitoring system developed during the PRogetto pilota Inquinamento Marino da Idrocarburi project (PRIMI, pilot project for marine oil pollution). For the first time, this system integrated in a modular way satellite oil spill detection (Observation Module) and oil spill displacement forecasting (Forecast Module) after detection. The Observation Module was based on both Synthetic Aperture RADAR (SAR) and optical satellite detection, namely SAR and Optical Modules, while the Forecast Module on Lagrangian numerical circulation models. The cruise (Aug. 6-Sep. 7, 2009) took place in the Mediterranean Sea, around Sicily, an area affected by heavy oil tanker traffic with frequent occurrence of oil spills resulting from illegal tank washing. The cruise plan was organized in order to have the ship within the SAR image frames selected for the cruise, at acquisition time. In this way, the ship could rapidly reach oil slicks detected in the images by the SAR Module, and/or eventually by the Optical Module, in order to carry out visual and instrumental inspection of the slicks. During the cruise, several oil spills were detected by the two Observation Modules and verified in situ, with the essential aid of the Forecasting Module which provided the slick position by the time the ship reached the area after the alert given by the SAR and/or optical imagery. Results confirm the good capability of oil spill SAR detection and indicate that also optical sensors are able to detect oil spills, ranging from thin films to slicks containing heavily polluted water. Also, results confirm the useful potential of oil spill forecasting models, but, on the other hand, that further work combining satellite, model and in situ data is necessary to refine the PRIMI system.

  13. A robust method to forecast volcanic ash clouds

    USGS Publications Warehouse

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

    2012-01-01

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

  14. Design and skill assessment of an Operational Forecasting System for currents and sea level variability to the Santos Estuarine System - Brazil

    NASA Astrophysics Data System (ADS)

    Godoi Rezende Costa, C.; Castro, B. M.; Blumberg, A. F.; Leite, J. R. B., Sr.

    2017-12-01

    Santos City is subject to an average of 12 storm tide events per year. Such events bring coastal flooding able to threat human life and damage coastal infrastructure. Severe events have forced the interruption of ferry boat services and ship traffic through Santos Harbor, causing great impacts to Santos Port, the largest in South America, activities. Several studies have focused on the hydrodynamics of storm tide events but only a few of those studies have pursued an operational initiative to predict short term (< 3 days) sea level variability. The goals of this study are (i) to describe the design of an operational forecasting system built to predict sea surface elevation and currents in the Santos Estuarine System and (ii) to evaluate model performance in simulating observed sea surface elevation. The Santos Operational Forecasting System (SOFS) hydrodynamic module is based on the Stevens Institute Estuarine and Coastal Ocean Model (sECOM). The fully automated SOFS is designed to provide up to 71 h forecast of sea surface elevations and currents every day. The system automatically collects results from global models to run the SOFS nested into another sECOM based model for the South Brazil Bight (SBB). Global forecasting results used to force both models come from Mercator Ocean, released by Copernicus Marine Service, and from the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) stablished by the Center for Weather Forecasts and Climate Studies (with Portuguese acronym CPTEC). The complete routines task take about 8 hours of run time to finish. SOFS was able to hindcast a severe storm tide event that took place in Santos on August 21-22, 2016. Comparisons with observed sea level provided skills of 0.92 and maximum root mean square errors of 25 cm. The good agreement with observed data shows the potential of the designed system to predict storm tides and to support both human and assets protection.

  15. Association Between Media Dose, Ad Tagging, and Changes in Web Traffic for a National Tobacco Education Campaign: A Market-Level Longitudinal Study.

    PubMed

    Shafer, Paul R; Davis, Kevin C; Patel, Deesha; Rodes, Robert; Beistle, Diane

    2016-02-17

    In 2012, the US Centers for Disease Control and Prevention (CDC) launched Tips From Former Smokers (Tips), the first federally funded national tobacco education campaign. In 2013, a follow-up Tips campaign aired on national cable television networks, radio, and other channels, with supporting digital advertising to drive traffic to the Tips campaign website. The objective of this study was to use geographic and temporal variability in 2013 Tips campaign television media doses and ad tagging to evaluate changes in traffic to the campaign website in response to specific doses of campaign media. Linear regression models were used to estimate the dose-response relationship between weekly market-level television gross rating points (GRPs) and weekly Web traffic to the Tips campaign website. This relationship was measured using unique visitors, total visits, and page views as outcomes. Ad GRP effects were estimated separately for ads tagged with the Tips campaign website URL and 1-800-QUIT-NOW. In the average media market, an increase of 100 television GRPs per week for ads tagged with the Tips campaign website URL was associated with an increase of 650 unique visitors (P<.001), 769 total visits (P<.001), and 1255 total page views (P<.001) per week. The associations between GRPs for ads tagged with 1-800-QUIT-NOW and each Web traffic measure were also statistically significant (P<.001), but smaller in magnitude. Based on these findings, we estimate that the 16-week 2013 Tips television campaign generated approximately 660,000 unique visitors, 900,000 total visits, and 1,390,000 page views for the Tips campaign website. These findings can help campaign planners forecast the likely impact of targeted advertising efforts on consumers' use of campaign-specific websites.

  16. Performance of Airborne Precision Spacing Under Realistic Wind Conditions and Limited Surveillance Range

    NASA Technical Reports Server (NTRS)

    Wieland, Frederick; Santos, Michel; Krueger, William; Houston, Vincent E.

    2011-01-01

    With the expected worldwide increase of air traffic during the coming decade, both the Federal Aviation Administration's (FAA's) Next Generation Air Transportation System (NextGen), as well as Eurocontrol's Single European Sky ATM Research (SESAR) program have, as part of their plans, air traffic management (ATM) solutions that can increase performance without requiring time-consuming and expensive infrastructure changes. One such solution involves the ability of both controllers and flight crews to deliver aircraft to the runway with greater accuracy than they can today. Previous research has shown that time-based spacing techniques, wherein the controller assigns a time spacing to each pair of arriving aircraft, can achieve this goal by providing greater runway delivery accuracy and producing a concomitant increase in system-wide performance. The research described herein focuses on one specific application of time-based spacing, called Airborne Precision Spacing (APS), which has evolved over the past ten years. This research furthers APS understanding by studying its performance with realistic wind conditions obtained from atmospheric sounding data and with realistic wind forecasts obtained from the Rapid Update Cycle (RUC) short-range weather forecast. In addition, this study investigates APS performance with limited surveillance range, as provided by the Automatic Dependent Surveillance-Broadcast (ADS-B) system, and with an algorithm designed to improve APS performance when ADS-B surveillance data is unavailable. The results presented herein quantify the runway threshold delivery accuracy of APS under these conditions, and also quantify resulting workload metrics such as the number of speed changes required to maintain spacing.

  17. Performance of Airborne Precision Spacing Under Realistic Wind Conditions

    NASA Technical Reports Server (NTRS)

    Wieland, Frederick; Santos, Michel; Krueger, William; Houston, Vincent E.

    2011-01-01

    With the expected worldwide increase of air traffic during the coming decade, both the Federal Aviation Administration s (FAA s) Next Generation Air Transportation System (NextGen), as well as Eurocontrol s Single European Sky ATM Research (SESAR) program have, as part of their plans, air traffic management solutions that can increase performance without requiring time-consuming and expensive infrastructure changes. One such solution involves the ability of both controllers and flight crews to deliver aircraft to the runway with greater accuracy than is possible today. Previous research has shown that time-based spacing techniques, wherein the controller assigns a time spacing to each pair of arriving aircraft, is one way to achieve this goal by providing greater runway delivery accuracy that produces a concomitant increase in system-wide performance. The research described herein focuses on a specific application of time-based spacing, called Airborne Precision Spacing (APS), which has evolved over the past ten years. This research furthers APS understanding by studying its performance with realistic wind conditions obtained from atmospheric sounding data and with realistic wind forecasts obtained from the Rapid Update Cycle (RUC) short-range weather forecast. In addition, this study investigates APS performance with limited surveillance range, as provided by the Automatic Dependent Surveillance-Broadcast (ADS-B) system, and with an algorithm designed to improve APS performance when an ADS-B signal is unavailable. The results presented herein quantify the runway threshold delivery accuracy of APS un-der these conditions, and also quantify resulting workload metrics such as the number of speed changes required to maintain spacing.

  18. Numerical simulations of an advection fog event over Shanghai Pudong International Airport with the WRF model

    NASA Astrophysics Data System (ADS)

    Lin, Caiyan; Zhang, Zhongfeng; Pu, Zhaoxia; Wang, Fengyun

    2017-10-01

    A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advection fog event over Shanghai Pudong International Airport (ZSPD) with the Weather Research and Forecasting (WRF) model. Using the current operational settings at the Meteorological Center of East China Air Traffic Management Bureau, the WRF model successfully predicts the fog event at ZSPD. Additional numerical experiments are performed to examine the physical processes associated with the fog event. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation (both longwave and shortwave) processes. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, suggesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physical processes to spin up adequately during the fog simulation. The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.

  19. The Primi Project: August-September 2009 Validation Cruise On Oil Spill Detection And Fate

    NASA Astrophysics Data System (ADS)

    Santoleri, R.; Bignami, F.; Bohm, E.; Nichio, F.; De Dominicis, M.; Ruggieri, G.; Marulllo, S.; Trivero, P.; Zambianchi, E.; Archetti, R.; Adamo, M.; Biamino, W.; Borasi, M.; Buongiorno Nardelli, B.; Cavagnero, M.; Colao, F.; Colella, S.; Coppini, G.; Debettio, V.; De Carolis, G.; Forneris, V.; Griffa, A.; Iacono, R.; Lombardi, E.; Manzella, G.; Mercantini, A.; Napolitano, E.; Pinardi, N.; Pandiscia, G.; Pisano, A.; Rupolo, V.; Reseghetti, F.; Sabia, L.; Sorgente, R.; Sprovieri, M.; Terranova, G.; Trani, M.; Volpe, G.

    2010-04-01

    In the framework of the ASI PRIMI Project, CNR- ISAC, in collaboration with the PRIMI partners, organized a validation cruise for the PRIMI oil spill monitoring and forecasting system on board the CNR R/V Urania. The cruise (Aug. 6 - Sept. 7 2009) took place in the Sicily Strait, an area affected by large oil tanker traffic. The cruise plan was organized in order to have the ship within the selected SAR image frames at acquisition time so that the ship could move toward the oil slick and verify it via visual and instrumental inspection. During the cruise, several oil spills, presumably being the result of illegal tank washing, were detected by the PRIMI system and were verified in situ. Preliminary results indicate that SAR and optical satellites are able to detect heavy and thin film oil spills, the maturity of oil spill forecasting models and that further work combining satellite, model and in situ data is necessary to assess the spill severity from the signature in satellite imagery.

  20. Forecast and control of epidemics in a globalized world

    PubMed Central

    Hufnagel, L.; Brockmann, D.; Geisel, T.

    2004-01-01

    The rapid worldwide spread of severe acute respiratory syndrome demonstrated the potential threat an infectious disease poses in a closely interconnected and interdependent world. Here we introduce a probabilistic model that describes the worldwide spread of infectious diseases and demonstrate that a forecast of the geographical spread of epidemics is indeed possible. This model combines a stochastic local infection dynamics among individuals with stochastic transport in a worldwide network, taking into account national and international civil aviation traffic. Our simulations of the severe acute respiratory syndrome outbreak are in surprisingly good agreement with published case reports. We show that the high degree of predictability is caused by the strong heterogeneity of the network. Our model can be used to predict the worldwide spread of future infectious diseases and to identify endangered regions in advance. The performance of different control strategies is analyzed, and our simulations show that a quick and focused reaction is essential to inhibiting the global spread of epidemics. PMID:15477600

  1. Developing a Model for Forecasting Road Traffic Accident (RTA) Fatalities in Yemen

    NASA Astrophysics Data System (ADS)

    Karim, Fareed M. A.; Abdo Saleh, Ali; Taijoobux, Aref; Ševrović, Marko

    2017-12-01

    The aim of this paper is to develop a model for forecasting RTA fatalities in Yemen. The yearly fatalities was modeled as the dependent variable, while the number of independent variables included the population, number of vehicles, GNP, GDP and Real GDP per capita. It was determined that all these variables are highly correlated with the correlation coefficient (r ≈ 0.9); in order to avoid multicollinearity in the model, a single variable with the highest r value was selected (real GDP per capita). A simple regression model was developed; the model was very good (R2=0.916); however, the residuals were serially correlated. The Prais-Winsten procedure was used to overcome this violation of the regression assumption. The data for a 20-year period from 1991-2010 were analyzed to build the model; the model was validated by using data for the years 2011-2013; the historical fit for the period 1991 - 2011 was very good. Also, the validation for 2011-2013 proved accurate.

  2. Investigating the Impact of Off-Nominal Events on High-Density "Green" Arrivals

    NASA Technical Reports Server (NTRS)

    Callatine, Todd J.; Cabrall, Christopher; Kupfer, Michael; Martin, Lynne; Mercer, Joey; Palmer, Everett A.

    2012-01-01

    Trajectory-based controller tools developed to support a schedule-based terminal-area air traffic management (ATM) concept have been shown effective for enabling green arrivals along Area Navigation (RNAV) routes in moderately high-density traffic conditions. A recent human-in-the-loop simulation investigated the robustness of the concept and tools to off-nominal events events that lead to situations in which runway arrival schedules require adjustments and controllers can no longer use speed control alone to impose the necessary delays. Study participants included a terminal-area Traffic Management Supervisor responsible for adjusting the schedules. Sector-controller participants could issue alternate RNAV transition routes to absorb large delays. The study also included real-time winds/wind-forecast changes. The results indicate that arrival spacing accuracy, schedule conformance, and tool usage and usefulness are similar to that observed in simulations of nominal operations. However, the time and effort required to recover from an off-nominal event is highly context-sensitive, and impacted by the required schedule adjustments and control methods available for managing the evolving situation. The research suggests ways to bolster the off-nominal recovery process, and highlights challenges related to using human-in-the-loop simulation to investigate the safety and robustness of advanced ATM concepts.

  3. Benefit Opportunities for Integrated Surface and Airspace Departure Scheduling: A Study of Operations at Charlotte-Douglas International Airport

    NASA Technical Reports Server (NTRS)

    Coppenbarger, Rich; Jung, Yoon; Kozon, Tom; Farrahi, Amir; Malik, Wakar; Lee, Hanbong; Chevalley, Eric; Kistler, Matt

    2016-01-01

    NASA is collaborating with the FAA and aviation industry to develop and demonstrate new capabilities that integrate arrival, departure, and surface air-traffic operations. The concept relies on trajectory-based departure scheduling and collaborative decision making to reduce delays and uncertainties in taxi and climb operations. The paper describes the concept and benefit mechanisms aimed at improving flight efficiency and predictability while maintaining or improving operational throughput. The potential impact of the technology is studied and discussed through a quantitative analysis of relevant shortfalls at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport. Results from trajectory analysis indicate substantial opportunity to reduce taxi delays for both departures and arrivals by metering departures at the gate in a manner that maximizes throughput while adhering to takeoff restrictions due mostly to airspace constraints. Substantial taxi-out delay reduction is shown for flights subject to departure restrictions stemming from traffic flow management initiatives. Opportunities to improve the predictability of taxi, takeoff, and climb operations are examined and their potential impact on airline scheduling decisions and air-traffic forecasting is discussed. In addition, the potential to improve throughput with departure scheduling that maximizes use of available runway and airspace capacity is analyzed.

  4. a European Global Navigation Satellite System — the German Market and Value Adding Chain Effects

    NASA Astrophysics Data System (ADS)

    Vollerthun, A.; Wieser, M.

    2002-03-01

    Since Europe is considering to establish a "market-driven" European Global Navigation Satellite System, the German Center of Aerospace initiated a market research to justify a German investment in such a European project. The market research performed included the following market segments: aviation, railway, road traffic, shipping, surveying, farming, military, space applications, leisure, and sport. In these market segments, the forementioned inputs were determined for satellite navigation hardware (receivers) as well as satellite navigation services. The forecast period was from year 2007 to 2017. For the considered period, the market amounts to a total of DM 83.0 billion (approx. US $50 billion), whereas the satellite navigation equipment market makes up DM 39.8 billion, and charges for value-added-services amount to DM 43.2 billion. On closer examination road traffic can be identified as the dominant market share, both in the receiver-market and service-market. With a share of 96% for receivers and 73% for services the significance of the road traffic segment becomes obvious. The second part of this paper investigates the effects the market potential has on the Value-Adding-Chain. Therefore, all participants in the Value-Adding-Chain are identified, using industrial cost structure models the employment effect is analyzed, and possible tax revenues for the state are examined.

  5. Space Weather effects on airline communications in the high latitude regions

    NASA Astrophysics Data System (ADS)

    Honary, Farideh

    2014-05-01

    Efficient air traffic management depends on reliable communications between aircraft and the air traffic control centres at all times. At high latitudes, and especially on polar routing, VHF ground infrastructure does not exist and the aircraft have to rely on HF radio for communications. HF relies on reflections from the ionosphere to achieve long distance communications. Unfortunately the high latitude ionosphere is affected by space weather events. During such events HF radio communication can be severely disrupted and aircraft are forced to use longer low latitude routes with consequent increased flight time, fuel consumption and cost. This presentation describes a new research programme at the University of Lancaster in collaboration with the University of Leicester, Solar Metrics Ltd and Natural Resources Canada for the development of a nowcasting and forecasting HF communications tool designed for the particular needs of civilian airlines. This project funded by EPSRC will access a wide variety of solar and interplanetary measurements to derive a complete picture of space weather disturbances affecting radio absorption and reflection

  6. Wind Prediction Accuracy for Air Traffic Management Decision Support Tools

    NASA Technical Reports Server (NTRS)

    Cole, Rod; Green, Steve; Jardin, Matt; Schwartz, Barry; Benjamin, Stan

    2000-01-01

    The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an optimal interpolation of the latest ACARS reports since the RUC run. This paper presents an overview of the study's results including the identification and use of new large mor wind-prediction accuracy metrics that are key to ATM DST performance.

  7. Analysis of Runway Incursion Data

    NASA Technical Reports Server (NTRS)

    Green, Lawrence L.

    2013-01-01

    A statistical analysis of runway incursion (RI) events was conducted to ascertain relevance to the top ten challenges of the National Aeronautics and Space Administration Aviation Safety Program (AvSP). The information contained in the RI database was found to contain data that may be relevant to several of the AvSP top ten challenges. When combined with other data from the FAA documenting air traffic volume from calendar year 2000 through 2011, the structure of a predictive model emerges that can be used to forecast the frequency of RI events at various airports for various classes of aircraft and under various environmental conditions.

  8. A methodology for long range prediction of air transportation

    NASA Technical Reports Server (NTRS)

    Ayati, M. B.; English, J. M.

    1980-01-01

    The paper describes the methodology for long-time projection of aircraft fuel requirements. A new concept of social and economic factors for future aviation industry which provides an estimate of predicted fuel usage is presented; it includes air traffic forecasts and lead times for producing new engines and aircraft types. An air transportation model is then developed in terms of an abstracted set of variables which represent the entire aircraft industry on a macroscale. This model was evaluated by testing the required output variables from a model based on historical data over the past decades.

  9. Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Sensor Development

    NASA Technical Reports Server (NTRS)

    Daniels, Taumi S.

    2002-01-01

    In response to recommendations from the National Aviation Weather Program Council, the National Aeronautics and Space Administration (NASA) is working with industry to develop an electronic pilot reporting capability for small aircraft. This paper describes the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) sensor development effort. NASA is working with industry to develop a sensor capable of measuring temperature, relative humidity, magnetic heading, pressure, icing, and average turbulence energy dissipation. Users of the data include National Centers for Environmental Prediction (NCEP) forecast modelers, air traffic controllers, flight service stations, airline operation centers, and pilots. Preliminary results from flight tests are presented.

  10. The 20/30 GHz satellite systems technology needs assessment

    NASA Technical Reports Server (NTRS)

    Stevens, G.; Wright, D.

    1978-01-01

    Rain attenuation in the 20/30 GHz bands, and the resultant impact on system user costs were estimated for a variety of satellite communication system concepts. Results of previous and current NASA Lewis contractual and in-house studies on system design are reported as well as market studies conducted to evaluate the concepts and test their relevancy against forecasted market needs. The 20/30 GHz bands appear attractive economically and, with certain technology, appear to offer a virtually unlimited spectrum resource. This attractiveness is especially relevant to high density trunking where there is sufficient traffic to justify dual-station site diversity.

  11. Advanced subsonic long-haul transport terminal area compatibility study. Volume 1: Compatibility assessment

    NASA Technical Reports Server (NTRS)

    1974-01-01

    An analysis was made to identify airplane research and technology necessary to ensure advanced transport aircraft the capability of accommodating forecast traffic without adverse impact on airport communities. Projections were made of the delay, noise, and emissions impact of future aircraft fleets on typical large urban airport. Design requirements, based on these projections, were developed for an advanced technology, long-haul, subsonic transport. A baseline aircraft was modified to fulfill the design requirements for terminal area compatibility. Technical and economic comparisons were made between these and other aircraft configured to support the study.

  12. Forecasting Cause-Specific Mortality in Korea up to Year 2032

    PubMed Central

    2016-01-01

    Forecasting cause-specific mortality can help estimate the future burden of diseases and provide a clue for preventing diseases. Our objective was to forecast the mortality for causes of death in the future (2013-2032) based on the past trends (1983-2012) in Korea. The death data consisted of 12 major causes of death from 1983 to 2012 and the population data consisted of the observed and estimated populations (1983-2032) in Korea. The modified age-period-cohort model with an R-based program, nordpred software, was used to forecast future mortality. Although the age-standardized rates for the world standard population for both sexes are expected to decrease from 2008-2012 to 2028-2032 (males: -31.4%, females: -32.3%), the crude rates are expected to increase (males: 46.3%, females: 33.4%). The total number of deaths is also estimated to increase (males: 52.7%, females: 41.9%). Additionally, the largest contribution to the overall change in deaths was the change in the age structures. Several causes of death are projected to increase in both sexes (cancer, suicide, heart diseases, pneumonia and Alzheimer’s disease), while others are projected to decrease (cerebrovascular diseases, liver diseases, diabetes mellitus, traffic accidents, chronic lower respiratory diseases, and pulmonary tuberculosis). Cancer is expected to be the highest cause of death for both the 2008-2012 and 2028-2032 time periods in Korea. To reduce the disease burden, projections of the future cause-specific mortality should be used as fundamental data for developing public health policies. PMID:27478326

  13. Prediflood: A French research project aiming at developing a road submersion warning system for flash flood prone areas

    NASA Astrophysics Data System (ADS)

    Naulin, J. P.; Payrastre, O.; Gaume, E.; Delrieu, G.; Arnaud, P.; Lutoff, C.; Vincendon, B.

    2010-09-01

    Accurate flood forecasts are crucial for an efficient flood event management. Until now, hydro-meteorological forecasts have been mainly used for early-warnings in France (Meteorological and flood vigilance maps) or over the world (Flash-flood guidances). Forecasts are also often limited to the main streams or to specific watersheds with particular assets like hydropower dams, leaving aside large parts of the territory. Distributed hydro-meteorological forecasting models, able to take advantage of the now available high spatial and temporal resolution rainfall measurements, are promising tools for anticipating and quantifying the short term consequences of storm events all over a region. They would be very useful, especially in regions frequently affected by severe storms with complex spatio-temporal patterns. They would provide the necessary information for flood event management services to identify the areas at risk and to take the appropriate safety and rescue measures: prepositioning of rescue means, stopping of the traffic on exposed roads, determination of safe accesses or evacuation routes. Some preliminary tests conducted by the LCPC within the European project FLOODsite have shown encouraging results of a distributed hydro-meteorological forecasting model. It seems possible, despite the limits of the available rainfall measurements and the shortcomings of the rainfall-runoff models, to deliver distributed forecasts of possible local flood consequences - road submersion risk rating at about 5000 different locations over the Gard department in the tested case - with an acceptable level of accuracy. The PreDiFlood project (http://heberge.lcpc.fr/prediflood/) aims at consolidating and extending these first results with the objective to conduct pre-operational tests with possible end-users at the end of the project. Such a tool will not replace, but complement existing flood forecasting approaches in time and space domains that have not been covered until now (short term forecasting at a regional scale). It will produce a completely new type of forecasts and the usefulness of such data for the emergency services for their real-time decision making will be assessed within the project. Beyond the direct operational objectives, this project aims at demonstrating, on a specific application (the now-casting of road submersions), the possibilities and also the limits and hence the needed improvements of tools that are still underused: radar quantitative precipitation estimates but also precipitation now-castings, distributed rainfall-runoff models, and the recent knowledge acquired on flash-floods consequence evaluation as well as event management.

  14. Statistical forecasting of repetitious dome failures during the waning eruption of Redoubt Volcano, Alaska, February-April 1990

    USGS Publications Warehouse

    Page, R.A.; Lahr, J.C.; Chouet, B.A.; Power, J.A.; Stephens, C.D.

    1994-01-01

    The waning phase of the 1989-1990 eruption of Redoubt Volcano in the Cook Inlet region of south-central Alaska comprised a quasi-regular pattern of repetitious dome growth and destruction that lasted from February 15 to late April 1990. The dome failures produced ash plumes hazardous to airline traffic. In response to this hazard, the Alaska Volcano Observatory sought to forecast these ash-producing events using two approaches. One approach built on early successes in issuing warnings before major eruptions on December 14, 1989 and January 2, 1990. These warnings were based largely on changes in seismic activity related to the occurrence of precursory swarms of long-period seismic events. The search for precursory swarms of long-period seismicity was continued through the waning phase of the eruption and led to warnings before tephra eruptions on March 23 and April 6. The observed regularity of dome failures after February 15 suggested that a statistical forecasting method based on a constant-rate failure model might also be successful. The first statistical forecast was issued on March 16 after seven events had occurred, at an average interval of 4.5 days. At this time, the interval between dome failures abruptly lengthened. Accordingly, the forecast was unsuccessful and further forecasting was suspended until the regularity of subsequent failures could be confirmed. Statistical forecasting resumed on April 12, after four dome failure episodes separated by an average of 7.8 days. One dome failure (April 15) was successfully forecast using a 70% confidence window, and a second event (April 21) was narrowly missed before the end of the activity. The cessation of dome failures after April 21 resulted in a concluding false alarm. Although forecasting success during the eruption was limited, retrospective analysis shows that early and consistent application of the statistical method using a constant-rate failure model and a 90% confidence window could have yielded five successful forecasts and two false alarms; no events would have been missed. On closer examination, the intervals between successive dome failures are not uniform but tend to increase with time. This increase attests to the continuous, slowly decreasing supply of magma to the surface vent during the waning phase of the eruption. The domes formed in a precarious position in a breach in the summit crater rim where they were susceptible to gravitational collapse. The instability of the February 15-April 21 domes relative to the earlier domes is attributed to reaming the lip of the vent by a laterally directed explosion during the major dome-destroying eruption of February 15, a process which would leave a less secure foundation for subsequent domes. ?? 1994.

  15. The future of volcanic ash-aircraft interactions from technical and policy perspectives

    NASA Astrophysics Data System (ADS)

    Casadevall, T. J.; Guffanti, M.

    2010-12-01

    Since the advent of jet-powered flight in the 1960s, the threat of volcanic ash to aviation operations has become widely recognized and the mitigation of this threat has received concerted international attention. At the same time the susceptibility to operational disruption has grown. Technical improvements to airframes, engines, and avionic systems have been made in response to the need for improved fuel efficiency and the demand for increased capacity for passenger and freight traffic. Operational demands have resulted in the growth of extended overseas flight operations (ETOPS), increased flight frequency on air traffic routes, and closer spacing of aircraft on heavily traveled routes. The net result has been great advances in flight efficiency, but also increased susceptibility to flight disruption, especially in heavily traveled regions such as North Atlantic-Europe, North America, and the North Pacific. Advances in ash avoidance procedures, pilot and air manager training, and in detection of ash-related damage and maintenance of aircraft and engines have been spurred by noteworthy eruptions such as Galunggung, Indonesia, 1982; Redoubt, Alaska, 1989-1990; and Pinatubo, Philippines, 1991. Comparable advances have been made in the detection and tracking of volcanic ash clouds using satellite-based remote sensing and numerical trajectory forecast models. Following the April 2010 eruption of Eyjafjallajökull volcano, Iceland, the global aviation community again focused attention on the issue of safe air operations in airspace affected by volcanic ash. The enormous global disruption to air traffic in the weeks after the Eyjafjallajökull eruption has placed added emphasis for the global air traffic management system as well as on the equipment manufacturers to reevaluate air operations in ash-affected airspace. Under the leadership of the International Civil Aviation Organization and the World Meteorological Organization, efforts are being made to address this growth in the risks facing aviation operation owing to volcanic ash hazard (http://www2.icao.int/en/anb/met-aim/met/ivatf/Documents/Final.Alltext.pdf) Modifications of international procedures for air traffic management, a new assessment of equipment vulnerability, and efforts to detect and to more precisely forecast the distribution and concentration of volcanic ash are underway. These efforts will result in modification and updating of current practices for advising and warning pilots and airspace managers about volcanic ash, and also in better understandings of the threat volcanic ash presents to aviation operations. While technical and policy changes will help improve flight safety, there continues to be a role for earth scientists to work with the aviation community to improve monitoring of volcanoes, especially in remote regions, and in understanding of explosive volcanic processes. A paramount need continues for improved communications amongst all of the scientific and technical parties to address and successfully mitigate the risks of volcanic ash to aviation operations.

  16. A novel air quality analysis and prediction system for São Paulo, Brazil to support decision-making

    NASA Astrophysics Data System (ADS)

    Hoshyaripour, Gholam Ali; Brasseur, Guy; Andrade, Maria Fatima; Gavidia-Calderón, Mario; Bouarar, Idir

    2016-04-01

    The extensive economic development and urbanization in southeastern Brazil (SEB) in recent decades have notably degraded the air quality with adverse impacts on human health. Since the Metropolitan Area of São Paulo (MASP) accommodates the majority of the economic growth in SEB, it overwhelmingly suffers from the air pollution. Consequently, there is a strong demand for developing ever-better assessment mechanisms to monitor the air quality and to assist the decision makers to mitigate the air pollution in MASP. Here we present the results of an air quality modeling system designed for SEB with focuses on MASP. The Weather Research and Forecast model with Chemistry (WRF-Chem) is used considering the anthropogenic, biomass-burning and biogenic emissions within a 1000×1500 km domain with resolution of 10 km. FINN and MEGAN are used for the biomass-burning and biogenic emissions, respectively. For the anthropogenic emissions we use a local bottom-up inventory for the transport sector and the HTAPv2 global inventory for all other sectors. The bottom-up inventory accounts for the traffic patterns, vehicle types and their emission factors in the area and thus could be used to evaluate the effect of changes in these parameters on air quality in MASP. The model outputs are compered to the satellite and ground-based observations for O3 and NOx. The results show that using the bottom-up or top-down inventories individually can result in a huge deviation between the predictions and observations. On the other hand, combining the inventories significantly enhances the forecast accuracy. It also provides a powerful tool to quantify the effects of traffic and vehicle emission policies on air quality in MASP.

  17. Analysis of potential diverted of passenger car to the new toll road (case study: Cileunyi - Sumedang, West Java)

    NASA Astrophysics Data System (ADS)

    Prahara, Eduardi; Suangga, Made; Lutfi Ansori, Ahmad

    2017-12-01

    This study aims to determine of potential of passenger car divert from national road to on-construction Cisumdawu Toll Road. The study was conducted by traffic count survey and followed by a roadside interview survey. Stated Preference method was used in order to analyse trip forecasting value. Mode choice model of new trip mode plans (Cisumdawu Toll Road) and current intercity road for Cileunyi - Sumedang is (UJT -UJR ) = 0.1079-0.507726x 1-0.8953764x 2, while Sumedang - Cileunyi is (UJT -UJR ) = 0.0790-0.301341x 1-0.548446x 2. Multiple linear regression analysis was used to obtain the forecasting of private vehicle that diverts to the new toll road (Cisumdawu Toll Road). Trip characteristics such as trip origin and destination, types of trips, occupations, salary, and others become a motive for respondents to choose a new trip mode. Results of the new trip mode forecasting that prefer to divert to the toll road in terms of the value of cost and time for Cileunyi - Sumedang are 74.11% and 86.62% respectively, while for Sumedang - Cileunyi are 69.60% and 76.48% respectively. These results are relatively high compare to toll planning document. The impact of this results can be determined such as lower overall fuel consumption, lower pollution and more important is the maintenance cost of national road will be decrease.

  18. Road safety forecasts in five European countries using structural time series models.

    PubMed

    Antoniou, Constantinos; Papadimitriou, Eleonora; Yannis, George

    2014-01-01

    Modeling road safety development is a complex task and needs to consider both the quantifiable impact of specific parameters as well as the underlying trends that cannot always be measured or observed. The objective of this research is to apply structural time series models for obtaining reliable medium- to long-term forecasts of road traffic fatality risk using data from 5 countries with different characteristics from all over Europe (Cyprus, Greece, Hungary, Norway, and Switzerland). Two structural time series models are considered: (1) the local linear trend model and the (2) latent risk time series model. Furthermore, a structured decision tree for the selection of the applicable model for each situation (developed within the Road Safety Data, Collection, Transfer and Analysis [DaCoTA] research project, cofunded by the European Commission) is outlined. First, the fatality and exposure data that are used for the development of the models are presented and explored. Then, the modeling process is presented, including the model selection process, introduction of intervention variables, and development of mobility scenarios. The forecasts using the developed models appear to be realistic and within acceptable confidence intervals. The proposed methodology is proved to be very efficient for handling different cases of data availability and quality, providing an appropriate alternative from the family of structural time series models in each country. A concluding section providing perspectives and directions for future research is presented.

  19. Environmental consequences of Pollution and its Impact on earth's surface climate Using Geospatial Technology

    NASA Astrophysics Data System (ADS)

    Kumar, Amit

    2016-07-01

    Modern transportation is an indispensable ingredient for development, allowing the pressure group of labor, supplies and goods, and enabling general public to access key resources and services. Climate change is a most important threat to sustainable development in any developing or developed country. Urban air pollution is on the rise, due to rapid economic and inhabitants growth and an increase in motorization. Modern transport is fundamental for improvement, allowing the movement of goods and enabling general public to access key resources and services. Travel today is relatively faster and people across the world are travelling more than ever before. Its stipulate regarding forecast is an indispensable part of transportation development in order to evaluate future needs of an urban area. Over increasing traffic concentration posed continued threat to ambient air quality and responsible for producing agents of physical condition hazards. Geospatial technology provides the smartest approach to resolve these inconvenience as it can cover a large area in a fraction of time. The research work focuses on the recognition of traffic intensities with increasing of SO2, NO2 and noise level considered at particular traffic sites in the Varanasi, Uttar Pradesh, India. SO2, NO2 and Noise levels recorded in the city, are much higher than the permissible level and are likely to causes associated health and psychological illnesses to nearby inhabitant.

  20. Association Between Media Dose, Ad Tagging, and Changes in Web Traffic for a National Tobacco Education Campaign: A Market-Level Longitudinal Study

    PubMed Central

    Davis, Kevin C; Patel, Deesha; Rodes, Robert; Beistle, Diane

    2016-01-01

    Background In 2012, the US Centers for Disease Control and Prevention (CDC) launched Tips From Former Smokers (Tips), the first federally funded national tobacco education campaign. In 2013, a follow-up Tips campaign aired on national cable television networks, radio, and other channels, with supporting digital advertising to drive traffic to the Tips campaign website. Objective The objective of this study was to use geographic and temporal variability in 2013 Tips campaign television media doses and ad tagging to evaluate changes in traffic to the campaign website in response to specific doses of campaign media. Methods Linear regression models were used to estimate the dose-response relationship between weekly market-level television gross rating points (GRPs) and weekly Web traffic to the Tips campaign website. This relationship was measured using unique visitors, total visits, and page views as outcomes. Ad GRP effects were estimated separately for ads tagged with the Tips campaign website URL and 1-800-QUIT-NOW. Results In the average media market, an increase of 100 television GRPs per week for ads tagged with the Tips campaign website URL was associated with an increase of 650 unique visitors (P<.001), 769 total visits (P<.001), and 1255 total page views (P<.001) per week. The associations between GRPs for ads tagged with 1-800-QUIT-NOW and each Web traffic measure were also statistically significant (P<.001), but smaller in magnitude. Conclusions Based on these findings, we estimate that the 16-week 2013 Tips television campaign generated approximately 660,000 unique visitors, 900,000 total visits, and 1,390,000 page views for the Tips campaign website. These findings can help campaign planners forecast the likely impact of targeted advertising efforts on consumers’ use of campaign-specific websites. PMID:26887959

  1. State-space based analysis and forecasting of macroscopic road safety trends in Greece.

    PubMed

    Antoniou, Constantinos; Yannis, George

    2013-11-01

    In this paper, macroscopic road safety trends in Greece are analyzed using state-space models and data for 52 years (1960-2011). Seemingly unrelated time series equations (SUTSE) models are developed first, followed by richer latent risk time-series (LRT) models. As reliable estimates of vehicle-kilometers are not available for Greece, the number of vehicles in circulation is used as a proxy to the exposure. Alternative considered models are presented and discussed, including diagnostics for the assessment of their model quality and recommendations for further enrichment of this model. Important interventions were incorporated in the models developed (1986 financial crisis, 1991 old-car exchange scheme, 1996 new road fatality definition) and found statistically significant. Furthermore, the forecasting results using data up to 2008 were compared with final actual data (2009-2011) indicating that the models perform properly, even in unusual situations, like the current strong financial crisis in Greece. Forecasting results up to 2020 are also presented and compared with the forecasts of a model that explicitly considers the currently on-going recession. Modeling the recession, and assuming that it will end by 2013, results in more reasonable estimates of risk and vehicle-kilometers for the 2020 horizon. This research demonstrates the benefits of using advanced state-space modeling techniques for modeling macroscopic road safety trends, such as allowing the explicit modeling of interventions. The challenges associated with the application of such state-of-the-art models for macroscopic phenomena, such as traffic fatalities in a region or country, are also highlighted. Furthermore, it is demonstrated that it is possible to apply such complex models using the relatively short time-series that are available in macroscopic road safety analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. Communications payload concepts for geostationary facilities

    NASA Technical Reports Server (NTRS)

    Poley, William A.; Lekan, Jack

    1987-01-01

    Summarized and compared are the major results of two NASA sponsored studies that defined potential communication payload concepts to meet the satellite traffic forecast for the turn of the century for the continental US and Region 2 of the International Telecommunications Union. The studies were performed by the Ford Aerospace and Communications Corporation and RCA Astro-Electronics (now GE-RCA Astro-Space Division). Future scenarios of aggregations of communications services are presented. Payload concepts are developed and defined in detail for nine of the scenarios. Payload costs and critical technologies per payload are also presented. Finally the payload concepts are compared and the findings of the reports are discussed.

  3. The role of the airline transportation network in the prediction and predictability of global epidemics.

    PubMed

    Colizza, Vittoria; Barrat, Alain; Barthélemy, Marc; Vespignani, Alessandro

    2006-02-14

    The systematic study of large-scale networks has unveiled the ubiquitous presence of connectivity patterns characterized by large-scale heterogeneities and unbounded statistical fluctuations. These features affect dramatically the behavior of the diffusion processes occurring on networks, determining the ensuing statistical properties of their evolution pattern and dynamics. In this article, we present a stochastic computational framework for the forecast of global epidemics that considers the complete worldwide air travel infrastructure complemented with census population data. We address two basic issues in global epidemic modeling: (i) we study the role of the large scale properties of the airline transportation network in determining the global diffusion pattern of emerging diseases; and (ii) we evaluate the reliability of forecasts and outbreak scenarios with respect to the intrinsic stochasticity of disease transmission and traffic flows. To address these issues we define a set of quantitative measures able to characterize the level of heterogeneity and predictability of the epidemic pattern. These measures may be used for the analysis of containment policies and epidemic risk assessment.

  4. Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 2

    NASA Technical Reports Server (NTRS)

    Keitz, J. F.

    1982-01-01

    The impact of more timely and accurate weather data on airline flight planning with the emphasis on fuel savings is studied. This volume of the report discusses the results of Task 2 of the four major tasks included in the study. Task 2 compares various catagories of flight plans and flight tracking data produced by a simulation system developed for the Federal Aviation Administrations by SRI International. (Flight tracking data simulate actual flight tracks of all aircraft operating at a given time and provide for rerouting of flights as necessary to resolve traffic conflicts.) The comparisons of flight plans on the forecast to flight plans on the verifying analysis confirm Task 1 findings that wind speeds are generally underestimated. Comparisons involving flight tracking data indicate that actual fuel burn is always higher than planned, in either direction, and even when the same weather data set is used. Since the flight tracking model output results in more diversions than is known to be the case, it was concluded that there is an error in the flight tracking algorithm.

  5. Comparison of Selected Weather Translation Products

    NASA Technical Reports Server (NTRS)

    Kulkarni, Deepak

    2017-01-01

    Weather is a primary contributor to the air traffic delays within the National Airspace System (NAS). At present, it is the individual decision makers who use weather information and assess its operational impact in creating effective air traffic management solutions. As a result, the estimation of the impact of forecast weather and the quality of ATM response relies on the skill and experience level of the decision maker. FAA Weather-ATM working groups have developed a Weather-ATM integration framework that consists of weather collection, weather translation, ATM impact conversion and ATM decision support. Some weather translation measures have been developed for hypothetical operations such as decentralized free flight, whereas others are meant to be relevant in current operations. This paper does comparative study of two different weather translation products relevant in current operations and finds that these products have strong correlation with each other. Given inaccuracies in prediction of weather, these differences would not be expected to be of significance in statistical study of a large number of decisions made with a look-ahead time of two hours or more.

  6. Detection and Tracking of Volcanic Ash and SO2 and its Impact to Aviation

    NASA Astrophysics Data System (ADS)

    Osiensky, J.; Hall, T.

    2008-12-01

    The eruptions of Okmok and Kasatochi Volcanoes in August 2008 produced a combination of volcanic ash and SO2 (sulfur dioxide) that impacted aviation across Alaska and the North Pacific Region. The Anchorage Volcanic Ash Advisory Center (A-VAAC) worked closely with the Alaska Volcano Observatory (AVO) and Federal Aviation Administration (FAA) Air Route Traffic Control Center (ARTCC) to ensure that accurate and timely detection and forecast of the ash plume occurred. Volcanic ash poses a hazard to all forms of transportation, but has been shown to be especially dangerous to aviation. Even a small eruption with limited vertical extent to the ash cloud impacts aviation traffic. A significant eruption where the ash cloud penetrates the jet airways (greater than 20,000 feet) requires major re-routing of air traffic, or even the cancellation of flights to ensure the safety of the airways. The AAWU and the AVO have demonstrated substantial experience successfully tracking volcanic ash clouds during the past 15 years. The AAWU issues special aviation warnings for volcanic ash (Volcanic Ash SIGMETs (Significant Meteorological Information)) to warn aircraft of impending ash hazards. However, an additional potential hazard to aviation associated with volcanic eruptions is being examined. A Sulfur Dioxide (SO2) cloud was identified and tracked across the Aleutians, Gulf of Alaska, and eventually into the Lower 48 states. The size and coverage of the SO2 clouds from the Okmok and Kasatochi eruptions may be unprecedented. There are currently no requirements to advise, or warn for SO2 as a hazard to aviation. However, SO2 has been demonstrated as a marker for potential areas of lower concentration volcanic ash. Dispersion models, such as NOAAs HYSPLIT, that are used to track volcanic ash are currently not tuned to track gases such as SO2. SO2 may not be a direct hazard to aviation per se; However, SO2 mixed with water produces H2SO4 (sulfuric acid), and long term exposure to even low concentrations of sulfuric acid may lead to deterioration of airframe paint and acrylic aircraft windows as well as sulfate deposits in the engines. Airlines typically avoid SO2 clouds because these clouds often contain small amounts of ash as well. Relatively new OMI (Ozone Monitoring Instrument) data from the EOS-Aura satellite provides a much higher resolution depiction of the SO2 cloud; However, a major drawback to this capability is that the OMI sensor is located on a Polar Orbiter satellite (where the frequency of this data is sparse). Forecasters in Alaska typically receive only one pass per day from the OMI due to its orbital path. Additional research is needed to better define thresholds and impacts of volcanic ash and SO2 as it relates to aviation. More importantly this research must be transferred rapidly from the research community into forecast operations.

  7. Configuring calendar variation based on time series regression method for forecasting of monthly currency inflow and outflow in Central Java

    NASA Astrophysics Data System (ADS)

    Setiawan, Suhartono, Ahmad, Imam Safawi; Rahmawati, Noorgam Ika

    2015-12-01

    Bank Indonesia (BI) as the central bank of Republic Indonesiahas a single overarching objective to establish and maintain rupiah stability. This objective could be achieved by monitoring traffic of inflow and outflow money currency. Inflow and outflow are related to stock and distribution of money currency around Indonesia territory. It will effect of economic activities. Economic activities of Indonesia,as one of Moslem country, absolutely related to Islamic Calendar (lunar calendar), that different with Gregorian calendar. This research aims to forecast the inflow and outflow money currency of Representative Office (RO) of BI Semarang Central Java region. The results of the analysis shows that the characteristics of inflow and outflow money currency influenced by the effects of the calendar variations, that is the day of Eid al-Fitr (moslem holyday) as well as seasonal patterns. In addition, the period of a certain week during Eid al-Fitr also affect the increase of inflow and outflow money currency. The best model based on the value of the smallestRoot Mean Square Error (RMSE) for inflow data is ARIMA model. While the best model for predicting the outflow data in RO of BI Semarang is ARIMAX model or Time Series Regression, because both of them have the same model. The results forecast in a period of 2015 shows an increase of inflow money currency happened in August, while the increase in outflow money currency happened in July.

  8. COSMO-PAFOG: Three-dimensional fog forecasting with the high-resolution COSMO-model

    NASA Astrophysics Data System (ADS)

    Hacker, Maike; Bott, Andreas

    2017-04-01

    The presence of fog can have critical impact on shipping, aviation and road traffic increasing the risk of serious accidents. Besides these negative impacts of fog, in arid regions fog is explored as a supplementary source of water for human settlements. Thus the improvement of fog forecasts holds immense operational value. The aim of this study is the development of an efficient three-dimensional numerical fog forecast model based on a mesoscale weather prediction model for the application in the Namib region. The microphysical parametrization of the one-dimensional fog forecast model PAFOG (PArameterized FOG) is implemented in the three-dimensional nonhydrostatic mesoscale weather prediction model COSMO (COnsortium for Small-scale MOdeling) developed and maintained by the German Meteorological Service. Cloud water droplets are introduced in COSMO as prognostic variables, thus allowing a detailed description of droplet sedimentation. Furthermore, a visibility parametrization depending on the liquid water content and the droplet number concentration is implemented. The resulting fog forecast model COSMO-PAFOG is run with kilometer-scale horizontal resolution. In vertical direction, we use logarithmically equidistant layers with 45 of 80 layers in total located below 2000 m. Model results are compared to satellite observations and synoptic observations of the German Meteorological Service for a domain in the west of Germany, before the model is adapted to the geographical and climatological conditions in the Namib desert. COSMO-PAFOG is able to represent the horizontal structure of fog patches reasonably well. Especially small fog patches typical of radiation fog can be simulated in agreement with observations. Ground observations of temperature are also reproduced. Simulations without the PAFOG microphysics yield unrealistically high liquid water contents. This in turn reduces the radiative cooling of the ground, thus inhibiting nocturnal temperature decrease. The simulated visibility agrees with observations. However, fog tends to be dissolved earlier than in the observation. As a result of the investigated fog events, it is concluded that the three-dimensional fog forecast model COSMO-PAFOG is able to simulate these fog events in accordance with observations. After the successful application of COSMO-PAFOG for fog events in the west of Germany, model simulations will be performed for coastal desert fog in the Namib region.

  9. Evaluation of Improved Pushback Forecasts Derived from Airline Ground Operations Data

    NASA Technical Reports Server (NTRS)

    Carr, Francis; Theis, Georg; Feron, Eric; Clarke, John-Paul

    2003-01-01

    Accurate and timely predictions of airline pushbacks can potentially lead to improved performance of automated decision-support tools for airport surface traffic, thus reducing the variability and average duration of costly airline delays. One factor which affects the realization of these benefits is the level of uncertainty inherent in the turn processes. To characterize this inherent uncertainty, three techniques are developed for predicting time-to-go until pushback as a function of available ground-time; elapsed ground-time; and the status (not-started/in-progress/completed) of individual turn processes (cleaning, fueling, etc.). These techniques are tested against a large and detailed dataset covering approximately l0(exp 4) real-world turn operations obtained through collaboration with Deutsche Lufthansa AG. Even after the dataset is filtered to obtain a sample of turn operations with minimal uncertainty, the standard deviation of forecast error for all three techniques is lower-bounded away from zero, indicating that turn operations have a significant stochastic component. This lower-bound result shows that decision-support tools must be designed to incorporate robust mechanisms for coping with pushback demand stochasticity, rather than treating the pushback demand process as a known deterministic input.

  10. Review the number of accidents in Tehran over a two-year period and prediction of the number of events based on a time-series model

    PubMed Central

    Teymuri, Ghulam Heidar; Sadeghian, Marzieh; Kangavari, Mehdi; Asghari, Mehdi; Madrese, Elham; Abbasinia, Marzieh; Ahmadnezhad, Iman; Gholizadeh, Yavar

    2013-01-01

    Background: One of the significant dangers that threaten people’s lives is the increased risk of accidents. Annually, more than 1.3 million people die around the world as a result of accidents, and it has been estimated that approximately 300 deaths occur daily due to traffic accidents in the world with more than 50% of that number being people who were not even passengers in the cars. The aim of this study was to examine traffic accidents in Tehran and forecast the number of future accidents using a time-series model. Methods: The study was a cross-sectional study that was conducted in 2011. The sample population was all traffic accidents that caused death and physical injuries in Tehran in 2010 and 2011, as registered in the Tehran Emergency ward. The present study used Minitab 15 software to provide a description of accidents in Tehran for the specified time period as well as those that occurred during April 2012. Results: The results indicated that the average number of daily traffic accidents in Tehran in 2010 was 187 with a standard deviation of 83.6. In 2011, there was an average of 180 daily traffic accidents with a standard deviation of 39.5. One-way analysis of variance indicated that the average number of accidents in the city was different for different months of the year (P < 0.05). Most of the accidents occurred in March, July, August, and September. Thus, more accidents occurred in the summer than in the other seasons. The number of accidents was predicted based on an auto-regressive, moving average (ARMA) for April 2012. The number of accidents displayed a seasonal trend. The prediction of the number of accidents in the city during April of 2012 indicated that a total of 4,459 accidents would occur with mean of 149 accidents per day during these three months. Conclusion: The number of accidents in Tehran displayed a seasonal trend, and the number of accidents was different for different seasons of the year. PMID:26120405

  11. Emission inventories for ships in the Arctic based on satellite sampled AIS data

    NASA Astrophysics Data System (ADS)

    Christensen, J. H.; Winther, M.; Plejdrup, M. S.; Ravn, E. S.; Eriksson, O. M.; Kristensen, H. O.

    2013-12-01

    Emissions from ships inside Arctic are an important source of the Arctic pollution as e.g. SO2, NOx and Black Carbon (BC). This paper presents a detailed BC, NOx and SO2 emission inventory for ships in the Arctic for the year 2012 based on satellite AIS data, ship engine power functions and technology stratified emission factors. Emission projections are presented for the years 2020, 2030 and 2050 combined with emission from polar diversion routes as given by Corbett et al. (2010). Furthermore the Danish Eulerian Hemispheric Model (Christensen, 1997; Brandt et al., 2012), which is 3-d Chemical Transport Model covering the Northern hemisphere was use to study the transport of BC, SO2 and O3 and estimate BC deposition results in order to study then current and future contribution from Arctic ship traffics to atmospheric concentrations and deposition of pollutants in the Arctic. In 2012, the largest emission contributions of Artic ships emissions are from fishing ships (45% for BC, 38% for NOx and 23% for SO2) followed by passenger ships (20%, 17%, 25%), tankers (9%, 13%, 15%), general cargo (8%, 11%, 12%) and container ships (5%, 7%, 8%). Without diverted traffic from 2012 to 2050 the total BC, NOx and SO2 emissions are expected to change by 16 %, -32 % and -63 %, respectively. For the year 2012 the average calculated contributions for ships of BC, SO, and O3 concentrations and BC deposition become low and similar for the emissions projections without diverted traffic of the years 2020, 2030 and 2050, but with diverted traffic the contributions for ships to the BC, SO, and O3 concentrations and BC deposition becomes significantly higher especially for the year 2050 and especially during the summer season over the areas, where the diverted traffic are assumed to occur. These high forecasted values for BC sea-ice deposition close to the Polar routes are of main concern due to decreases in the albedo which in turn enhances the melting of sea-ice.

  12. Risk-Hedged Approach for Re-Routing Air Traffic Under Weather Uncertainty

    NASA Technical Reports Server (NTRS)

    Sadovsky, Alexander V.; Bilimoria, Karl D.

    2016-01-01

    This presentation corresponds to: our paper explores a new risk-hedged approach for re-routing air traffic around forecast convective weather. In this work, flying through a more likely weather instantiation is considered to pose a higher level of risk. Current operational practice strategically plans re-routes to avoid only the most likely (highest risk) weather instantiation, and then tactically makes any necessary adjustments as the weather evolves. The risk-hedged approach strategically plans re-routes by minimizing the risk-adjusted path length, incorporating multiple possible weather instantiations with associated likelihoods (risks). The resulting model is transparent and is readily analyzed for realism and treated with well-understood shortest-path algorithms. Risk-hedged re-routes are computed for some example weather instantiations. The main result is that in some scenarios, relative to an operational-practice proxy solution, the risk-hedged solution provides the benefits of lower risk as well as shorter path length. In other scenarios, the benefits of the risk-hedged solution are ambiguous, because the solution is characterized by a tradeoff between risk and path length. The risk-hedged solution can be executed in those scenarios where it provides a clear benefit over current operational practice.

  13. Predictability Analysis of PM10 Concentrations in Budapest

    NASA Astrophysics Data System (ADS)

    Ferenczi, Zita

    2013-04-01

    Climate, weather and air quality may have harmful effects on human health and environment. Over the past few hundred years we had to face the changes in climate in parallel with the changes in air quality. These observed changes in climate, weather and air quality continuously interact with each other: pollutants are changing the climate, thus changing the weather, but climate also has impacts on air quality. The increasing number of extreme weather situations may be a result of climate change, which could create favourable conditions for rising of pollutant concentrations. Air quality in Budapest is determined by domestic and traffic emissions combined with the meteorological conditions. In some cases, the effect of long-range transport could also be essential. While the time variability of the industrial and traffic emissions is not significant, the domestic emissions increase in winter season. In recent years, PM10 episodes have caused the most critical air quality problems in Budapest, especially in winter. In Budapest, an air quality network of 11 stations detects the concentration values of different pollutants hourly. The Hungarian Meteorological Service has developed an air quality prediction model system for the area of Budapest. The system forecasts the concentration of air pollutants (PM10, NO2, SO2 and O3) for two days in advance. In this work we used meteorological parameters and PM10 data detected by the stations of the air quality network, as well as the forecasted PM10 values of the air quality prediction model system. In this work we present the evaluation of PM10 predictions in the last two years and the most important meteorological parameters affecting PM10 concentration. The results of this analysis determine the effect of the meteorological parameters and the emission of aerosol particles on the PM10 concentration values as well as the limits of this prediction system.

  14. A Bayesian method to rank different model forecasts of the same volcanic ash cloud: Chapter 24

    USGS Publications Warehouse

    Denlinger, Roger P.; Webley, P.; Mastin, Larry G.; Schwaiger, Hans F.

    2012-01-01

    Volcanic eruptions often spew fine ash high into the atmosphere, where it is carried downwind, forming long ash clouds that disrupt air traffic and pose a hazard to air travel. To mitigate such hazards, the community studying ash hazards must assess risk of ash ingestion for any flight path and provide robust and accurate forecasts of volcanic ash dispersal. We provide a quantitative and objective method to evaluate the efficacy of ash dispersal estimates from different models, using Bayes theorem to assess the predictions that each model makes about ash dispersal. We incorporate model and measurement uncertainty and produce a posterior probability for model input parameters. The integral of the posterior over all possible combinations of model inputs determines the evidence for each model and is used to compare models. We compare two different types of transport models, an Eulerian model (Ash3d) and a Langrangian model (PUFF), as applied to the 2010 eruptions of Eyjafjallajökull volcano in Iceland. The evidence for each model benefits from common physical characteristics of ash dispersal from an eruption column and provides a measure of how well each model forecasts cloud transport. Given the complexity of the wind fields, we find that the differences between these models depend upon the differences in the way the models disperse ash into the wind from the source plume. With continued observation, the accuracy of the estimates made by each model increases, increasing the efficacy of each model’s ability to simulate ash dispersal.

  15. An emission processing system for air quality modelling in the Mexico City metropolitan area: Evaluation and comparison of the MOBILE6.2-Mexico and MOVES-Mexico traffic emissions.

    PubMed

    Guevara, M; Tena, C; Soret, A; Serradell, K; Guzmán, D; Retama, A; Camacho, P; Jaimes-Palomera, M; Mediavilla, A

    2017-04-15

    This article describes the High-Elective Resolution Modelling Emission System for Mexico (HERMES-Mex) model, an emission processing tool developed to transform the official Mexico City Metropolitan Area (MCMA) emission inventory into hourly, gridded (up to 1km 2 ) and speciated emissions used to drive mesoscale air quality simulations with the Community Multi-scale Air Quality (CMAQ) model. The methods and ancillary information used for the spatial and temporal disaggregation and speciation of the emissions are presented and discussed. The resulting emission system is evaluated, and a case study on CO, NO 2 , O 3 , VOC and PM 2.5 concentrations is conducted to demonstrate its applicability. Moreover, resulting traffic emissions from the Mobile Source Emission Factor Model for Mexico (MOBILE6.2-Mexico) and the MOtor Vehicle Emission Simulator for Mexico (MOVES-Mexico) models are integrated in the tool to assess and compare their performance. NO x and VOC total emissions modelled are reduced by 37% and 26% in the MCMA when replacing MOBILE6.2-Mexico for MOVES-Mexico traffic emissions. In terms of air quality, the system composed by the Weather Research and Forecasting model (WRF) coupled with the HERMES-Mex and CMAQ models properly reproduces the pollutant levels and patterns measured in the MCMA. The system's performance clearly improves in urban stations with a strong influence of traffic sources when applying MOVES-Mexico emissions. Despite reducing estimations of modelled precursor emissions, O 3 peak averages are increased in the MCMA core urban area (up to 30ppb) when using MOVES-Mexico mobile emissions due to its VOC-limited regime, while concentrations in the surrounding suburban/rural areas decrease or increase depending on the meteorological conditions of the day. The results obtained suggest that the HERMES-Mex model can be used to provide model-ready emissions for air quality modelling in the MCMA. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Space Station needs, attributes and architectural options. Volume 2, book 1, part 3: Manned Space Station relevance to commercial telecommunications satellites

    NASA Technical Reports Server (NTRS)

    1983-01-01

    A document containing a forecast of satellite traffic and revelant technology trends to the year 2000 was prepared which includes those space station capabilities and characteristics that should be provided to make the station useful to commercial satellite owners. The document was circulated to key representative organizations within the commercial telecommunications satellite and related communities of interest, including spacecraft manufacturers, commercial satellite owners, communications carriers, networks and risk insurers. The prospectus document is presented as well as the transmittal letter and the mailing list of the people and companies that were asked to review it. Key commercial telecommunications comments are summarized the actual response letters from the industry are included.

  17. The 30/20 GHz fixed communications systems service demand assessment. Volume 1: Executive summary

    NASA Technical Reports Server (NTRS)

    Gamble, R. B.; Seltzer, H. R.; Speter, K. M.; Westheimer, M.

    1979-01-01

    Demand for telecommunications services is forecasted for the period 1980-2000, with particular reference to that portion of the demand associated with satellite communications. Overall demand for telecommunications is predicted to increase by a factor of five over the period studied and the satellite portion of demand will increase even more rapidly. Traffic demand is separately estimated for voice, video, and data services and is also described as a function of distance traveled and city size. The satellite component of projected demand is compared with the capacity available in the C and Ku satellite bands and it is projected that new satellite technology and the implementation of Ka band transmission will be needed in the decade of the 1990's.

  18. Modeling Weather Impact on Ground Delay Programs

    NASA Technical Reports Server (NTRS)

    Wang, Yao; Kulkarni, Deepak

    2011-01-01

    Scheduled arriving aircraft demand may exceed airport arrival capacity when there is abnormal weather at an airport. In such situations, Federal Aviation Administration (FAA) institutes ground-delay programs (GDP) to delay flights before they depart from their originating airports. Efficient GDP planning depends on the accuracy of prediction of airport capacity and demand in the presence of uncertainties in weather forecast. This paper presents a study of the impact of dynamic airport surface weather on GDPs. Using the National Traffic Management Log, effect of weather conditions on the characteristics of GDP events at selected busy airports is investigated. Two machine learning methods are used to generate models that map the airport operational conditions and weather information to issued GDP parameters and results of validation tests are described.

  19. Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

    NASA Technical Reports Server (NTRS)

    Chatterji, Gano B.; Gyarfas, Brett; Chan, William N.; Meyn, Larry A.

    2006-01-01

    Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

  20. A multidisciplinary system for monitoring and forecasting Etna volcanic plumes

    NASA Astrophysics Data System (ADS)

    Coltelli, Mauro; Prestifilippo, Michele; Spata, Gaetano; Scollo, Simona; Andronico, Daniele

    2010-05-01

    One of the most active volcanoes in the world is Mt. Etna, in Italy, characterized by frequent explosive activity from the central craters and from fractures opened along the volcano flanks which, during the last years, caused several damages to aviation and forced the closure of the Catania International Airport. To give precise warning to the aviation authorities and air traffic controller and to assist the work of VAACs, a novel system for monitoring and forecasting Etna volcanic plumes, was developed at the Istituto Nazionale di Geofisica e Vulcanologia, sezione di Catania, the managing institution for the surveillance of Etna volcano. Monitoring is carried out using multispectral infrared measurements from the Spin Enhanced Visible and Infrared Imager (SEVIRI) on board the Meteosat Second Generation geosynchronous satellite able to track the volcanic plume with a high time resolution, visual and thermal cameras used to monitor the explosive activity, three continuous wave X-band disdrometers which detect ash dispersal and fallout, sounding balloons used to evaluate the atmospheric fields, and finally field data collected after the end of the eruptive event needed to extrapolate important features of explosive activity. Forecasting is carried out daily using automatic procedures which download weather forecast data obtained by meteorological mesoscale models from the Italian Air Force national Meteorological Office and from the hydrometeorological service of ARPA-SIM; run four different tephra dispersal models using input parameters obtained by the analysis of the deposits collected after few hours since the eruptive event similar to 22 July 1998, 21-24 July 2001 and 2002-03 Etna eruptions; plot hazard maps on ground and in air and finally publish them on a web-site dedicated to the Italian Civil Protection. The system has been already tested successfully during several explosive events occurring at Etna in 2006, 2007 and 2008. These events produced eruption columns high up to several kilometers above sea level and, on the basis of parameters such as mass eruption rate and total grain-size distributions, showed different explosive style. The monitoring and forecasting system is going on developing through the installation of new instruments able to detect different features of the volcanic plumes (e.g. the dispersal and sedimentation processes) in order to reduce the uncertainty of the input parameters used in the modeling. This is crucial to perform a reliable forecasting. We show that multidisciplinary approaches can really give useful information on the presence of volcanic ash and consequently to prevent damages and airport disruptions.

  1. A numerical forecast model for road meteorology

    NASA Astrophysics Data System (ADS)

    Meng, Chunlei

    2017-05-01

    A fine-scale numerical model for road surface parameters prediction (BJ-ROME) is developed based on the Common Land Model. The model is validated using in situ observation data measured by the ROSA road weather stations of Vaisala Company, Finland. BJ-ROME not only takes into account road surface factors, such as imperviousness, relatively low albedo, high heat capacity, and high heat conductivity, but also considers the influence of urban anthropogenic heat, impervious surface evaporation, and urban land-use/land-cover changes. The forecast time span and the update interval of BJ-ROME in vocational operation are 24 and 3 h, respectively. The validation results indicate that BJ-ROME can successfully simulate the diurnal variation of road surface temperature both under clear-sky and rainfall conditions. BJ-ROME can simulate road water and snow depth well if the artificial removing was considered. Road surface energy balance in rainy days is quite different from that in clear-sky conditions. Road evaporation could not be neglected in road surface water cycle research. The results of sensitivity analysis show solar radiation correction coefficient, asphalt depth, and asphalt heat conductivity are important parameters in road interface temperatures simulation. The prediction results could be used as a reference of maintenance decision support system to mitigate the traffic jam and urban water logging especially in large cities.

  2. Induced seismicity closed-form traffic light system for actuarial decision-making during deep fluid injections.

    PubMed

    Mignan, A; Broccardo, M; Wiemer, S; Giardini, D

    2017-10-19

    The rise in the frequency of anthropogenic earthquakes due to deep fluid injections is posing serious economic, societal, and legal challenges to many geo-energy and waste-disposal projects. Existing tools to assess such problems are still inherently heuristic and mostly based on expert elicitation (so-called clinical judgment). We propose, as a complementary approach, an adaptive traffic light system (ATLS) that is function of a statistical model of induced seismicity. It offers an actuarial judgement of the risk, which is based on a mapping between earthquake magnitude and risk. Using data from six underground reservoir stimulation experiments, mostly from Enhanced Geothermal Systems, we illustrate how such a data-driven adaptive forecasting system could guarantee a risk-based safety target. The proposed model, which includes a linear relationship between seismicity rate and flow rate, as well as a normal diffusion process for post-injection, is first confirmed to be representative of the data. Being integrable, the model yields a closed-form ATLS solution that is both transparent and robust. Although simulations verify that the safety target is consistently ensured when the ATLS is applied, the model from which simulations are generated is validated on a limited dataset, hence still requiring further tests in additional fluid injection environments.

  3. US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 1: Executive summary

    NASA Technical Reports Server (NTRS)

    1986-01-01

    Over the past two decades, fiber optics has emerged as a highly practical and cost-efficient communications technology. Its competitiveness vis-a-vis other transmission media, especially satellite, has become a critical question. This report studies the likely evolution and application of fiber optic networks in the United States to the end of the century. The outlook for the technology of fiber systems is assessed and forecast, scenarios of the evolution of fiber optic network development are constructed, and costs to provide service are determined and examined parametrically as a function of network size and traffic carried. Volume 1 consists of the Executive Summary. Volume 2 focuses on fiber optic technology and long distance fiber optic networks. Volume 3 develops a traffic and financial model of a nationwide long distance transmission network. Among the study's most important conclusions are: revenue requirements per circuit for LATA-to-LATA fiber optic links are less than one cent per call minute; multiplex equipment, which is likely to be required in any competing system, is the largest contributor to circuit costs; the potential capacity of fiber optic cable is very large and as yet undefined; and fiber optic transmission combined with other network optimization schemes can lead to even lower costs than those identified in this study.

  4. Advancing Environmental Prediction Capabilities for the Polar Regions and Beyond during The Year of Polar Prediction

    NASA Astrophysics Data System (ADS)

    Werner, Kirstin; Goessling, Helge; Hoke, Winfried; Kirchhoff, Katharina; Jung, Thomas

    2017-04-01

    Environmental changes in polar regions open up new opportunities for economic and societal operations such as vessel traffic related to scientific, fishery and tourism activities, and in the case of the Arctic also enhanced resource development. The availability of current and accurate weather and environmental information and forecasts will therefore play an increasingly important role in aiding risk reduction and safety management around the poles. The Year of Polar Prediction (YOPP) has been established by the World Meteorological Organization's World Weather Research Programme as the key activity of the ten-year Polar Prediction Project (PPP; see more on www.polarprediction.net). YOPP is an internationally coordinated initiative to significantly advance our environmental prediction capabilities for the polar regions and beyond, supporting improved weather and climate services. Scheduled to take place from mid-2017 to mid-2019, the YOPP core phase covers an extended period of intensive observing, modelling, prediction, verification, user-engagement and education activities in the Arctic and Antarctic, on a wide range of time scales from hours to seasons. The Year of Polar Prediction will entail periods of enhanced observational and modelling campaigns in both polar regions. With the purpose to close the gaps in the conventional polar observing systems in regions where the observation network is sparse, routine observations will be enhanced during Special Observing Periods for an extended period of time (several weeks) during YOPP. This will allow carrying out subsequent forecasting system experiments aimed at optimizing observing systems in the polar regions and providing insight into the impact of better polar observations on forecast skills in lower latitudes. With various activities and the involvement of a wide range of stakeholders, YOPP will contribute to the knowledge base needed to managing the opportunities and risks that come with polar climate change.

  5. An experimental study of summertime coastal fog and its inland penetration in Northern California

    NASA Astrophysics Data System (ADS)

    Lucena Kreppel Paes, P.; Torres, P.; Faloona, I. C.; Torregrosa, A.; Gultepe, I.

    2012-12-01

    The occurrence and continental inundation of marine stratocumulus and fog along the California Coast during summer has been linked to many environmental concerns including redwood ecosystem vitality, air traffic control, power grid load balancing, and radiatve climate forcing. An exploratory study was instigated this past summer at the Bodega Marine Laboratory and Pepperwood Preserve, a large nature reserve located 40 km inland in Sonoma County, in order to investigate fog formation, persistence, and penetration through the orographic gap in the Pacific coastal mountain range. Analysis of the synoptic patterns and in-situ meteorological observations, including visibility and boundary layer depth, are presented with the aim of improving fog forecasts and elucidating the principal physical parameters that control summertime fog formation and dissipation along the Northern California Coast.

  6. Design of an advanced flight planning system

    NASA Technical Reports Server (NTRS)

    Sorensen, J. A.; Goka, T.

    1985-01-01

    The demand for both fuel conservation and four-dimensional traffic management require that the preflight planning process be designed to account for advances in airborne flight management and weather forecasting. The steps and issues in designing such an advanced flight planning system are presented. Focus is placed on the different optimization options for generating the three-dimensional reference path. For the cruise phase, one can use predefined jet routes, direct routes based on a network of evenly spaced grid points, or a network where the grid points are existing navaid locations. Each choice has its own problem in determining an optimum solution. Finding the reference path is further complicated by choice of cruise altitude levels, use of a time-varying weather field, and requiring a fixed time-of-arrival (four-dimensional problem).

  7. Computationally-Efficient Minimum-Time Aircraft Routes in the Presence of Winds

    NASA Technical Reports Server (NTRS)

    Jardin, Matthew R.

    2004-01-01

    A computationally efficient algorithm for minimizing the flight time of an aircraft in a variable wind field has been invented. The algorithm, referred to as Neighboring Optimal Wind Routing (NOWR), is based upon neighboring-optimal-control (NOC) concepts and achieves minimum-time paths by adjusting aircraft heading according to wind conditions at an arbitrary number of wind measurement points along the flight route. The NOWR algorithm may either be used in a fast-time mode to compute minimum- time routes prior to flight, or may be used in a feedback mode to adjust aircraft heading in real-time. By traveling minimum-time routes instead of direct great-circle (direct) routes, flights across the United States can save an average of about 7 minutes, and as much as one hour of flight time during periods of strong jet-stream winds. The neighboring optimal routes computed via the NOWR technique have been shown to be within 1.5 percent of the absolute minimum-time routes for flights across the continental United States. On a typical 450-MHz Sun Ultra workstation, the NOWR algorithm produces complete minimum-time routes in less than 40 milliseconds. This corresponds to a rate of 25 optimal routes per second. The closest comparable optimization technique runs approximately 10 times slower. Airlines currently use various trial-and-error search techniques to determine which of a set of commonly traveled routes will minimize flight time. These algorithms are too computationally expensive for use in real-time systems, or in systems where many optimal routes need to be computed in a short amount of time. Instead of operating in real-time, airlines will typically plan a trajectory several hours in advance using wind forecasts. If winds change significantly from forecasts, the resulting flights will no longer be minimum-time. The need for a computationally efficient wind-optimal routing algorithm is even greater in the case of new air-traffic-control automation concepts. For air-traffic-control automation, thousands of wind-optimal routes may need to be computed and checked for conflicts in just a few minutes. These factors motivated the need for a more efficient wind-optimal routing algorithm.

  8. Environmental Information for the U.S. Next Generation Air Transportation System (NextGen)

    NASA Astrophysics Data System (ADS)

    Murray, J.; Miner, C.; Pace, D.; Minnis, P.; Mecikalski, J.; Feltz, W.; Johnson, D.; Iskendarian, H.; Haynes, J.

    2009-09-01

    It is estimated that weather is responsible for approximately 70% of all air traffic delays and cancellations in the United States. Annually, this produces an overall economic loss of nearly 40B. The FAA and NASA have determined that weather impacts and other environmental constraints on the U.S. National Airspace System (NAS) will increase to the point of system unsustainability unless the NAS is radically transformed. A Next Generation Air Transportation System (NextGen) is planned to accommodate the anticipated demand for increased system capacity and the super-density operations that this transformation will entail. The heart of the environmental information component that is being developed for NextGen will be a 4-dimensional data cube which will include a single authoritative source comprising probabilistic weather information for NextGen Air Traffic Management (ATM) systems. Aviation weather constraints and safety hazards typically comprise meso-scale, storm-scale and microscale observables that can significantly impact both terminal and enroute aviation operations. With these operational impacts in mind, functional and performance requirements for the NextGen weather system were established which require significant improvements in observation and forecasting capabilities. This will include satellite observations from geostationary and/or polar-orbiting hyperspectral sounders, multi-spectral imagers, lightning mappers, space weather monitors and other environmental observing systems. It will also require improved in situ and remotely sensed observations from ground-based and airborne systems. These observations will be used to better understand and to develop forecasting applications for convective weather, in-flight icing, turbulence, ceilings and visibility, volcanic ash, space weather and the environmental impacts of aviation. Cutting-edge collaborative research efforts and results from NASA, NOAA and the FAA which address these phenomena are summarized. In 2003, a Joint Planning and Development Office (JPDO) was established by public law to meet the significant challenges that NextGen presents. JPDO partners were chartered which include, but are not limited to, the Federal Aviation Administration (FAA), the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), the Department of Defense (DOD) and broad elements of academia and the aviation industry. This paper provides the aviation meteorology community with useful insight on salient NextGen environmental information requirements that have been developed by the JPDO Weather Working Group's Environmental Information Team. These efforts will help to define observation and forecast systems needed to support NextGen and to develop the operational applications for NextGen aviation weather information. Another major goal of this paper is to inform the international weather community of our research progress and plans for NextGen, to foster research collaboration with our colleagues, and to exchange information to maximize success of NextGen, SESAR and related initiatives world-wide.

  9. Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52)

    NASA Astrophysics Data System (ADS)

    Grewe, Volker; Tsati, Eleni; Mertens, Mariano; Frömming, Christine; Jöckel, Patrick

    2017-07-01

    Questions such as what is the contribution of road traffic emissions to climate change? or what is the impact of shipping emissions on local air quality? require a quantification of the contribution of specific emissions sectors to the concentration of radiatively active species and air-quality-related species, respectively. Here, we present a diagnostics package, implemented in the Modular Earth Submodel System (MESSy), which keeps track of the contribution of source categories (mainly emission sectors) to various concentrations. The diagnostics package is implemented as a submodel (TAGGING) of EMAC (European Centre for Medium-Range Weather Forecasts - Hamburg (ECHAM)/MESSy Atmospheric Chemistry). It determines the contributions of 10 different source categories to the concentration of ozone, nitrogen oxides, peroxyacytyl nitrate, carbon monoxide, non-methane hydrocarbons, hydroxyl, and hydroperoxyl radicals ( = tagged tracers). The source categories are mainly emission sectors and some other sources for completeness. As emission sectors, road traffic, shipping, air traffic, anthropogenic non-traffic, biogenic, biomass burning, and lightning are considered. The submodel obtains information on the chemical reaction rates, online emissions, such as lightning, and wash-out rates. It then solves differential equations for the contribution of a source category to each of the seven tracers. This diagnostics package does not feed back to any other part of the model. For the first time, it takes into account chemically competing effects: for example, the competition between NOx, CO, and non-methane hydrocarbons (NMHCs) in the production and destruction of ozone. We show that the results are in-line with results from other tagging schemes and provide plausibility checks for concentrations of trace gases, such as OH and HO2, which have not previously been tagged. The budgets of the tagged tracers, i.e. the contribution from individual source categories (mainly emission sectors) to, e.g., ozone, are only marginally sensitive to changes in model resolution, though the level of detail increases. A reduction in road traffic emissions by 5 % shows that road traffic global tropospheric ozone is reduced by 4 % only, because the net ozone productivity increases. This 4 % reduction in road traffic tropospheric ozone corresponds to a reduction in total tropospheric ozone by ≈ 0.3 %, which is compensated by an increase in tropospheric ozone from other sources by 0.1 %, resulting in a reduction in total tropospheric ozone of ≈ 0.2 %. This compensating effect compares well with previous findings. The computational costs of the TAGGING submodel are low with respect to computing time, but a large number of additional tracers are required. The advantage of the tagging scheme is that in one simulation and at every time step and grid point, information is available on the contribution of different emission sectors to the ozone budget, which then can be further used in upcoming studies to calculate the respective radiative forcing simultaneously.

  10. Battery cars on superconducting magnetically levitated carriers: One commuting solution

    NASA Technical Reports Server (NTRS)

    Briggs, B. Mike; Oman, Henry

    1992-01-01

    Commuting to work in an urban-suburban metropolitan environment is becoming an unpleasant time-wasting process. We applied the technology of communication management to this commuting problem. Communication management is a system-engineering tool that produced today's efficient telephone network. The resulting best commuting option is magnetically levitated carriers of two-passenger, battery-powered, personally-owned local-travel cars. A commuter drives a car to a nearby station, selects a destination, drives on a waiting carrier, and enters an accelerating ramp. A central computer selects an optimum 100 miles-per-hour trunk route, considering existing and forecast traffic; assigns the commuter a travel slot, and subsequently orders switching-station actions. The commuter uses the expensive facilities for only a few minutes during each trip. The cost of travel could be less than 6 cents per mile.

  11. Differing Air Traffic Controller Responses to Similar Trajectory Prediction Errors

    NASA Technical Reports Server (NTRS)

    Mercer, Joey; Hunt-Espinosa, Sarah; Bienert, Nancy; Laraway, Sean

    2016-01-01

    A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASA's Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlanta's Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the study's trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 30-knot over-predictions and 30-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?

  12. Planning for growth in satellite systems - The Intelsat experience

    NASA Astrophysics Data System (ADS)

    Nadkarni, P.; Perillan, L.; Chasia, H.

    It is thought that the increase in conventional voice traffic will result primarily from growth on existing links rather than the establishment of new links. A steady growth of approximately 15% per annum is forecast over the next decade, for a requirement of more than 125,000 circuits, worldwide, by the early 1990s. It is noted that the transfer of services from a satellite to its successor is becoming increasingly complex with successive generations. Increases in the number of beams and beam interconnections, together with differences in coverages between successive satellites, have required totally new frequency plans and carrier assignments to be implemented as part of the operation transition. Attention is also given to the way that the investment in resources, technologies, and installed plant already in use exerts a strong influence on the alternatives for growth.

  13. Empirical Data Fusion for Convective Weather Hazard Nowcasting

    NASA Astrophysics Data System (ADS)

    Williams, J.; Ahijevych, D.; Steiner, M.; Dettling, S.

    2009-09-01

    This paper describes a statistical analysis approach to developing an automated convective weather hazard nowcast system suitable for use by aviation users in strategic route planning and air traffic management. The analysis makes use of numerical weather prediction model fields and radar, satellite, and lightning observations and derived features along with observed thunderstorm evolution data, which are aligned using radar-derived motion vectors. Using a dataset collected during the summers of 2007 and 2008 over the eastern U.S., the predictive contributions of the various potential predictor fields are analyzed for various spatial scales, lead-times and scenarios using a technique called random forests (RFs). A minimal, skillful set of predictors is selected for each scenario requiring distinct forecast logic, and RFs are used to construct an empirical probabilistic model for each. The resulting data fusion system, which ran in real-time at the National Center for Atmospheric Research during the summer of 2009, produces probabilistic and deterministic nowcasts of the convective weather hazard and assessments of the prediction uncertainty. The nowcasts' performance and results for several case studies are presented to demonstrate the value of this approach. This research has been funded by the U.S. Federal Aviation Administration to support the development of the Consolidated Storm Prediction for Aviation (CoSPA) system, which is intended to provide convective hazard nowcasts and forecasts for the U.S. Next Generation Air Transportation System (NextGen).

  14. The Use of OMPS Near Real Time Products in Volcanic Cloud Risk Mitigation and Smoke/Dust Air Quality Assessments

    NASA Astrophysics Data System (ADS)

    Seftor, C. J.; Krotkov, N. A.; McPeters, R. D.; Li, J. Y.; Durbin, P. B.

    2015-12-01

    Near real time (NRT) SO2 and aerosol index (AI) imagery from Aura's Ozone Monitoring Instrument (OMI) has proven invaluable in mitigating the risk posed to air traffic by SO2 and ash clouds from volcanic eruptions. The OMI products, generated as part of NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) NRT system and available through LANCE and both NOAA's NESDIS and ESA's Support to Aviation Control Service (SACS) portals, are used to monitor the current location of volcanic clouds and to provide input into Volcanic Ash (VA) advisory forecasts. NRT products have recently been developed using data from the Ozone Mapping and Profiler Suite onboard the Suomi NPP platform; they are currently being made available through the SACS portal and will shortly be incorporated into the LANCE NRT system. We will show examples of the use of OMPS NRT SO2 and AI imagery to monitor recent volcanic eruption events. We will also demonstrate the usefulness of OMPS AI imagery to detect and track dust storms and smoke from fires, and how this information can be used to forecast their impact on air quality in areas far removed from their source. Finally, we will show SO2 and AI imagery generated from our OMPS Direct Broadcast data to highlight the capability of our real time system.

  15. Air System Information Management

    NASA Technical Reports Server (NTRS)

    Filman, Robert E.

    2004-01-01

    I flew to Washington last week, a trip rich in distributed information management. Buying tickets, at the gate, in flight, landing and at the baggage claim, myriad messages about my reservation, the weather, our flight plans, gates, bags and so forth flew among a variety of travel agency, airline and Federal Aviation Administration (FAA) computers and personnel. By and large, each kind of information ran on a particular application, often specialized to own data formats and communications network. I went to Washington to attend an FAA meeting on System-Wide Information Management (SWIM) for the National Airspace System (NAS) (http://www.nasarchitecture.faa.gov/Tutorials/NAS101.cfm). NAS (and its information infrastructure, SWIM) is an attempt to bring greater regularity, efficiency and uniformity to the collection of stovepipe applications now used to manage air traffic. Current systems hold information about flight plans, flight trajectories, weather, air turbulence, current and forecast weather, radar summaries, hazardous condition warnings, airport and airspace capacity constraints, temporary flight restrictions, and so forth. Information moving among these stovepipe systems is usually mediated by people (for example, air traffic controllers) or single-purpose applications. People, whose intelligence is critical for difficult tasks and unusual circumstances, are not as efficient as computers for tasks that can be automated. Better information sharing can lead to higher system capacity, more efficient utilization and safer operations. Better information sharing through greater automation is possible though not necessarily easy.

  16. Network planning study of the metro-optical-network-oriented 3G application

    NASA Astrophysics Data System (ADS)

    Gong, Qian; Xu, Rong; Lin, Jin Tong

    2005-02-01

    To compare with the 2G mobile communication, 3G technologies can supply the perfect service scope and performance. 3G is the trend of the mobile communication. So now to build the transmission network, it is needed to consider how the transmission network to support the 3G applications. For the 3G network architecture, it include the 2 part: Utran access network and core network. So the metro optical network should consider how to build the network to adapt the 3G applications. Include the metro core and access layer. In the metro core, we should consider the network should evolved towards the Mesh architecture with ASON function to realize the fast protection and restoration, quick end-to-end service provision, and high capacity cross-connect matrix etc. In the access layer, the network should have the ability to access the 3G services such as ATM interface with IMA function. In addition, the traffic grooming should be provided to improve the bandwidth utility. In this paper, first we present the MCC network situation, the network planning model will be introduced. Then we present the topology architecture, node capacity and traffic forecast. At last, based on our analysis, we will give a total solution to MCC to build their metro optical network toward to the mesh network with the consideration of 3G services.

  17. Integrating Smart Health in the US Health Care System: Infodemiology Study of Asthma Monitoring in the Google Era

    PubMed Central

    Sampri, Alexia; Sypsa, Karla; Tsagarakis, Konstantinos P

    2018-01-01

    Background With the internet’s penetration and use constantly expanding, this vast amount of information can be employed in order to better assess issues in the US health care system. Google Trends, a popular tool in big data analytics, has been widely used in the past to examine interest in various medical and health-related topics and has shown great potential in forecastings, predictions, and nowcastings. As empirical relationships between online queries and human behavior have been shown to exist, a new opportunity to explore the behavior toward asthma—a common respiratory disease—is present. Objective This study aimed at forecasting the online behavior toward asthma and examined the correlations between queries and reported cases in order to explore the possibility of nowcasting asthma prevalence in the United States using online search traffic data. Methods Applying Holt-Winters exponential smoothing to Google Trends time series from 2004 to 2015 for the term “asthma,” forecasts for online queries at state and national levels are estimated from 2016 to 2020 and validated against available Google query data from January 2016 to June 2017. Correlations among yearly Google queries and between Google queries and reported asthma cases are examined. Results Our analysis shows that search queries exhibit seasonality within each year and the relationships between each 2 years’ queries are statistically significant (P<.05). Estimated forecasting models for a 5-year period (2016 through 2020) for Google queries are robust and validated against available data from January 2016 to June 2017. Significant correlations were found between (1) online queries and National Health Interview Survey lifetime asthma (r=–.82, P=.001) and current asthma (r=–.77, P=.004) rates from 2004 to 2015 and (2) between online queries and Behavioral Risk Factor Surveillance System lifetime (r=–.78, P=.003) and current asthma (r=–.79, P=.002) rates from 2004 to 2014. The correlations are negative, but lag analysis to identify the period of response cannot be employed until short-interval data on asthma prevalence are made available. Conclusions Online behavior toward asthma can be accurately predicted, and significant correlations between online queries and reported cases exist. This method of forecasting Google queries can be used by health care officials to nowcast asthma prevalence by city, state, or nationally, subject to future availability of daily, weekly, or monthly data on reported cases. This method could therefore be used for improved monitoring and assessment of the needs surrounding the current population of patients with asthma. PMID:29530839

  18. 4-D Cloud Water Content Fields Derived from Operational Satellite Data

    NASA Technical Reports Server (NTRS)

    Smith, William L., Jr.; Minnis, Patrick

    2010-01-01

    In order to improve operational safety and efficiency, the transportation industry, including aviation, has an urgent need for accurate diagnoses and predictions of clouds and associated weather conditions. Adverse weather accounts for 70% of all air traffic delays within the U.S. National Airspace System. The Federal Aviation Administration has determined that as much as two thirds of weather-related delays are potentially avoidable with better weather information and roughly 20% of all aviation accidents are weather related. Thus, it is recognized that an important factor in meeting the goals of the Next Generation Transportation System (NexGen) vision is the improved integration of weather information. The concept of a 4-D weather cube is being developed to address that need by integrating observed and forecasted weather information into a shared 4-D database, providing an integrated and nationally consistent weather picture for a variety of users and to support operational decision support systems. Weather analyses and forecasts derived using Numerical Weather Prediction (NWP) models are a critical tool that forecasters rely on for guidance and also an important element in current and future decision support systems. For example, the Rapid Update Cycle (RUC) and the recently implemented Rapid Refresh (RR) Weather Research and Forecast (WRF) models provide high frequency forecasts and are key elements of the FAA Aviation Weather Research Program. Because clouds play a crucial role in the dynamics and thermodynamics of the atmosphere, they must be adequately accounted for in NWP models. The RUC, for example, cycles at full resolution five cloud microphysical species (cloud water, cloud ice, rain, snow, and graupel) and has the capability of updating these fields from observations. In order to improve the models initial state and subsequent forecasts, cloud top altitude (or temperature, T(sub c)) derived from operational satellite data, surface observations of cloud base altitude, radar reflectivity, and lightning data are used to help build and remove clouds in the models assimilation system. Despite this advance and the many recent advances made in our understanding of cloud physical processes and radiative effects, many problems remain in adequately representing clouds in models. While the assimilation of cloud top information derived from operational satellite data has merit, other information is available that has not yet been exploited. For example, the vertically integrated cloud water content (CWC) or cloud water path (CWP) and cloud geometric thickness (delta Z) are standard products being derived routinely from operational satellite data. These and other cloud products have been validated under a variety of conditions. Since the uncertainties have generally been found to be less than those found in model analyses and forecasts, the satellite products should be suitable for data assimilation, provided an appropriate strategy can be developed that links the satellite-derived cloud parameters with cloud parameters specified in the model. In this paper, we briefly outline such a strategy and describe a methodology to retrieve cloud water content profiles from operational satellite data. Initial results and future plans are presented. It is expected that the direct assimilation of this new product will provide the most accurate depiction of the vertical distribution of cloud water ever produced at the high spatial and temporal resolution needed for short term weather analyses and forecasts.

  19. UCAR group urges STORM program

    NASA Astrophysics Data System (ADS)

    Richman, Barbara T.

    A blue-ribbon panel of scientists has proposed a decade-long, $1 billion program to improve forecasting operations and research of regional and local hazardous weather. The panel, appointed by the University Corporation for Atmospheric Research (UCAR), believes that the program could reduce the $20-billion annual cost of damage from severe weather by $1 billion per year.The primary aim of the program is to ‘enable weather services, public and private, to observe and predict stormscale weather phenomena— such as squall lines, thunderstorms, flash floods, local heavy snows, or tornadoes—with the accuracy and reliability to protect the public, serve the national economy, and meet defense requirements,’ as explained in the report, The National STORM (Stormscale Operational and Research Meteorology) Program: A Call to Action. Stormscale phenomena also include nonviolent weather: freezing rain, dense ground fog, low-lying clouds that disrupt ground or air traffic, persistent temperature inversions, and strong nocturnal cooling that may produce killing frost.

  20. Integrated Mode Choice, Small Aircraft Demand, and Airport Operations Model User's Guide

    NASA Technical Reports Server (NTRS)

    Yackovetsky, Robert E. (Technical Monitor); Dollyhigh, Samuel M.

    2004-01-01

    A mode choice model that generates on-demand air travel forecasts at a set of GA airports based on changes in economic characteristics, vehicle performance characteristics such as speed and cost, and demographic trends has been integrated with a model to generate itinerate aircraft operations by airplane category at a set of 3227 airports. Numerous intermediate outputs can be generated, such as the number of additional trips diverted from automobiles and schedule air by the improved performance and cost of on-demand air vehicles. The total number of transported passenger miles that are diverted is also available. From these results the number of new aircraft to service the increased demand can be calculated. Output from the models discussed is in the format to generate the origin and destination traffic flow between the 3227 airports based on solutions to a gravity model.

  1. Characteristics of future air cargo demand and impact on aircraft development - A report on the Cargo/Logistic Airlift Systems Study /CLASS/ project

    NASA Technical Reports Server (NTRS)

    Whitehead, A. H., Jr.

    1978-01-01

    The considered study has been conducted to evaluate the future potential for an advanced air cargo transport. A current operations analysis is discussed, taking into account the traffic structure, modal cost comparisons, terminal operations, containerization, and institutional factors. Attention is also given to case studies, a demand forecast, and an advanced air cargo systems analysis. The effects of potential improvements on reducing costs are shown. Improvement to the current infrastructure can occur from 1978 to 1985 with off-the-shelf technology, which when combined with higher load factors for aircraft and containers, can provide up to a 16 percent reduction in total operating costs and a 15 percent rate reduction. The results of the analysis indicate that the proposed changes in the infrastructure and improved cargo loading efficiencies are as important to improving the airlines' financial posture as is the anticipated large dedicated cargo aircraft.

  2. Human mobility: Models and applications

    NASA Astrophysics Data System (ADS)

    Barbosa, Hugo; Barthelemy, Marc; Ghoshal, Gourab; James, Charlotte R.; Lenormand, Maxime; Louail, Thomas; Menezes, Ronaldo; Ramasco, José J.; Simini, Filippo; Tomasini, Marcello

    2018-03-01

    Recent years have witnessed an explosion of extensive geolocated datasets related to human movement, enabling scientists to quantitatively study individual and collective mobility patterns, and to generate models that can capture and reproduce the spatiotemporal structures and regularities in human trajectories. The study of human mobility is especially important for applications such as estimating migratory flows, traffic forecasting, urban planning, and epidemic modeling. In this survey, we review the approaches developed to reproduce various mobility patterns, with the main focus on recent developments. This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems. The review organizes the subject by differentiating between individual and population mobility and also between short-range and long-range mobility. Throughout the text the description of the theory is intertwined with real-world applications.

  3. Application of GIS to modified models of vehicle emission dispersion

    NASA Astrophysics Data System (ADS)

    Jin, Taosheng; Fu, Lixin

    This paper reports on a preliminary study of the forecast and evaluation of transport-related air pollution dispersion in urban areas. Some modifications of the traditional Gauss dispersion models are provided, and especially a crossroad model is built, which considers the great variation of vehicle emission attributed to different driving patterns at the crossroad. The above models are combined with a self-developed geographic information system (GIS) platform, and a simulative system with graphical interfaces is built. The system aims at visually describing the influences on the urban environment by urban traffic characteristics and therefore gives a reference to the improvement of urban air quality. Due to the introduction of a self-developed GIS platform and a creative crossroad model, the system is more effective, flexible and accurate. Finally, a comparison of the simulated (predicted) and observed hourly concentration is given, which indicates a good simulation.

  4. Cross-impact study of foreign satellite communications on NASA's 30/20 GHz program

    NASA Technical Reports Server (NTRS)

    1980-01-01

    A comprehensive traffic demand forecast and a scenario for the transition process from current satellite systems to more advanced systems of the 1990's are presented. Systems configurations with and without the use of 30/20 GHz are described and these two alternatives are compared. It is concluded that: (1) the use of 30/20 GHz will result in increased satellite capacity, which will be needed to satisfy demand; (2) the use of 30/20 GHz will decrease the transmission cost, especially for broadband communications; (3) in some areas, particularly Europe and Japan but also the U.S., 30/20 GHz is the only available frequency band for customer premise Earth stations because of the dense terrestrial microwave networks; and (4) the development of 30/20 GHz technology will improve U.S. markets for equipment and satellites in many world regions.

  5. Cross-impact study of foreign satellite communications on NASA's 30/20 GHz program

    NASA Astrophysics Data System (ADS)

    1980-08-01

    A comprehensive traffic demand forecast and a scenario for the transition process from current satellite systems to more advanced systems of the 1990's are presented. Systems configurations with and without the use of 30/20 GHz are described and these two alternatives are compared. It is concluded that: (1) the use of 30/20 GHz will result in increased satellite capacity, which will be needed to satisfy demand; (2) the use of 30/20 GHz will decrease the transmission cost, especially for broadband communications; (3) in some areas, particularly Europe and Japan but also the U.S., 30/20 GHz is the only available frequency band for customer premise Earth stations because of the dense terrestrial microwave networks; and (4) the development of 30/20 GHz technology will improve U.S. markets for equipment and satellites in many world regions.

  6. Reference dataset of volcanic ash physicochemical and optical properties for atmospheric measurement retrievals and transport modelling

    NASA Astrophysics Data System (ADS)

    Vogel, Andreas; Durant, Adam; Sytchkova, Anna; Diplas, Spyros; Bonadonna, Costanza; Scarnato, Barbara; Krüger, Kirstin; Kylling, Arve; Kristiansen, Nina; Stohl, Andreas

    2016-04-01

    Explosive volcanic eruptions emit up to 50 wt.% (total erupted mass) of fine ash particles (<63 microns), which individually can have theoretical atmospheric lifetimes that span hours to days. Depending on the injection height, fine ash may be subsequently transported and dispersed by the atmosphere over 100s - 1000s km and can pose a major threat for aviation operations. Recent volcanic eruptions, such as the 2010 Icelandic Eyjafjallajökull event, illustrated how volcanic ash can severely impact commercial air traffic. In order to manage the threat, it is important to have accurate forecast information on the spatial extent and absolute quantity of airborne volcanic ash. Such forecasts are constrained by empirically-derived estimates of the volcanic source term and the nature of the constituent volcanic ash properties. Consequently, it is important to include a quantitative assessment of measurement uncertainties of ash properties to provide realistic ash forecast uncertainty. Currently, information on volcanic ash physicochemical and optical properties is derived from a small number of somewhat dated publications. In this study, we provide a reference dataset for physical (size distribution and shape), chemical (bulk vs. surface chemistry) and optical properties (complex refractive index in the UV-vis-NIR range) of a representative selection of volcanic ash samples from 10 different volcanic eruptions covering the full variability in silica content (40-75 wt.% SiO2). Through the combination of empirical analytical methods (e.g., image analysis, Energy Dispersive Spectroscopy, X-ray Photoelectron Spectroscopy, Transmission Electron Microscopy and UV/Vis/NIR/FTIR Spectroscopy) and theoretical models (e.g., Bruggeman effective medium approach), it was possible to fully capture the natural variability of ash physicochemical and optical characteristics. The dataset will be applied in atmospheric measurement retrievals and atmospheric transport modelling to determine the sensitivity to uncertainty in ash particle characteristics.

  7. Relating traffic fatalities to GDP in Europe on the long term.

    PubMed

    Antoniou, Constantinos; Yannis, George; Papadimitriou, Eleonora; Lassarre, Sylvain

    2016-07-01

    Modeling road safety development can provide important insight into policies for the reduction of traffic fatalities. In order to achieve this goal, both the quantifiable impact of specific parameters, as well as the underlying trends that cannot always be measured or observed, need to be considered. One of the key relationships in road safety links fatalities with risk and exposure, where exposure reflects the amount of travel, which in turn translates to how much travelers are exposed to risk. In general two economic variables: GDP and unemployment rate are selected to analyse the statistical relationships with some indicators of road accident fatality risk. The objective of this research is to provide an overview of relevant literature on the topic and outline some recent developments in macro-panel data analysis that have resulted in ongoing research that has the potential to improve our ability to forecast traffic fatality trends, especially under turbulent financial situations. For this analysis, time series of the number of fatalities and GDP in 30 European countries for a period of 38 years (1975-2012) are used. This process relies on estimating long-term models (as captured by long term time-series models, which model each country separately). Based on these developments, utilizing state-of-the-art modelling and analysis techniques such as the Common Correlated Effects Mean Group estimator (Pesaran), the long-term elasticity mean value equals 0.63, and is significantly different from zero for 10 countries only. When we take away the countries, where the number of fatalities is stationary, the average elasticity takes a higher value of nearly 1. This shows the strong sensitivity of the estimate of the average elasticity over a panel of European countries and underlines the necessity to be aware of the underlying nature of the time series, to get a suitable regression model. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Relative impact of emissions controls and meteorology on air pollution mitigation associated with the Asia-Pacific Economic Cooperation (APEC) conference in Beijing, China.

    PubMed

    Wang, Yuqin; Zhang, Yang; Schauer, James Jay; de Foy, Benjamin; Guo, Bo; Zhang, Yuanxun

    2016-11-15

    The Beijing government and its surrounding provinces implemented a series of measures to ensure haze-free skies during the 22(nd) Asia-Pacific Economic Cooperation (APEC) conference (November 10(th)-11(th), 2014). These measures included restrictions on traffic, construction, and industrial activity. Twelve hour measurements of the concentration and composition of ambient fine particulate matter (PM2.5) were performed for 5 consecutive months near the APEC conference site before (September 11(th)-November 2(nd), 2014), during (November 3(rd)-12(th), 2014) and after (November 13(th), 2014-January 31(st), 2015). The measurements are used in a positive matrix factorization model to determine the contributions from seven sources of PM2.5: secondary aerosols, traffic exhaust, industrial emission, road dust, soil dust, biomass burning and residual oil combustion. The source apportionment results are integrated with backward trajectory analysis using Weather Research and Forecast (WRF) meteorological simulations, which determine the relative influence of new regulation and meteorology upon improved air quality during the APEC conference. Data show that controls are very effective, but meteorology must be taken into account to determine the actual influence of the controls on pollution reduction. The industry source control is the most effective for reducing concentrations, followed by secondary aerosol and biomass controls, while the least effective control is for the residual oil combustion source. The largest reductions in concentrations occur when air mass transport is from the west-northwest (Ulanqab). Secondary aerosol and traffic exhaust reductions are most significant for air mass transport from the north-northwest (Xilingele League) origin, and least significant for northeast transport (Chifeng via Tangshan conditions). The largest reductions of soil dust, biomass burning, and industrial source are distinctly seen for Ulanqab conditions and least distinct for Xilingele League. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. The evaluation of marine traffic noise and its effect on the Chinese White Dolphins in Sha Chau and Lung Kwu Chau Marine Park, Hong Kong

    NASA Astrophysics Data System (ADS)

    Chan, T.

    2016-12-01

    The Hong Kong International Airport (HKIA) handles a large amount of air traffic, at 68.5 million passengers per year (approx. 40.1 million flights per year). Given that flight demand is forecast to reach 97 million passengers per year (approx 60.2 million flights per year) by 2030, the HKIA must optimise runway capacity in order to meet growing demand. Hence, the Airport Authority Hong Kong (AAHK) has put forward a proposal to expand the airport into a three-runway system by building a third runway. However, this presents many environmental constraints. These include major impacts on marine ecology; especially the Chinese White Dolphins (Sousa chinensis) that live around the Sha Chau and Lung Kwu Chau Marine Park north to the airport. Due to that the third runway will reclaim approximately 650 hectares of the se so re-routing of speed boats and ferries has been planned. This includes one route that passes through the marine nursery inside the park. This indirectly causes noise pollution that will affect marine life. Since dolphins rely on echolocation (often discerned by a "click" sound) to communicate and navigate, increasing marine traffic (re-routing) causes obscuring noises and acoustic communication interfering with echolocation, as well as collisions which lead to physical injuries. Underwater construction works involving techniques such as percussive piling may interfere with the dolphins' echolocation capability. The data has been collected using a hydrophone by observing the noise frequency changes within the marine park. The noises come from a number of sources, including fishing boats, and speed boats, krill and around 20 estuarine fish species. The evaluation of four years (2013-2016) has shown that noise pollution is increasing (as indicated by the increase of frequencies around 100 125 kHz) and that it has caused disruption in regular dolphin movement (irregular clicking sequence) .

  10. VOC flux measurements using a novel Relaxed Eddy Accumulation GC-FID system in urban Houston, Texas

    NASA Astrophysics Data System (ADS)

    Park, C.; Schade, G.; Boedeker, I.

    2008-12-01

    Houston experiences higher ozone production rates than most other major cities in the US, which is related to high anthropogenic VOC emissions from both area/mobile sources (car traffic) and a large number of petrochemical facilities. The EPA forecasts that Houston is likely to still violate the new 8-h NAAQS in 2020. To monitor neighborhood scale pollutant fluxes, we established a tall flux tower installation a few kilometers north of downtown Houston. We measure energy and trace gas fluxes, including VOCs from both anthropogenic and biogenic emission sources in the urban surface layer using eddy covariance and related techniques. Here, we describe a Relaxed Eddy Accumulation (REA) system combined with a dual-channel GC-FID used for VOC flux measurements, including first results. Ambient air is sampled at approximately 15 L min-1 through a 9.5 mm OD PFA line from 60 m above ground next to a sonic anemometer. Subsamples of this air stream are extracted through an ozone scrubber and pushed into two Teflon bag reservoirs, from which they are transferred to the GC pre-concentration units consisting of carbon-based adsorption traps encapsulated in heater blocks for thermal desorption. We discuss the performance of our system and selected measurement results from the 2008 spring and summer seasons in Houston. We present diurnal variations of the fluxes of the traffic tracers benzene, toluene, ethylbenzene, and xylenes (BTEX) during different study periods. Typical BTEX fluxes ranged from -0.36 to 3.10 mg m-2 h-1 for benzene, and -0.47 to 5.04 mg m-2 h-1 for toluene, and exhibited diurnal cycles with two dominant peaks related to rush-hour traffic. A footprint analysis overlaid onto a geographic information system (GIS) will be presented to reveal the dominant emission sources and patterns in the study area.

  11. Delay functions in trip assignment for transport planning process

    NASA Astrophysics Data System (ADS)

    Leong, Lee Vien

    2017-10-01

    In transportation planning process, volume-delay and turn-penalty functions are the functions needed in traffic assignment to determine travel time on road network links. Volume-delay function is the delay function describing speed-flow relationship while turn-penalty function is the delay function associated to making a turn at intersection. The volume-delay function used in this study is the revised Bureau of Public Roads (BPR) function with the constant parameters, α and β values of 0.8298 and 3.361 while the turn-penalty functions for signalized intersection were developed based on uniform, random and overflow delay models. Parameters such as green time, cycle time and saturation flow were used in the development of turn-penalty functions. In order to assess the accuracy of the delay functions, road network in areas of Nibong Tebal, Penang and Parit Buntar, Perak was developed and modelled using transportation demand forecasting software. In order to calibrate the models, phase times and traffic volumes at fourteen signalised intersections within the study area were collected during morning and evening peak hours. The prediction of assigned volumes using the revised BPR function and the developed turn-penalty functions show close agreement to actual recorded traffic volume with the lowest percentage of accuracy, 80.08% and the highest, 93.04% for the morning peak model. As for the evening peak model, they were 75.59% and 95.33% respectively for lowest and highest percentage of accuracy. As for the yield left-turn lanes, the lowest percentage of accuracy obtained for the morning and evening peak models were 60.94% and 69.74% respectively while the highest percentage of accuracy obtained for both models were 100%. Therefore, can be concluded that the development and utilisation of delay functions based on local road conditions are important as localised delay functions can produce better estimate of link travel times and hence better planning for future scenarios.

  12. Direct carbon dioxide emissions from civil aircraft

    NASA Astrophysics Data System (ADS)

    Grote, Matt; Williams, Ian; Preston, John

    2014-10-01

    Global airlines consume over 5 million barrels of oil per day, and the resulting carbon dioxide (CO2) emitted by aircraft engines is of concern. This article provides a contemporary review of the literature associated with the measures available to the civil aviation industry for mitigating CO2 emissions from aircraft. The measures are addressed under two categories - policy and legal-related measures, and technological and operational measures. Results of the review are used to develop several insights into the challenges faced. The analysis shows that forecasts for strong growth in air-traffic will result in civil aviation becoming an increasingly significant contributor to anthropogenic CO2 emissions. Some mitigation-measures can be left to market-forces as the key-driver for implementation because they directly reduce airlines' fuel consumption, and their impact on reducing fuel-costs will be welcomed by the industry. Other mitigation-measures cannot be left to market-forces. Speed of implementation and stringency of these measures will not be satisfactorily resolved unattended, and the current global regulatory-framework does not provide the necessary strength of stewardship. A global regulator with ‘teeth' needs to be established, but investing such a body with the appropriate level of authority requires securing an international agreement which history would suggest is going to be very difficult. If all mitigation-measures are successfully implemented, it is still likely that traffic growth-rates will continue to out-pace emissions reduction-rates. Therefore, to achieve an overall reduction in CO2 emissions, behaviour change will be necessary to reduce demand for air-travel. However, reducing demand will be strongly resisted by all stakeholders in the industry; and the ticket price-increases necessary to induce the required reduction in traffic growth-rates place a monetary-value on CO2 emissions of approximately 7-100 times greater than other common valuations. It is clear that, whilst aviation must remain one piece of the transport-jigsaw, environmentally a global regulator with ‘teeth' is urgently required.

  13. Modeling the Impact of Arctic Shipping Pollution on Air Quality off the Coast of Northern Norway

    NASA Astrophysics Data System (ADS)

    Thomas, J. L.; Law, K.; Marelle, L.; Raut, J.; Jalkanen, J.; Johansson, L.; Roiger, A.; Schlager, H.; Kim, J.; Reiter, A.; Weinzierl, B.; Rose, M.; Fast, J. D.

    2013-12-01

    As the Arctic is undergoing rapid and potentially irreversible changes, such as the shrinking and thinning of sea-ice cover, the levels of atmospheric pollution are expected to rise dramatically due to the emergence of local pollution sources including shipping. Shipping routes through the Arctic (such as Russia's Northern Sea Route) are already used as an alternative to the traditional global transit shipping routes. In summer 2012, the ACCESS (Arctic Climate Change, Economy, and Society) aircraft campaign focused on studying pollution sources off the coast of northern Norway to quantify emissions from shipping and other anthropogenic pollution sources. To complement these measurements, a regional chemical transport model is used to study the impact of shipping pollution on gas and aerosol concentrations in the region. WRF-Chem (The Weather Research and Forecasting Model with Chemistry, which simulates gas and aerosols simultaneously with meteorology) is run with real time shipping emissions from STEAM (Ship Traffic Emission Assessment Model) for July 2012. The STEAM model calculates gas and aerosol emissions of marine traffic based on the ship type and location provided by the Automatic Identification System (AIS). Use of real time position, speed, and ship specific information allows for development of emissions with very high spatial (1x1 km) and temporal (30 min) resolution, which are used in the regional model runs. STEAM emissions have been specifically generated for shipping off the coast of Norway during the entire ACCESS campaign period. Simulated ship plumes from high-resolution model runs are compared to aircraft measurements. The regional impact of current summertime shipping is also examined. At present, relatively light ship traffic off the coast of northern Norway results in only a small impact of shipping pollution on regional atmospheric chemistry. The impact of increased future shipping on regional atmospheric chemistry is also assessed.

  14. Operational air quality forecasting system for Spain: CALIOPE

    NASA Astrophysics Data System (ADS)

    Baldasano, J. M.; Piot, M.; Jorba, O.; Goncalves, M.; Pay, M.; Pirez, C.; Lopez, E.; Gasso, S.; Martin, F.; García-Vivanco, M.; Palomino, I.; Querol, X.; Pandolfi, M.; Dieguez, J. J.; Padilla, L.

    2009-12-01

    The European Commission (EC) and the United States Environmental Protection Agency (US-EPA) have shown great concerns to understand the transport and dynamics of pollutants in the atmosphere. According to the European directives (1996/62/EC, 2002/3/EC, 2008/50/EC), air quality modeling, if accurately applied, is a useful tool to understand the dynamics of air pollutants, to analyze and forecast the air quality, and to develop programs reducing emissions and alert the population when health-related issues occur. The CALIOPE project, funded by the Spanish Ministry of the Environment, has the main objective to establish an air quality forecasting system for Spain. A partnership of four research institutions composes the CALIOPE project: the Barcelona Supercomputing Center (BSC), the center of investigation CIEMAT, the Earth Sciences Institute ‘Jaume Almera’ (IJA-CSIC) and the CEAM Foundation. CALIOPE will become the official Spanish air quality operational system. This contribution focuses on the recent developments and implementation of the integrated modelling system for the Iberian Peninsula (IP) and Canary Islands (CI) with a high spatial and temporal resolution (4x4 sq. km for IP and 2x2 sq. km for CI, 1 hour), namely WRF-ARW/HERMES04/CMAQ/BSC-DREAM. The HERMES04 emission model has been specifically developed as a high-resolution (1x1 sq. km, 1 hour) emission model for Spain. It includes biogenic and anthropogenic emissions such as on-road and paved-road resuspension production, power plant generation, ship and plane traffic, airports and ports activities, industrial and agricultural sectors as well as domestic and commercial emissions. The qualitative and quantitative evaluation of the model was performed for a reference year (2004) using data from ground-based measurement networks. The products of the CALIOPE system will provide 24h and 48h forecasts for O3, NO2, SO2, CO, PM10 and PM2.5 at surface level. An operational evaluation system has been developed to provide near real-time evaluation products for the Spanish territory. For this purpose, more than 130 surface stations, 2 ozonesondes and the OMI satellite retrieval information are introduced to the system on a daily basis. A web-based visualization system allows a straightforward access to all the evaluation products. The present contribution will describe the main characteristics of the operational system and results of the operational evaluation.

  15. Deterministic decomposition and seasonal ARIMA time series models applied to airport noise forecasting

    NASA Astrophysics Data System (ADS)

    Guarnaccia, Claudio; Quartieri, Joseph; Tepedino, Carmine

    2017-06-01

    One of the most hazardous physical polluting agents, considering their effects on human health, is acoustical noise. Airports are a strong source of acoustical noise, due to the airplanes turbines, to the aero-dynamical noise of transits, to the acceleration or the breaking during the take-off and landing phases of aircrafts, to the road traffic around the airport, etc.. The monitoring and the prediction of the acoustical level emitted by airports can be very useful to assess the impact on human health and activities. In the airports noise scenario, thanks to flights scheduling, the predominant sources may have a periodic behaviour. Thus, a Time Series Analysis approach can be adopted, considering that a general trend and a seasonal behaviour can be highlighted and used to build a predictive model. In this paper, two different approaches are adopted, thus two predictive models are constructed and tested. The first model is based on deterministic decomposition and is built composing the trend, that is the long term behaviour, the seasonality, that is the periodic component, and the random variations. The second model is based on seasonal autoregressive moving average, and it belongs to the stochastic class of models. The two different models are fitted on an acoustical level dataset collected close to the Nice (France) international airport. Results will be encouraging and will show good prediction performances of both the adopted strategies. A residual analysis is performed, in order to quantify the forecasting error features.

  16. Multiscale Observation System for Sea Ice Drift and Deformation

    NASA Astrophysics Data System (ADS)

    Lensu, M.; Haapala, J. J.; Heiler, I.; Karvonen, J.; Suominen, M.

    2011-12-01

    The drift and deformation of sea ice cover is most commonly followed from successive SAR images. The time interval between the images is seldom less than one day which provides rather crude approximation of the motion fields as ice can move tens of kilometers per day. This is particulary so from the viewpoint of operative services, seeking to provide real time information for ice navigating ships and other end users, as leads are closed and opened or ridge fields created in time scales of one hour or less. The ice forecast models are in a need of better temporal resolution for ice motion data as well. We present experiences from a multiscale monitoring system set up to the Bay of Bothnia, the northernmost basin of the Baltic Sea. The basin generates difficult ice conditions every winter while the ports are kept open with the help of an icebreaker fleet. The key addition to SAR imagery is the use of coastal radars for the monitoring of coastal ice fields. An independent server is used to tap the radar signal and process it to suit ice monitoring purposes. This is done without interfering the basic use of the radars, the ship traffic monitoring. About 20 images per minute are captured and sent to the headquarters for motion field extraction, website animation and distribution. This provides very detailed real time picture of the ice movement and deformation within 20 km range. The real time movements are followed in addition with ice drifter arrays, and using AIS ship identification data, from which the translation of ship cannels due to ice drift can be found out. To the operative setup is associated an extensive research effort that uses the data for ice drift model enhancement. The Baltic ice models seek to forecast conditions relevant to ship traffic, especilly hazardous ones like severe ice compression. The main missing link here is downscaling, or the relation of local scale ice dynamics and kinematics to the ice model scale behaviour. The data flow when combined with SAR images gives information on how large scale ice cover motions manifest as local scale deformations. The research includes also ice stress measurements for relating the kinematic state and modeled stresses to local scale ice cover stresses, and ice thickness mappings with profiling sonars and EM methods. Downscaling results based on four-month campaing during winter 2011 are presented.

  17. The Processing of Airspace Concept Evaluations Using FASTE-CNS as a Pre- or Post-Simulation CNS Analysis Tool

    NASA Technical Reports Server (NTRS)

    Mainger, Steve

    2004-01-01

    As NASA speculates on and explores the future of aviation, the technological and physical aspects of our environment increasing become hurdles that must be overcome for success. Research into methods for overcoming some of these selected hurdles have been purposed by several NASA research partners as concepts. The task of establishing a common evaluation environment was placed on NASA's Virtual Airspace Simulation Technologies (VAST) project (sub-project of VAMS), and they responded with the development of the Airspace Concept Evaluation System (ACES). As one examines the ACES environment from a communication, navigation or surveillance (CNS) perspective, the simulation parameters are built with assumed perfection in the transactions associated with CNS. To truly evaluate these concepts in a realistic sense, the contributions/effects of CNS must be part of the ACES. NASA Glenn Research Center (GRC) has supported the Virtual Airspace Modeling and Simulation (VAMS) project through the continued development of CNS models and analysis capabilities which supports the ACES environment. NASA GRC initiated the development a communications traffic loading analysis tool, called the Future Aeronautical Sub-network Traffic Emulator for Communications, Navigation and Surveillance (FASTE-CNS), as part of this support. This tool allows for forecasting of communications load with the understanding that, there is no single, common source for loading models used to evaluate the existing and planned communications channels; and that, consensus and accuracy in the traffic load models is a very important input to the decisions being made on the acceptability of communication techniques used to fulfill the aeronautical requirements. Leveraging off the existing capabilities of the FASTE-CNS tool, GRC has called for FASTE-CNS to have the functionality to pre- and post-process the simulation runs of ACES to report on instances when traffic density, frequency congestion or aircraft spacing/distance violations have occurred. The integration of these functions require that the CNS models used to characterize these avionic system be of higher fidelity and better consistency then is present in FASTE-CNS system. This presentation will explore the capabilities of FASTE-CNS with renewed emphasis on the enhancements being added to perform these processing functions; the fidelity and reliability of CNS models necessary to make the enhancements work; and the benchmarking of FASTE-CNS results to improve confidence for the results of the new processing capabilities.

  18. Geographic range and structure of cryptic genetic diversity among Pacific North American populations of the non-native amphipod Grandidierella japonica

    USGS Publications Warehouse

    Pilgrim, Erik M.; Blum, Michael J.; Reusser, Deborah A.; Lee, Henry; Darling, John A.

    2013-01-01

    Reconstructing the invasion history of aquatic invasive species can enhance understanding of invasion risks by recognizing areas most susceptible to invasion and forecasting future spread based on past patterns of population expansion. Here we reconstruct the invasion history of the Japanese amphipod Grandidierella japonica Stephensen 1938 combining information from historical collection data with molecular genetic data to better understand post-invasion range expansion and anthropogenic connectivity across the Pacific coast of North America. Compilation of collection data from bays and estuaries of the Pacific North American coast show many new localities have been colonized in the last two decades, moving outward from harbors and bays with high commercial traffic into smaller coastal locations dominated by local recreational traffic. DNA barcode sequence data for G. japonica reveals two distinct clades: one found in San Francisco Bay and sites to the north, and one also found in San Francisco Bay and sites to the south. The two clades differ by an average 7.28 % genetic distance, large enough to consider these invasive amphipods two separate species. Both northern and southern clades exhibit low levels of genetic diversity, suggesting a single introduction event for each. The presence of cryptic diversity within this invasive amphipod highlights the need for more extensive study of the invasive and native populations of aquatic invasive invertebrates to address questions of taxonomy, diversity, and invasion history.

  19. Integrating Smart Health in the US Health Care System: Infodemiology Study of Asthma Monitoring in the Google Era.

    PubMed

    Mavragani, Amaryllis; Sampri, Alexia; Sypsa, Karla; Tsagarakis, Konstantinos P

    2018-03-12

    With the internet's penetration and use constantly expanding, this vast amount of information can be employed in order to better assess issues in the US health care system. Google Trends, a popular tool in big data analytics, has been widely used in the past to examine interest in various medical and health-related topics and has shown great potential in forecastings, predictions, and nowcastings. As empirical relationships between online queries and human behavior have been shown to exist, a new opportunity to explore the behavior toward asthma-a common respiratory disease-is present. This study aimed at forecasting the online behavior toward asthma and examined the correlations between queries and reported cases in order to explore the possibility of nowcasting asthma prevalence in the United States using online search traffic data. Applying Holt-Winters exponential smoothing to Google Trends time series from 2004 to 2015 for the term "asthma," forecasts for online queries at state and national levels are estimated from 2016 to 2020 and validated against available Google query data from January 2016 to June 2017. Correlations among yearly Google queries and between Google queries and reported asthma cases are examined. Our analysis shows that search queries exhibit seasonality within each year and the relationships between each 2 years' queries are statistically significant (P<.05). Estimated forecasting models for a 5-year period (2016 through 2020) for Google queries are robust and validated against available data from January 2016 to June 2017. Significant correlations were found between (1) online queries and National Health Interview Survey lifetime asthma (r=-.82, P=.001) and current asthma (r=-.77, P=.004) rates from 2004 to 2015 and (2) between online queries and Behavioral Risk Factor Surveillance System lifetime (r=-.78, P=.003) and current asthma (r=-.79, P=.002) rates from 2004 to 2014. The correlations are negative, but lag analysis to identify the period of response cannot be employed until short-interval data on asthma prevalence are made available. Online behavior toward asthma can be accurately predicted, and significant correlations between online queries and reported cases exist. This method of forecasting Google queries can be used by health care officials to nowcast asthma prevalence by city, state, or nationally, subject to future availability of daily, weekly, or monthly data on reported cases. This method could therefore be used for improved monitoring and assessment of the needs surrounding the current population of patients with asthma. ©Amaryllis Mavragani, Alexia Sampri, Karla Sypsa, Konstantinos P Tsagarakis. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 12.03.2018.

  20. An Operational Coastal Forecasting System in Galicia (NW Spain)

    NASA Astrophysics Data System (ADS)

    Balseiro, C. F.; Carracedo, P.; Pérez, E.; Pérez, V.; Taboada, J.; Venacio, A.; Vilasa, L.

    2009-09-01

    The Galician coast (NW Iberian Peninsula coast) and mainly the Rias Baixas (southern Galician rias) are one of the most productive ecosystems in the world, supporting a very active fishing and aquiculture industry. This high productivity lives together with a high human pressure and an intense maritime traffic, which means an important environmental risk. Besides that, Harmful Algae Blooms (HAB) are common in this area, producing important economical losses in aquiculture. In this context, the development of an Operational Hydrodynamic Ocean Forecast System is the first step to the development of a more sophisticated Ocean Integrated Decision Support Tool. A regional oceanographic forecasting system in the Galician Coast has been developed by MeteoGalicia (the Galician regional meteorological agency) inside ESEOO project to provide forecasts on currents, sea level, water temperature and salinity. This system is based on hydrodynamic model MOHID, forced with the operational meteorological model WRF, supported daily at MeteoGalicia . Two grid meshes are running nested at different scales, one of ~2km at the shelf scale and the other one with a resolution of 500 m at the rias scale. ESEOAT (Puertos del Estado) model provide salinity and temperature fields which are relaxed at all depth along the open boundary of the regional model (~6km). Temperature and salinity initial fields are also obtained from this application. Freshwater input from main rivers are included as forcing in MOHID model. Monthly mean discharge data from gauge station have been provided by Aguas de Galicia. Nowadays a coupling between an hydrological model (SWAT) and the hydrodynamic one are in development with the aim to verify the impact of the rivers discharges. The system runs operationally daily, providing two days of forecast. First model verifications had been performed against Puertos del Estado buoys and Xunta de Galicia buoys network along the Galician coast. High resolution model results were validated against a CTDs profiles campaign carried out during an oil spill exercise in the Ria de Vigo in April 2007. During EROCIPS INTERREG IIIB and EASY INTERREG IVB projects, a Galician oceanographic observation network were built. Three stations located inside the Rias Baixas allow to collect meteorological and oceanographic data at different depths to calibrate and validate the modelization of the rias. To complete this network and to create a common data platform a new project emerged (RAIA INTERREG IVA). It will provide MeteoGalicia more scientific data to improve the study of the rias. Furthermore, MeteoGalicia is also involved in DRIFTER AMPERA project which allows to improve the capability of modelling and monitoring the trajectory of hazardous substances and inerts.

  1. New tool for the Black Sea environmental safety: BlackSea Track Web

    NASA Astrophysics Data System (ADS)

    Kubryakov, A. I.; Korotayev, G. K.; Thoorens, F.-X.; Liungman, O.; Ambjorn, C.

    2012-04-01

    Huge increases in the volume of oil being transported across the Black Sea have greatly increased the risk of oil pollution. Remote sensing data show that the majority of oil spills occur along major shipping routes, suggesting that shipping, rather than land-based oil installations have been the principal cause of concern. However, a single large spill from ships, platforms or land-based oil installations could severely impact biota and the economies of all coastal countries and could produce significant damage of the Black Sea ecosystem and fishing. Also, due to the semi-enclosed character of the basin, oil spill will definitely pollute coast of the basin suffering great losses to the recreation industry and potentially to the human health. Fighting oil pollution in the Black Sea is a great challenge. The challenge is likely to become even greater in the future as maritime traffic is expected to increase over the next few years, making offences and accidents more likely. The risks of shipwrecks and catastrophic oil spill necessitate the use of the modern technologies to effectively protect the marine environment. In turn, such technologies require high-quality products of operational oceanography. Recently such products are the products of the MyOcean project. The development of the Black Sea operational oceanography made it possible to transfer of cost-efficient technologies to the region to create a new tool against oil pollution and for life-saving in case of a shipwreck. The Black Sea Track Web (BSTW) system of accidental oil spill evolution forecast in the Black Sea has been created in the framework of MONINFO project. The system is based on the Seatrack Web (STW) model developing by the consortium of the Baltic Sea countries. It is adapted to the configuration of the Black Sea observing system and is implemented to the regional contingency plans. The BSTW system consists of three parts: - forcing in the form of forecasted stratification, sea currents and wind fields, which is provided by the Black Sea MFC located at MHI in Sevastopol. The Black Sea MFC is the MyOcean regional marine forecasting center. It runs operationally and forms weather and ocean forecasts; - the oil drift model jointly developed by SMHI and the Royal Danish Administration of Navigation and Hydrography and which takes into account and adequately describes almost all physical processes affecting the oil spill; - the graphical user interface developed by SMHI and based on open source GIS-server technology. The developed BSTW system is available via the Internet, fully operational 24 hours a day and user friendly. It allows immediate access to the latest forecasts that drives the system. And in addition, it provides other floating objects and back tracking.

  2. Characteristics of turn signal use at intersections in baseline naturalistic driving.

    PubMed

    Sullivan, John M; Bao, Shan; Goudy, Roy; Konet, Heather

    2015-01-01

    The purpose of this study was to determine whether a driver's use of turn signals is sufficiently reliable to forecast a vehicle's future path around an intersection, when detailed information about the intersection is unavailable. Naturalistic observations of turn signal use among 108 drivers on surface streets were extracted from the baseline portion of a field operational test of a safety system. Left and right turns that resulted in heading changes of between 70 and 110° and turn radii between 18 and 90 m were selected from the dataset. The odds that a driver would signal a turn were modeled as a function of road type, turn direction, presence of a forward vehicle, whether the vehicle stopped before the turn, and driver age and gender. Overall, 25 percent of left turns and 29 percent of right turns were not signaled. Road type, turn direction, and presence of a forward vehicle were found to influence the odds that a turn is signaled, while gender and age of the driver did not. The results suggest that situational factors like road type and turn direction are more powerful predictors of whether a turn will be signaled than either age or gender. Signaling on major and minor surface roads was about 5 times more likely than on local roads and 1.5 times more likely when a forward vehicle was present, suggesting a possible effect of traffic volume. It was concluded that turn signal activation alone may be insufficiently reliable to forecast a driver's path. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. Statistical analysis of the induced Basel 2006 earthquake sequence: introducing a probability-based monitoring approach for Enhanced Geothermal Systems

    NASA Astrophysics Data System (ADS)

    Bachmann, C. E.; Wiemer, S.; Woessner, J.; Hainzl, S.

    2011-08-01

    Geothermal energy is becoming an important clean energy source, however, the stimulation of a reservoir for an Enhanced Geothermal System (EGS) is associated with seismic risk due to induced seismicity. Seismicity occurring due to the water injection at depth have to be well recorded and monitored. To mitigate the seismic risk of a damaging event, an appropriate alarm system needs to be in place for each individual experiment. In recent experiments, the so-called traffic-light alarm system, based on public response, local magnitude and peak ground velocity, was used. We aim to improve the pre-defined alarm system by introducing a probability-based approach; we retrospectively model the ongoing seismicity in real time with multiple statistical forecast models and then translate the forecast to seismic hazard in terms of probabilities of exceeding a ground motion intensity level. One class of models accounts for the water injection rate, the main parameter that can be controlled by the operators during an experiment. By translating the models into time-varying probabilities of exceeding various intensity levels, we provide tools which are well understood by the decision makers and can be used to determine thresholds non-exceedance during a reservoir stimulation; this, however, remains an entrepreneurial or political decision of the responsible project coordinators. We introduce forecast models based on the data set of an EGS experiment in the city of Basel. Between 2006 December 2 and 8, approximately 11 500 m3 of water was injected into a 5-km-deep well at high pressures. A six-sensor borehole array, was installed by the company Geothermal Explorers Limited (GEL) at depths between 300 and 2700 m around the well to monitor the induced seismicity. The network recorded approximately 11 200 events during the injection phase, more than 3500 of which were located. With the traffic-light system, actions where implemented after an ML 2.7 event, the water injection was reduced and then stopped after another ML 2.5 event. A few hours later, an earthquake with ML 3.4, felt within the city, occurred, which led to bleed-off of the well. A risk study was later issued with the outcome that the experiment could not be resumed. We analyse the statistical features of the sequence and show that the sequence is well modelled with the Omori-Utsu law following the termination of water injection. Based on this model, the sequence will last 31+29/-14 years to reach the background level. We introduce statistical models based on Reasenberg and Jones and Epidemic Type Aftershock Sequence (ETAS) models, commonly used to model aftershock sequences. We compare and test different model setups to simulate the sequences, varying the number of fixed and free parameters. For one class of the ETAS models, we account for the flow rate at the injection borehole. We test the models against the observed data with standard likelihood tests and find the ETAS model accounting for the on flow rate to perform best. Such a model may in future serve as a valuable tool for designing probabilistic alarm systems for EGS experiments.

  4. Can cyclist safety be improved with intelligent transport systems?

    PubMed

    Silla, Anne; Leden, Lars; Rämä, Pirkko; Scholliers, Johan; Van Noort, Martijn; Bell, Daniel

    2017-08-01

    In recent years, Intelligent Transport Systems (ITS) have assisted in the decrease of road traffic fatalities, particularly amongst passenger car occupants. Vulnerable Road Users (VRUs) such as pedestrians, cyclists, moped riders and motorcyclists, however, have not been that much in focus when developing ITS. Therefore, there is a clear need for ITS which specifically address VRUs as an integrated element of the traffic system. This paper presents the results of a quantitative safety impact assessment of five systems that were estimated to have high potential to improve the safety of cyclists, namely: Blind Spot Detection (BSD), Bicycle to Vehicle communication (B2V), Intersection safety (INS), Pedestrian and Cyclist Detection System+Emergency Braking (PCDS+EBR) and VRU Beacon System (VBS). An ex-ante assessment method proposed by Kulmala (2010) targeted to assess the effects of ITS for cars was applied and further developed in this study to assess the safety impacts of ITS specifically designed for VRUs. The main results of the assessment showed that all investigated systems affect cyclist safety in a positive way by preventing fatalities and injuries. The estimates considering 2012 accident data and full penetration showed that the highest effects could be obtained by the implementation of PCDS+EBR and B2V, whereas VBS had the lowest effect. The estimated yearly reduction in cyclist fatalities in the EU-28 varied between 77 and 286 per system. A forecast for 2030, taking into accounts the estimated accident trends and penetration rates, showed the highest effects for PCDS+EBR and BSD. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. The String Stability of a Trajectory-Based Interval Management Algorithm in the Midterm Airspace

    NASA Technical Reports Server (NTRS)

    Swieringa, Kurt A.

    2015-01-01

    NASA's first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature ATM technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise time-based scheduling in the terminal airspace; Controller Managed Spacing (CMS), which provides terminal controllers with decision support tools enabling precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain a precise spacing interval behind a target aircraft. As the percentage of IM equipped aircraft increases, controllers may provide IM clearances to sequences, or strings, of IM-equipped aircraft. It is important for these strings to maintain stable performance. This paper describes an analytic analysis of the string stability of the latest version of NASA's IM algorithm and a fast-time simulation designed to characterize the string performance of the IM algorithm. The analytic analysis showed that the spacing algorithm has stable poles, indicating that a spacing error perturbation will be reduced as a function of string position. The fast-time simulation investigated IM operations at two airports using constraints associated with the midterm airspace, including limited information of the target aircraft's intended speed profile and limited information of the wind forecast on the target aircraft's route. The results of the fast-time simulation demonstrated that the performance of the spacing algorithm is acceptable for strings of moderate length; however, there is some degradation in IM performance as a function of string position.

  6. Time series models for prediction the total and dissolved heavy metals concentration in road runoff and soil solution of roadside embankments

    NASA Astrophysics Data System (ADS)

    Aljoumani, Basem; Kluge, Björn; sanchez, Josep; Wessolek, Gerd

    2017-04-01

    Highways and main roads are potential sources of contamination for the surrounding environment. High traffic rates result in elevated heavy metal concentrations in road runoff, soil and water seepage, which has attracted much attention in the recent past. Prediction of heavy metals transfer near the roadside into deeper soil layers are very important to prevent the groundwater pollution. This study was carried out on data of a number of lysimeters which were installed along the A115 highway (Germany) with a mean daily traffic of 90.000 vehicles per day. Three polyethylene (PE) lysimeters were installed at the A115 highway. They have the following dimensions: length 150 cm, width 100 cm, height 60 cm. The lysimeters were filled with different soil materials, which were recently used for embankment construction in Germany. With the obtained data, we will develop a time series analysis model to predict total and dissolved metal concentration in road runoff and in soil solution of the roadside embankments. The time series consisted of monthly measurements of heavy metals and was transformed to a stationary situation. Subsequently, the transformed data will be used to conduct analyses in the time domain in order to obtain the parameters of a seasonal autoregressive integrated moving average (ARIMA) model. Four phase approaches for identifying and fitting ARIMA models will be used: identification, parameter estimation, diagnostic checking, and forecasting. An automatic selection criterion, such as the Akaike information criterion, will use to enhance this flexible approach to model building

  7. Anuran road-kills neighboring a peri-urban reserve in the Atlantic Forest, Brazil.

    PubMed

    Coelho, Igor Pfeifer; Teixeira, Fernanda Zimmermann; Colombo, Patrick; Coelho, Artur Vicente Pfeifer; Kindel, Andreas

    2012-12-15

    Mortality from road-kills may figure among the important causes of decline in amphibian populations and species extinctions worldwide. Evaluation of the magnitude, composition, and temporal and spatial distributions of amphibian road-kills is a key step for mitigation planning, especially in peri-urban reserves. Once a month for 16 months, we surveyed, on foot, a 4.4 km section of state road ERS-389 bordering the Itapeva reserve in the southern Atlantic Forest. We recorded 1433 anuran road-kills and estimated a mortality rate of 9002 road-kills/km/year. The species most often recorded were the largest ones: Leptodactylus latrans, Rhinella icterica, Leptodactylus gracilis and Hypsiboas faber; 54.5% of the carcasses could not be identified. Anuran mortality was concentrated in summer, and was associated with temperature, rainfall and photoperiod. Leptodactylus road-kills were strongly influenced by vehicle traffic, probably because of its high abundance during the entire study period. Road-kill hotspots differed for anurans as a group and for single species, and we found an association among spatial patterns of mortality and types of land cover, distance from the nearest waterbody, roadside ditches, and artificial light. Traffic should be banned temporarily during periods of high mortality, which can be forecasted based on meteorological data. A comprehensive mitigation approach should take into account hotspots of all anuran records, and also of target species for selecting locations for amphibian passages and fencing. Roadside ditches, artificial waterbodies, and conventional street lights should be reduced as much as possible, since they may represent ecological traps for anuran populations. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. Movement of Goods, Services and People: Entanglements with Sustainability Implications

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Southworth, Frank; Wigan, Marcus

    2008-01-01

    In both Europe and North America the continued growth in both passenger and freight traffic promises growing competition for road space between these two forms of travel. Forecast traffic levels call into question the ability of current infrastructures to sustain the efficient movement of both goods and people over increasingly crowded roadways and through increasingly delay-prone terminals. Costs of maintaining current highway networks in the face of heavy truck use also limit the budgets available for capacity expansion. In this paper the authors examine potential areas of both conflict and synergy in the movement of goods and people and considermore » the sort of data and analytical tools available for understanding the needs of, in particular, mixed use highway systems. Similarities in the movement of goods and people within urban areas exist on both continents, suggesting a number of promising areas for complementary research efforts.Limited data on the intra-urban activities of commercial vehicles is identified as a major barrier to our current understanding of how best to use available road space, and this too is a common situation on both continents. In contrast, the different histories, geographies and population densities associated with inter-city transportation activities make comparative work in this area more difficult and may suggest different modal solutionson the two continents. In either case the authors argue that there is considerable value atthe present time in predicting the present especially as it applies to the functional linkages between personal, goods and a rapidly growing services transport sector.« less

  9. Conflict Resolution for Wind-Optimal Aircraft Trajectories in North Atlantic Oceanic Airspace with Wind Uncertainties

    NASA Technical Reports Server (NTRS)

    Rodionova, Olga; Sridhar, Banavar; Ng, Hok K.

    2016-01-01

    Air traffic in the North Atlantic oceanic airspace (NAT) experiences very strong winds caused by jet streams. Flying wind-optimal trajectories increases individual flight efficiency, which is advantageous when operating in the NAT. However, as the NAT is highly congested during peak hours, a large number of potential conflicts between flights are detected for the sets of wind-optimal trajectories. Conflict resolution performed at the strategic level of flight planning can significantly reduce the airspace congestion. However, being completed far in advance, strategic planning can only use predicted environmental conditions that may significantly differ from the real conditions experienced further by aircraft. The forecast uncertainties result in uncertainties in conflict prediction, and thus, conflict resolution becomes less efficient. This work considers wind uncertainties in order to improve the robustness of conflict resolution in the NAT. First, the influence of wind uncertainties on conflict prediction is investigated. Then, conflict resolution methods accounting for wind uncertainties are proposed.

  10. Method for Assessing Risk of Road Accidents in Transportation of School Children

    NASA Astrophysics Data System (ADS)

    Pogotovkina, N. S.; Volodkin, P. P.; Demakhina, E. S.

    2017-11-01

    The rationale behind the problem being investigated is explained by the remaining high level of the accident rates with the participation of vehicles carrying groups of children, including school buses, in the Russian Federation over the period of several years. The article is aimed at the identification of new approaches to improve the safety of transportation of schoolchildren in accordance with the Concept of children transportation by buses and the plan for its implementation. The leading approach to solve the problem under consideration is the prediction of accidents in the schoolchildren transportation. The article presents the results of the accident rate analysis with the participation of school buses in the Russian Federation for five years. Besides, a system to monitor the transportation of schoolchildren is proposed; the system will allow analyzing and forecasting traffic accidents which involve buses carrying groups of children, including school buses. In addition, the article presents a methodology for assessing the risk of road accidents during the transportation of schoolchildren.

  11. Graphene photodetectors with a bandwidth  >76 GHz fabricated in a 6″ wafer process line

    NASA Astrophysics Data System (ADS)

    Schall, Daniel; Porschatis, Caroline; Otto, Martin; Neumaier, Daniel

    2017-03-01

    In recent years, the data traffic has grown exponentially and the forecasts indicate a huge market that could be addressed by communication infrastructure and service providers. However, the processing capacity, space, and energy consumption of the available technology is a serious bottleneck for the exploitation of these markets. Chip-integrated optical communication systems hold the promise of significantly improving these issues related to the current technology. At the moment, the answer to the question which material is best suited for ultrafast chip integrated communication systems is still open. In this manuscript we report on ultrafast graphene photodetectors with a bandwidth of more than 76 GHz well suitable for communication links faster than 100 GBit s-1 per channel. We extract an upper value of 7.2 ps for the timescale in which the bolometric photoresponse in graphene is generated. The photodetectors were fabricated on 6″ silicon-on-insulator wafers in a semiconductor pilot line, demonstrating the scalable fabrication of high-performance graphene based devices.

  12. Improving Prediction Accuracy for WSN Data Reduction by Applying Multivariate Spatio-Temporal Correlation

    PubMed Central

    Carvalho, Carlos; Gomes, Danielo G.; Agoulmine, Nazim; de Souza, José Neuman

    2011-01-01

    This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction. PMID:22346626

  13. A Fuel-Efficient Conflict Resolution Maneuver for Separation Assurance

    NASA Technical Reports Server (NTRS)

    Bowe, Aisha Ruth; Santiago, Confesor

    2012-01-01

    Automated separation assurance algorithms are envisioned to play an integral role in accommodating the forecasted increase in demand of the National Airspace System. Developing a robust, reliable, air traffic management system involves safely increasing efficiency and throughput while considering the potential impact on users. This experiment seeks to evaluate the benefit of augmenting a conflict detection and resolution algorithm to consider a fuel efficient, Zero-Delay Direct-To maneuver, when resolving a given conflict based on either minimum fuel burn or minimum delay. A total of twelve conditions were tested in a fast-time simulation conducted in three airspace regions with mixed aircraft types and light weather. Results show that inclusion of this maneuver has no appreciable effect on the ability of the algorithm to safely detect and resolve conflicts. The results further suggest that enabling the Zero-Delay Direct-To maneuver significantly increases the cumulative fuel burn savings when choosing resolution based on minimum fuel burn while marginally increasing the average delay per resolution.

  14. Self-Nowcast Model of extreme precipitation events for operational meteorology

    NASA Astrophysics Data System (ADS)

    França, G. B.; de Almeida, M. V.; Rosette, A. C.

    2015-10-01

    Nowadays many social activities require short-term (one to two hours) and local area forecasts of extreme weather. In particular, air traffic systems have been studying how to minimize the impact of meteorological events, such as turbulence, wind shear, ice, and heavy rain, which are related to the presence of convective systems during all flight phases. This paper presents an alternative self-nowcast model, based on neural network techniques, to produce short-term and local-specific forecasts of extreme meteorological events in the area of the landing and take-off region of Galeão, the principal airport in Rio de Janeiro, Brazil. Twelve years of data were used for neural network training and validation. Data are originally from four sources: (1) hourly meteorological observations from surface meteorological stations at five airports distributed around the study area, (2) atmospheric profiles collected twice a day at the meteorological station at Galeão Airport, (3) rain rate data collected from a network of twenty-nine rain gauges in the study area; and (4) lightning data regularly collected by national detection networks. An investigation was done about the capability of a neural network to produce early warning signs - or as a nowcasting tool - for extreme meteorological events. The self-nowcast model was validated using results from six categorical statistics, indicated in parentheses for forecasts of the first, second, and third hours, respectively, namely: proportion correct (0.98, 0.96, and 0.94), bias (1.37, 1.48, and 1.83), probability of detection (0.84, 0.80, and 0.76), false-alarm ratio (0.38, 0.46, and 0.58), and threat score (0.54, 0.47, and 0.37). Possible sources of error related to the validation procedure are discussed. Two key points have been identified in which there is a possibility of error: i.e., subjectivity on the part of the meteorologist making the observation, and a rain gauge measurement error of about 20 % depending on wind speed. The latter was better demonstrated when lightning data were included in the validation. The validation showed that the proposed model's performance was quite encouraging for the first and second hours.

  15. Regional model studies of the atmospheric dispersion of fine volcanic ash after the eruption of Eyjafjallajoekull

    NASA Astrophysics Data System (ADS)

    Langmann, B.; Hort, M. K.

    2010-12-01

    During the eruption of Eyjafjallajoekull on Iceland in April/May 2010 air traffic over Europe was repeatedly interrupted because of volcanic ash in the atmosphere. This completely unusual situation in Europe leads to the demand of improved crisis management, e.g. European wide regulations of volcanic ash thresholds and improved forecasts of theses thresholds. However, the quality of the forecast of fine volcanic ash concentrations in the atmosphere depends to a great extent on a realistic description of the erupted mass flux of fine ash particles, which is rather uncertain. Numerous aerosol measurements (ground based and satellite remote sensing, and in situ measurements) all over Europe have tracked the volcanic ash clouds during the eruption of Eyjafjallajoekull offering the possibility for an interdisciplinary effort between volcanologists and aerosol researchers to analyse the release and dispersion of fine volcanic ash in order to better understand the needs for realistic volcanic ash forecasts. This contribution describes the uncertainties related to the amount of fine volcanic ash released from Eyjafjallajoekull and its influence on the dispersion of volcanic ash over Europe by numerical modeling. We use the three-dimensional Eulerian atmosphere-chemistry/aerosol model REMOTE (Langmann et al., 2008) to simulate the distribution of volcanic ash as well as its deposition after the eruptions of Eyjafjallajoekull during April and May 2010. The model has been used before to simulate the fate of the volcanic ash after the volcanic eruptions of Kasatochi in 2008 (Langmann et al., 2010) and Mt. Pinatubo in 1991. Comparing our model results with available measurements for the Eyjafjallajoekull eruption we find a quite good agreement with available ash concentrations data measured over Europe as well as with the results from other models. Langmann, B., K. Zakšek and M. Hort, Atmospheric distribution and removal of volcanic ash after the eruption of Kasatochi volcano: A regional model study, J. Geophys. Res., 115, D00L06, doi:10.1029/2009JD013298, 2010. Langmann, B., S. Varghese, E. Marmer, E. Vignati, J. Wilson, P. Stier and C. O’Dowd, Aerosol distribution over Europe: A model evaluation study with detailed aerosol microphysics, Atmos. Chem. Phys. 8, 1591-1607, 2008.

  16. Refinement of pollutant gas emissions in the state of Rio de Janeiro for applications in modeling air quality on a local scale

    NASA Astrophysics Data System (ADS)

    Domínguez Chovert, Angel; Félix Alonso, Marcelo; Frassoni, Ariane; José Ferreira, Valter; Eiras, Denis; Longo, Karla; Freitas, Saulo

    2017-04-01

    Numerical modeling is a fundamental tool for studying the earth system components along with weather and climate forecast. In fact, the development of on-line models allows to simulate conditions of the atmosphere, for example, to evaluate certain chemicals in weather events with the purpose of improving a region's quality of air. For this determined purpose, the on-line models employ information from a broad range of sources in order to generate its variables forecasts. But beyond vast information sources, for a region's quality of air study, the data concerning the amount and distribution of emissions of polluting gases must be representative, as well as, it's required complete georeferenced emissions for simulations made with high resolution. Consequently, the modifications made in this work to the PREP-CHEM-SRC (Preprocessor of trace gas and aerosol emission fields for regional and a global atmospheric chemistry models) tool are presented to meliorate the initialization files for BRAMS models, 5.2 version (Brazilian Developments on the Regional Atmospheric Modeling System) and WRF (Weather Research and Forecasting Model) with vehicle emissions in the state of Rio de Janeiro, Brazil. It was determined the annual vehicle emission, until the year 2030, of the nitrogen oxides species (NOx) and carbon monoxide (CO) for each city and using different scenarios. For Rio de Janeiro city, a process of distribution by emissions of the main pollutant gases was implemented. In total, five different types of routes were used and the emission percentage for each one was calculated using the most current traffic information in them. For to check the industrial contributions to the emissions were used the global datasets RETRO (REanalysis of TROpospheric chemical composition) and EDGAR-HTAP (Emission Database for Global Atmospheric Research). On the other hand, for the biogenic contributions was used information from the MEGAN model (Model of Emissions of Gases and Aerosols from Nature). For all the analyzed species it was possible to observe the strong influence of the vehicular activity on the emission distribution.

  17. Fog Simulations Based on Multi-Model System: A Feasibility Study

    NASA Astrophysics Data System (ADS)

    Shi, Chune; Wang, Lei; Zhang, Hao; Zhang, Su; Deng, Xueliang; Li, Yaosun; Qiu, Mingyan

    2012-05-01

    Accurate forecasts of fog and visibility are very important to air and high way traffic, and are still a big challenge. A 1D fog model (PAFOG) is coupled to MM5 by obtaining the initial and boundary conditions (IC/BC) and some other necessary input parameters from MM5. Thus, PAFOG can be run for any area of interest. On the other hand, MM5 itself can be used to simulate fog events over a large domain. This paper presents evaluations of the fog predictability of these two systems for December of 2006 and December of 2007, with nine regional fog events observed in a field experiment, as well as over a large domain in eastern China. Among the simulations of the nine fog events by the two systems, two cases were investigated in detail. Daily results of ground level meteorology were validated against the routine observations at the CMA observational network. Daily fog occurrences for the two study periods was validated in Nanjing. General performance of the two models for the nine fog cases are presented by comparing with routine and field observational data. The results of MM5 and PAFOG for two typical fog cases are verified in detail against field observations. The verifications demonstrated that all methods tended to overestimate fog occurrence, especially for near-fog cases. In terms of TS/ETS, the LWC-only threshold with MM5 showed the best performance, while PAFOG showed the worst. MM5 performed better for advection-radiation fog than for radiation fog, and PAFOG could be an alternative tool for forecasting radiation fogs. PAFOG did show advantages over MM5 on the fog dissipation time. The performance of PAFOG highly depended on the quality of MM5 output. The sensitive runs of PAFOG with different IC/BC showed the capability of using MM5 output to run the 1D model and the high sensitivity of PAFOG on cloud cover. Future works should intensify the study of how to improve the quality of input data (e.g. cloud cover, advection, large scale subsidence) for the 1D model, particularly how to eliminate near-fog case in fog forecasting.

  18. Expanding the Operational Use of Total Lightning Ahead of GOES-R

    NASA Technical Reports Server (NTRS)

    Stano, Geoffrey T.; Wood, Lance; Garner, Tim; Nunez, Roland; Kann, Deirdre; Reynolds, James; Rydell, Nezette; Cox, Rob; Bobb, William R.

    2015-01-01

    NASA's Short-term Prediction Research and Transition Center (SPoRT) has been transitioning real-time total lightning observations from ground-based lightning mapping arrays since 2003. This initial effort was with the local Weather Forecast Offices (WFO) that could use the North Alabama Lightning Mapping Array (NALMA). These early collaborations established a strong interest in the use of total lightning for WFO operations. In particular the focus started with warning decision support, but has since expanded to include impact-based decision support and lightning safety. SPoRT has used its experience to establish connections with new lightning mapping arrays as they become available. The GOES-R / JPSS Visiting Scientist Program has enabled SPoRT to conduct visits to new partners and expand the number of operational users with access to total lightning observations. In early 2014, SPoRT conducted the most recent visiting scientist trips to meet with forecast offices that will used the Colorado, Houston, and Langmuir Lab (New Mexico) lightning mapping arrays. In addition, SPoRT met with the corresponding Center Weather Service Units (CWSUs) to expand collaborations with the aviation community. These visits were an opportunity to learn about the forecast needs of each office visited as well as to provide on-site training for the use of total lightning, setting the stage for a real-time assessment during May-July 2014. With five lightning mapping arrays covering multiple geographic locations, the 2014 assessment has demonstrated numerous uses of total lightning in varying situations. Several highlights include a much broader use of total lightning for impact-based decision support ranging from airport weather warnings, supporting fire crews, and protecting large outdoor events. The inclusion of the CWSUs has broadened the operational scope of total lightning, demonstrating how these data can support air traffic management, particularly in the Terminal Radar Approach Control Facilities (TRACON) region around an airport. These collaborations continue to demonstrate, from the operational perspective, the utility of total lightning and the importance of continued training and preparation in advance of the Geostationary Lightning Mapper.

  19. Development of a Healthy Urban Route Planner for cyclists and pedestrians in Amsterdam

    NASA Astrophysics Data System (ADS)

    van der Molen, Michiel; Ligtenberg, Arend; Vreugdenhil, Corne; Steeneveld, Gert-Jan

    2017-04-01

    Cities are hotspots of air pollution and heat stress, the exposure to which results in nuisance, health risks, cost of medication, reduced labour productivity and sick leave for citizens. Yet the air pollution and heat stress are spatially and temporally unevenly distributed over the city, depending on pollutant emissions, street design and atmospheric turbulent mixing and radiation. This spatiotemporal variation allows pedestrians and bikers to choose alternative routes to minimize their exposure, if the distribution is known. In this project, we develop a route planner for bicyclists and pedestrians for Amsterdam (NL), that proposes routes and departure times based on model simulations of weather and air quality. We use the WRF-Chem atmosphere and air quality model at unprecedented grid spacing of 100-m (Ronda et al, 2015, Super et al, 2016), with an underlying urban canopy model and NOx and PM10 emissions. The emissions by traffic are calculated based on observed traffic intensities and emission factors. An urban land use map will characterize urban density and street configuration to estimate urban heat storage (Attema et al, 2015). WRF-Chem runs will be issued daily for a lead time of 48 hours, resulting in forecast maps of temperature and pollutant concentrations that will be uniquely expressed in a metric that combines both threats. The hourly fields of this metric are provided to the route planner based on the open source routing library pgRouting to identify the more healthy routes on the route network of Amsterdam. The objectives of the healthy urban route planner are to raise awareness of heat and air quality issues in Amsterdam, to provide an innovative adaptation tool for citizens and tourists, to locate the most important bottlenecks in (the exposure to) air pollution and heat stress, and ultimately to test the readiness of the travellers to use the information and adapt the route. We expect to particularly target a group of lung- and cardiovascular patients, and elderly people. In the future the planner will be expanded with pollen information and possibly with real-time traffic information.

  20. Emissions from international shipping: 2. Impact of future technologies on scenarios until 2050

    NASA Astrophysics Data System (ADS)

    Eyring, V.; KöHler, H. W.; Lauer, A.; Lemper, B.

    2005-09-01

    In this study the today's fleet-average emission factors of the most important ship exhausts are used to calculate emission scenarios for the future. To develop plausible future technology scenarios, first upcoming regulations and compliance with future regulations through technological improvements are discussed. We present geographically resolved emission inventory scenarios until 2050, based on a mid-term prognosis for 2020 and a long-term prognosis for 2050. The scenarios are based on some very strict assumptions on future ship traffic demands and technological improvements. The four future ship traffic demand scenarios are mainly determined by the economic growth, which follows the IPCC SRES storylines. The resulting fuel consumption is projected through extrapolations of historical trends in economic growth, total seaborne trade and number of ships, as well as the average installed power per ship. For the future technology scenarios we assume a diesel-only fleet in 2020 resulting in fuel consumption between 382 and 409 million metric tons (Mt). For 2050 one technology scenario assumes that 25% of the fuel consumed by a diesel-only fleet can be saved by applying future alternative propulsion plants, resulting in a fuel consumption that varies between 402 and 543 Mt. The other scenario is a business-as-usual scenario for a diesel-only fleet even in 2050 and gives an estimate between 536 and 725 Mt. Dependent on how rapid technology improvements for diesel engines are introduced, possible technology reduction factors are applied to the today's fleet-average emission factors of all important species to estimate future ship emissions. Combining the four traffic demand scenarios with the four technology scenarios, our results suggest emissions between 8.8 and 25.0 Tg (NO2) in 2020, and between 3.1 to 38.8 Tg (NO2) in 2050. The development of forecast scenarios for CO2, NOx, SOx, CO, hydrocarbons, and particulate matter is driven by the requirements for global model studies of the effects of these emissions on the chemical composition of the atmosphere and on climate. The developed scenarios are suitable for use as input for chemical transport models (CTMs) and coupled chemistry-climate models (CCMs).

  1. The meta-Gaussian Bayesian Processor of forecasts and associated preliminary experiments

    NASA Astrophysics Data System (ADS)

    Chen, Fajing; Jiao, Meiyan; Chen, Jing

    2013-04-01

    Public weather services are trending toward providing users with probabilistic weather forecasts, in place of traditional deterministic forecasts. Probabilistic forecasting techniques are continually being improved to optimize available forecasting information. The Bayesian Processor of Forecast (BPF), a new statistical method for probabilistic forecast, can transform a deterministic forecast into a probabilistic forecast according to the historical statistical relationship between observations and forecasts generated by that forecasting system. This technique accounts for the typical forecasting performance of a deterministic forecasting system in quantifying the forecast uncertainty. The meta-Gaussian likelihood model is suitable for a variety of stochastic dependence structures with monotone likelihood ratios. The meta-Gaussian BPF adopting this kind of likelihood model can therefore be applied across many fields, including meteorology and hydrology. The Bayes theorem with two continuous random variables and the normal-linear BPF are briefly introduced. The meta-Gaussian BPF for a continuous predictand using a single predictor is then presented and discussed. The performance of the meta-Gaussian BPF is tested in a preliminary experiment. Control forecasts of daily surface temperature at 0000 UTC at Changsha and Wuhan stations are used as the deterministic forecast data. These control forecasts are taken from ensemble predictions with a 96-h lead time generated by the National Meteorological Center of the China Meteorological Administration, the European Centre for Medium-Range Weather Forecasts, and the US National Centers for Environmental Prediction during January 2008. The results of the experiment show that the meta-Gaussian BPF can transform a deterministic control forecast of surface temperature from any one of the three ensemble predictions into a useful probabilistic forecast of surface temperature. These probabilistic forecasts quantify the uncertainty of the control forecast; accordingly, the performance of the probabilistic forecasts differs based on the source of the underlying deterministic control forecasts.

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  3. Weather forecasting expert system study

    NASA Technical Reports Server (NTRS)

    1985-01-01

    Weather forecasting is critical to both the Space Transportation System (STS) ground operations and the launch/landing activities at NASA Kennedy Space Center (KSC). The current launch frequency places significant demands on the USAF weather forecasters at the Cape Canaveral Forecasting Facility (CCFF), who currently provide the weather forecasting for all STS operations. As launch frequency increases, KSC's weather forecasting problems will be great magnified. The single most important problem is the shortage of highly skilled forecasting personnel. The development of forecasting expertise is difficult and requires several years of experience. Frequent personnel changes within the forecasting staff jeopardize the accumulation and retention of experience-based weather forecasting expertise. The primary purpose of this project was to assess the feasibility of using Artificial Intelligence (AI) techniques to ameliorate this shortage of experts by capturing aria incorporating the forecasting knowledge of current expert forecasters into a Weather Forecasting Expert System (WFES) which would then be made available to less experienced duty forecasters.

  4. Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Sensor Validation and Verification on National Oceanographic and Atmospheric Administration (NOAA) Lockheed WP-3D Aircraft

    NASA Technical Reports Server (NTRS)

    Tsoucalas, George; Daniels, Taumi S.; Zysko, Jan; Anderson, Mark V.; Mulally, Daniel J.

    2010-01-01

    As part of the National Aeronautics and Space Administration's Aviation Safety and Security Program, the Tropospheric Airborne Meteorological Data Reporting project (TAMDAR) developed a low-cost sensor for aircraft flying in the lower troposphere. This activity was a joint effort with support from Federal Aviation Administration, National Oceanic and Atmospheric Administration, and industry. This paper reports the TAMDAR sensor performance validation and verification, as flown on board NOAA Lockheed WP-3D aircraft. These flight tests were conducted to assess the performance of the TAMDAR sensor for measurements of temperature, relative humidity, and wind parameters. The ultimate goal was to develop a small low-cost sensor, collect useful meteorological data, downlink the data in near real time, and use the data to improve weather forecasts. The envisioned system will initially be used on regional and package carrier aircraft. The ultimate users of the data are National Centers for Environmental Prediction forecast modelers. Other users include air traffic controllers, flight service stations, and airline weather centers. NASA worked with an industry partner to develop the sensor. Prototype sensors were subjected to numerous tests in ground and flight facilities. As a result of these earlier tests, many design improvements were made to the sensor. The results of tests on a final version of the sensor are the subject of this report. The sensor is capable of measuring temperature, relative humidity, pressure, and icing. It can compute pressure altitude, indicated air speed, true air speed, ice presence, wind speed and direction, and eddy dissipation rate. Summary results from the flight test are presented along with corroborative data from aircraft instruments.

  5. Near-real time forecasts of MeV protons based on sub-relativistic electrons: communicating the outputs to the end users

    NASA Astrophysics Data System (ADS)

    Sarlanis, Christos; Heber, Bernd; Labrenz, Johannes; Kühl, Patrick; Marquardt, Johannes; Dimitroulakos, John; Papaioannou, Athanasios; Posner, Arik

    2017-04-01

    Solar Energetic Particle (SEP) events are one of the most important elements of space weather. Given that the complexity of the underlying physical processes of the acceleration and propagation of SEP events is still a very active research area, the prognosis of SEP event occurrence and their corresponding characteristics remains challenging. In order to provide up to an hour warning time before these particles arrive at Earth, relativistic electron and below 50 MeV proton data from the Electron Proton Helium Instrument (EPHIN) on SOHO were used to implement the 'Relativistic Electron Alert System for Exploration (REleASE)'. The REleASE forecasting scheme was recently rewritten in the open access programming language PYTHON and will be made publicly available. As a next step, along with relativistic electrons (v > 0.9 c) provided by SOHO, near-relativistic (v <0.8 c) electron measurements from other instruments like the Electron Proton Alpha Monitor (EPAM) aboard the Advanced Composition Explorer (ACE) have been utilized. In this work, we demonstrate the real-time outputs derived by the end user from the REleASE using both SOHO/EPHIN and ACE/EPAM. We further, show a user friendly illustration of the outputs that make use of a "traffic light" to monitor the different warning stages: quiet, warning, alert offering a simple guidance to the end users. Finally, the capabilities offered by this new system, accessing both the pictorial and textural outputs REleASE are being presented. This work has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 637324.

  6. NWS Alaska Sea Ice Program: Operations and Decision Support Services

    NASA Astrophysics Data System (ADS)

    Schreck, M. B.; Nelson, J. A., Jr.; Heim, R.

    2015-12-01

    The National Weather Service's Alaska Sea Ice Program is designed to service customers and partners operating and planning operations within Alaska waters. The Alaska Sea Ice Program offers daily sea ice and sea surface temperature analysis products. The program also delivers a five day sea ice forecast 3 times each week, provides a 3 month sea ice outlook at the end of each month, and has staff available to respond to sea ice related information inquiries. These analysis and forecast products are utilized by many entities around the state of Alaska and nationally for safety of navigation and community strategic planning. The list of current customers stem from academia and research institutions, to local state and federal agencies, to resupply barges, to coastal subsistence hunters, to gold dredgers, to fisheries, to the general public. Due to a longer sea ice free season over recent years, activity in the waters around Alaska has increased. This has led to a rise in decision support services from the Alaska Sea Ice Program. The ASIP is in constant contact with the National Ice Center as well as the United States Coast Guard (USCG) for safety of navigation. In the past, the ASIP provided briefings to the USCG when in support of search and rescue efforts. Currently, not only does that support remain, but our team is also briefing on sea ice outlooks into the next few months. As traffic in the Arctic increases, the ASIP will be called upon to provide more and more services on varying time scales to meet customer needs. This talk will address the many facets of the current Alaska Sea Ice Program as well as delve into what we see as the future of the ASIP.

  7. NWS Alaska Sea Ice Program: Operations, Customer Support & Challenges

    NASA Astrophysics Data System (ADS)

    Heim, R.; Schreck, M. B.

    2016-12-01

    The National Weather Service's Alaska Sea Ice Program is designed to service customers and partners operating and planning operations within Alaska waters. The Alaska Sea Ice Program offers daily sea ice and sea surface temperature analysis products. The program also delivers a five day sea ice forecast 3 times each week, provides a 3 month sea ice outlook at the end of each month, and has staff available to respond to sea ice related information inquiries. These analysis and forecast products are utilized by many entities around the state of Alaska and nationally for safety of navigation and community strategic planning. The list of current customers stem from academia and research institutions, to local state and federal agencies, to resupply barges, to coastal subsistence hunters, to gold dredgers, to fisheries, to the general public. Due to a longer sea ice free season over recent years, activity in the waters around Alaska has increased. This has led to a rise in decision support services from the Alaska Sea Ice Program. The ASIP is in constant contact with the National Ice Center as well as the United States Coast Guard (USCG) for safety of navigation. In the past, the ASIP provided briefings to the USCG when in support of search and rescue efforts. Currently, not only does that support remain, but our team is also briefing on sea ice outlooks into the next few months. As traffic in the Arctic increases, the ASIP will be called upon to provide more and more services on varying time scales to meet customer needs. This talk will address the many facets of the current Alaska Sea Ice Program as well as delve into what we see as the future of the ASIP.

  8. Automatized near-real-time short-term Probabilistic Volcanic Hazard Assessment of tephra dispersion before eruptions: BET_VHst for Vesuvius and Campi Flegrei during recent exercises

    NASA Astrophysics Data System (ADS)

    Selva, Jacopo; Costa, Antonio; Sandri, Laura; Rouwet, Dmtri; Tonini, Roberto; Macedonio, Giovanni; Marzocchi, Warner

    2015-04-01

    Probabilistic Volcanic Hazard Assessment (PVHA) represents the most complete scientific contribution for planning rational strategies aimed at mitigating the risk posed by volcanic activity at different time scales. The definition of the space-time window for PVHA is related to the kind of risk mitigation actions that are under consideration. Short temporal intervals (days to weeks) are important for short-term risk mitigation actions like the evacuation of a volcanic area. During volcanic unrest episodes or eruptions, it is of primary importance to produce short-term tephra fallout forecast, and frequently update it to account for the rapidly evolving situation. This information is obviously crucial for crisis management, since tephra may heavily affect building stability, public health, transportations and evacuation routes (airports, trains, road traffic) and lifelines (electric power supply). In this study, we propose a methodology named BET_VHst (Selva et al. 2014) for short-term PVHA of volcanic tephra dispersal based on automatic interpretation of measures from the monitoring system and physical models of tephra dispersal from all possible vent positions and eruptive sizes based on frequently updated meteorological forecasts. The large uncertainty at all the steps required for the analysis, both aleatory and epistemic, is treated by means of Bayesian inference and statistical mixing of long- and short-term analyses. The BET_VHst model is here presented through its implementation during two exercises organized for volcanoes in the Neapolitan area: MESIMEX for Mt. Vesuvius, and VUELCO for Campi Flegrei. References Selva J., Costa A., Sandri L., Macedonio G., Marzocchi W. (2014) Probabilistic short-term volcanic hazard in phases of unrest: a case study for tephra fallout, J. Geophys. Res., 119, doi: 10.1002/2014JB011252

  9. Improved prediction and tracking of volcanic ash clouds

    USGS Publications Warehouse

    Mastin, Larry G.; Webley, Peter

    2009-01-01

    During the past 30??years, more than 100 airplanes have inadvertently flown through clouds of volcanic ash from erupting volcanoes. Such encounters have caused millions of dollars in damage to the aircraft and have endangered the lives of tens of thousands of passengers. In a few severe cases, total engine failure resulted when ash was ingested into turbines and coating turbine blades. These incidents have prompted the establishment of cooperative efforts by the International Civil Aviation Organization and the volcanological community to provide rapid notification of eruptive activity, and to monitor and forecast the trajectories of ash clouds so that they can be avoided by air traffic. Ash-cloud properties such as plume height, ash concentration, and three-dimensional ash distribution have been monitored through non-conventional remote sensing techniques that are under active development. Forecasting the trajectories of ash clouds has required the development of volcanic ash transport and dispersion models that can calculate the path of an ash cloud over the scale of a continent or a hemisphere. Volcanological inputs to these models, such as plume height, mass eruption rate, eruption duration, ash distribution with altitude, and grain-size distribution, must be assigned in real time during an event, often with limited observations. Databases and protocols are currently being developed that allow for rapid assignment of such source parameters. In this paper, we summarize how an interdisciplinary working group on eruption source parameters has been instigating research to improve upon the current understanding of volcanic ash cloud characterization and predictions. Improved predictions of ash cloud movement and air fall will aid in making better hazard assessments for aviation and for public health and air quality. ?? 2008 Elsevier B.V.

  10. Safety and Convergence Analysis of Intersecting Aircraft Flows Under Decentralized Collision Avoidance

    NASA Astrophysics Data System (ADS)

    Dallal, Ahmed H.

    Safety is an essential requirement for air traffic management and control systems. Aircraft are not allowed to get closer to each other than a specified safety distance, to avoid any conflicts and collisions between aircraft. Forecast analysis predicts a tremendous increase in the number of flights. Subsequently, automated tools are needed to help air traffic controllers resolve air born conflicts. In this dissertation, we consider the problem of conflict resolution of aircraft flows with the assumption that aircraft are flowing through a fixed specified control volume at a constant speed. In this regard, several centralized and decentralized resolution rules have been proposed for path planning and conflict avoidance. For the case of two intersecting flows, we introduce the concept of conflict touches, and a collaborative decentralized conflict resolution rule is then proposed and analyzed for two intersecting flows. The proposed rule is also able to resolved airborne conflicts that resulted from resolving another conflict via the domino effect. We study the safety conditions under the proposed conflict resolution and collision avoidance rule. Then, we use Lyapunov analysis to analytically prove the convergence of conflict resolution dynamics under the proposed rule. The analysis show that, under the proposed conflict resolution rule, the system of intersecting aircraft flows is guaranteed to converge to safe, conflict free, trajectories within a bounded time. Simulations are provided to verify the analytically derived conclusions and study the convergence of the conflict resolution dynamics at different encounter angles. Simulation results show that lateral deviations taken by aircraft in each flow, to resolve conflicts, are bounded, and aircraft converged to safe and conflict free trajectories, within a finite time.

  11. Emissions of CO2 and criteria air pollutants from mobile sources: Insights from integrating real-time traffic data into local air quality models

    NASA Astrophysics Data System (ADS)

    Gately, Conor; Hutyra, Lucy

    2016-04-01

    In 2013, on-road mobile sources were responsible for over 26% of U.S. fossil fuel carbon dioxide (ffCO2) emissions, and over 34% of both CO and NOx emissions. However, accurate representations of these emissions at the scale of urban areas remains a difficult challenge. Quantifying emissions at the scale of local streets and highways is critical to provide policymakers with the information needed to develop appropriate mitigation strategies and to guide research into the underlying process that drive mobile emissions. Quantification of vehicle ffCO2 emissions at high spatial and temporal resolutions requires a detailed synthesis of data on traffic activity, roadway attributes, fleet characteristics and vehicle speeds. To accurately characterize criteria air pollutant emissions, information on local meteorology is also critical, as the temperature and relative humidity can affect emissions rates of these pollutants by as much as 400%. As the health impacts of air pollutants are more severe for residents living in close proximity (<500m) to road sources, it is critical that inventories of these emissions rely on highly resolved source data to locate potential hot-spots of exposure. In this study we utilize real-time GPS estimates of vehicle speeds to estimate ffCO2 and criteria air pollutant emissions at multiple spatial and temporal scales across a large metropolitan area. We observe large variations in emissions associated with diurnal activity patterns, congestion, sporting and civic events, and weather anomalies. We discuss the advantages and challenges of using highly-resolved source data to quantify emissions at a roadway scale, and the potential of this methodology for forecasting the air quality impacts of changes in infrastructure, urban planning policies, and regional climate.

  12. Emissions of CO2 and criteria air pollutants from mobile sources: Insights from integrating real-time traffic data into local air quality models

    NASA Astrophysics Data System (ADS)

    Gately, C.; Hutyra, L.; Sue Wing, I.; Peterson, S.; Janetos, A.

    2015-12-01

    In 2013, on-road mobile sources were responsible for over 26% of U.S. fossil fuel carbon dioxide (ffCO2) emissions, and over 34% of both CO and NOx emissions. However, accurate representations of these emissions at the scale of urban areas remains a difficult challenge. Quantifying emissions at the scale of local streets and highways is critical to provide policymakers with the information needed to develop appropriate mitigation strategies and to guide research into the underlying process that drive mobile emissions. Quantification of vehicle ffCO2 emissions at high spatial and temporal resolutions requires a detailed synthesis of data on traffic activity, roadway attributes, fleet characteristics and vehicle speeds. To accurately characterize criteria air pollutant emissions, information on local meteorology is also critical, as the temperature and relative humidity can affect emissions rates of these pollutants by as much as 400%. As the health impacts of air pollutants are more severe for residents living in close proximity (<500m) to road sources, it is critical that inventories of these emissions rely on highly resolved source data to locate potential hot-spots of exposure. In this study we utilize real-time GPS estimates of vehicle speeds to estimate ffCO2 and criteria air pollutant emissions at multiple spatial and temporal scales across a large metropolitan area. We observe large variations in emissions associated with diurnal activity patterns, congestion, sporting and civic events, and weather anomalies. We discuss the advantages and challenges of using highly-resolved source data to quantify emissions at a roadway scale, and the potential of this methodology for forecasting the air quality impacts of changes in infrastructure, urban planning policies, and regional climate.

  13. The combined Fog Monitoring System of ARPAV over the Veneto Region, Po Valley - Italy

    NASA Astrophysics Data System (ADS)

    Domenichini, F.; Rossa, A.; Zardini, F.; Monai, M.; Calza, M.; Della Valle, A.; Gaspari, V.

    2010-07-01

    The presence of fog is a frequent problem in the Po Valley. The consequent reduction in visibility has a strong impact on the road, air, ship and railway traffic. Both, fog monitoring and forecasting, constitute significant challenges, not least due to the high spatial and temporal variability of the phenomenon. ARPAV (Regional Agency for Environmental Prevention and Protection of Veneto) is the regional meteorological service of the north-eastern Italian region Veneto and, as such, is responsible for meteorological support to institutional and private users. Real-time visibility information over an extended area would represent an interesting product for road and transport safety. In the framework of the FP7 project Roadidea, (14 partners from 8 different countries, Dec 2007 - Aug 2010) on road safety and traffic control ARPAV developed pilot system for the fog monitoring. The main idea of this fog monitoring methodology is to merge information derived from different observation platforms, i.e. satellite low stratus cloud classification, direct visibility monitoring, statistical estimation of low visibility from meteorological parameters at the ground. This information is translated into probability maps of fog occurrence and information weight on a common grid (4x4 km) covering the flat portion of the region Veneto. These weights are used to combine the three data sources into the final fog probability map. A probabilistic verification applied to the fog monitoring product yields encouraging results, and is systematically more skillfull than the fog probabilities derived from the individual data sources. First real-time products are now available on the ARPAV Fog Pilot website for a group of specific users (motorway head office, road police, national railways and others) and are under testing.

  14. Interval Management with Spacing to Parallel Dependent Runways (IMSPIDR) Experiment and Results

    NASA Technical Reports Server (NTRS)

    Baxley, Brian T.; Swieringa, Kurt A.; Capron, William R.

    2012-01-01

    An area in aviation operations that may offer an increase in efficiency is the use of continuous descent arrivals (CDA), especially during dependent parallel runway operations. However, variations in aircraft descent angle and speed can cause inaccuracies in estimated time of arrival calculations, requiring an increase in the size of the buffer between aircraft. This in turn reduces airport throughput and limits the use of CDAs during high-density operations, particularly to dependent parallel runways. The Interval Management with Spacing to Parallel Dependent Runways (IMSPiDR) concept uses a trajectory-based spacing tool onboard the aircraft to achieve by the runway an air traffic control assigned spacing interval behind the previous aircraft. This paper describes the first ever experiment and results of this concept at NASA Langley. Pilots flew CDAs to the Dallas Fort-Worth airport using airspeed calculations from the spacing tool to achieve either a Required Time of Arrival (RTA) or Interval Management (IM) spacing interval at the runway threshold. Results indicate flight crews were able to land aircraft on the runway with a mean of 2 seconds and less than 4 seconds standard deviation of the air traffic control assigned time, even in the presence of forecast wind error and large time delay. Statistically significant differences in delivery precision and number of speed changes as a function of stream position were observed, however, there was no trend to the difference and the error did not increase during the operation. Two areas the flight crew indicated as not acceptable included the additional number of speed changes required during the wind shear event, and issuing an IM clearance via data link while at low altitude. A number of refinements and future spacing algorithm capabilities were also identified.

  15. Benefits Analysis of Multi-Center Dynamic Weather Routes

    NASA Technical Reports Server (NTRS)

    Sheth, Kapil; McNally, David; Morando, Alexander; Clymer, Alexis; Lock, Jennifer; Petersen, Julien

    2014-01-01

    Dynamic weather routes are flight plan corrections that can provide airborne flights more than user-specified minutes of flying-time savings, compared to their current flight plan. These routes are computed from the aircraft's current location to a flight plan fix downstream (within a predefined limit region), while avoiding forecasted convective weather regions. The Dynamic Weather Routes automation has been continuously running with live air traffic data for a field evaluation at the American Airlines Integrated Operations Center in Fort Worth, TX since July 31, 2012, where flights within the Fort Worth Air Route Traffic Control Center are evaluated for time savings. This paper extends the methodology to all Centers in United States and presents benefits analysis of Dynamic Weather Routes automation, if it was implemented in multiple airspace Centers individually and concurrently. The current computation of dynamic weather routes requires a limit rectangle so that a downstream capture fix can be selected, preventing very large route changes spanning several Centers. In this paper, first, a method of computing a limit polygon (as opposed to a rectangle used for Fort Worth Center) is described for each of the 20 Centers in the National Airspace System. The Future ATM Concepts Evaluation Tool, a nationwide simulation and analysis tool, is used for this purpose. After a comparison of results with the Center-based Dynamic Weather Routes automation in Fort Worth Center, results are presented for 11 Centers in the contiguous United States. These Centers are generally most impacted by convective weather. A breakdown of individual Center and airline savings is presented and the results indicate an overall average savings of about 10 minutes of flying time are obtained per flight.

  16. On statistical inference in time series analysis of the evolution of road safety.

    PubMed

    Commandeur, Jacques J F; Bijleveld, Frits D; Bergel-Hayat, Ruth; Antoniou, Constantinos; Yannis, George; Papadimitriou, Eleonora

    2013-11-01

    Data collected for building a road safety observatory usually include observations made sequentially through time. Examples of such data, called time series data, include annual (or monthly) number of road traffic accidents, traffic fatalities or vehicle kilometers driven in a country, as well as the corresponding values of safety performance indicators (e.g., data on speeding, seat belt use, alcohol use, etc.). Some commonly used statistical techniques imply assumptions that are often violated by the special properties of time series data, namely serial dependency among disturbances associated with the observations. The first objective of this paper is to demonstrate the impact of such violations to the applicability of standard methods of statistical inference, which leads to an under or overestimation of the standard error and consequently may produce erroneous inferences. Moreover, having established the adverse consequences of ignoring serial dependency issues, the paper aims to describe rigorous statistical techniques used to overcome them. In particular, appropriate time series analysis techniques of varying complexity are employed to describe the development over time, relating the accident-occurrences to explanatory factors such as exposure measures or safety performance indicators, and forecasting the development into the near future. Traditional regression models (whether they are linear, generalized linear or nonlinear) are shown not to naturally capture the inherent dependencies in time series data. Dedicated time series analysis techniques, such as the ARMA-type and DRAG approaches are discussed next, followed by structural time series models, which are a subclass of state space methods. The paper concludes with general recommendations and practice guidelines for the use of time series models in road safety research. Copyright © 2012 Elsevier Ltd. All rights reserved.

  17. Near real-time traffic routing

    NASA Technical Reports Server (NTRS)

    Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)

    2012-01-01

    A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

  18. Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hoff, Thomas Hoff; Kankiewicz, Adam

    Four major research objectives were completed over the course of this study. Three of the objectives were to evaluate three, new, state-of-the-art solar irradiance forecasting models. The fourth objective was to improve the California Independent System Operator’s (ISO) load forecasts by integrating behind-the-meter (BTM) PV forecasts. The three, new, state-of-the-art solar irradiance forecasting models included: the infrared (IR) satellite-based cloud motion vector (CMV) model; the WRF-SolarCA model and variants; and the Optimized Deep Machine Learning (ODML)-training model. The first two forecasting models targeted known weaknesses in current operational solar forecasts. They were benchmarked against existing operational numerical weather prediction (NWP)more » forecasts, visible satellite CMV forecasts, and measured PV plant power production. IR CMV, WRF-SolarCA, and ODML-training forecasting models all improved the forecast to a significant degree. Improvements varied depending on time of day, cloudiness index, and geographic location. The fourth objective was to demonstrate that the California ISO’s load forecasts could be improved by integrating BTM PV forecasts. This objective represented the project’s most exciting and applicable gains. Operational BTM forecasts consisting of 200,000+ individual rooftop PV forecasts were delivered into the California ISO’s real-time automated load forecasting (ALFS) environment. They were then evaluated side-by-side with operational load forecasts with no BTM-treatment. Overall, ALFS-BTM day-ahead (DA) forecasts performed better than baseline ALFS forecasts when compared to actual load data. Specifically, ALFS-BTM DA forecasts were observed to have the largest reduction of error during the afternoon on cloudy days. Shorter term 30 minute-ahead ALFS-BTM forecasts were shown to have less error under all sky conditions, especially during the morning time periods when traditional load forecasts often experience their largest uncertainties. This work culminated in a GO decision being made by the California ISO to include zonal BTM forecasts into its operational load forecasting system. The California ISO’s Manager of Short Term Forecasting, Jim Blatchford, summarized the research performed in this project with the following quote: “The behind-the-meter (BTM) California ISO region forecasting research performed by Clean Power Research and sponsored by the Department of Energy’s SUNRISE program was an opportunity to verify value and demonstrate improved load forecast capability. In 2016, the California ISO will be incorporating the BTM forecast into the Hour Ahead and Day Ahead load models to look for improvements in the overall load forecast accuracy as BTM PV capacity continues to grow.”« less

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

    NASA Astrophysics Data System (ADS)

    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 the commencement of a forecast season. The system would allow for forecasts to be updated if necessary.

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

    NASA Astrophysics Data System (ADS)

    Christensen, Hannah; Moroz, Irene; Palmer, Tim

    2015-04-01

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

  1. Value of long-term streamflow forecast to reservoir operations for water supply in snow-dominated catchments

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Anghileri, Daniela; Voisin, Nathalie; Castelletti, Andrea F.

    In this study, we develop a forecast-based adaptive control framework for Oroville reservoir, California, to assess the value of seasonal and inter-annual forecasts for reservoir operation.We use an Ensemble Streamflow Prediction (ESP) approach to generate retrospective, one-year-long streamflow forecasts based on the Variable Infiltration Capacity hydrology model. The optimal sequence of daily release decisions from the reservoir is then determined by Model Predictive Control, a flexible and adaptive optimization scheme.We assess the forecast value by comparing system performance based on the ESP forecasts with that based on climatology and a perfect forecast. In addition, we evaluate system performance based onmore » a synthetic forecast, which is designed to isolate the contribution of seasonal and inter-annual forecast skill to the overall value of the ESP forecasts.Using the same ESP forecasts, we generalize our results by evaluating forecast value as a function of forecast skill, reservoir features, and demand. Our results show that perfect forecasts are valuable when the water demand is high and the reservoir is sufficiently large to allow for annual carry-over. Conversely, ESP forecast value is highest when the reservoir can shift water on a seasonal basis.On average, for the system evaluated here, the overall ESP value is 35% less than the perfect forecast value. The inter-annual component of the ESP forecast contributes 20-60% of the total forecast value. Improvements in the seasonal component of the ESP forecast would increase the overall ESP forecast value between 15 and 20%.« less

  2. Improved Anvil Forecasting

    NASA Technical Reports Server (NTRS)

    Lambert, Winifred C.

    2000-01-01

    This report describes the outcome of Phase 1 of the AMU's Improved Anvil Forecasting task. Forecasters in the 45th Weather Squadron and the Spaceflight Meteorology Group have found that anvil forecasting is a difficult task when predicting LCC and FR violations. The purpose of this task is to determine the technical feasibility of creating an anvil-forecasting tool. Work on this study was separated into three steps: literature search, forecaster discussions, and determination of technical feasibility. The literature search revealed no existing anvil-forecasting techniques. However, there appears to be growing interest in anvils in recent years. If this interest continues to grow, more information will be available to aid in developing a reliable anvil-forecasting tool. The forecaster discussion step revealed an array of methods on how better forecasting techniques could be developed. The forecasters have ideas based on sound meteorological principles and personal experience in forecasting and analyzing anvils. Based on the information gathered in the discussions with the forecasters, the conclusion of this report is that it is technically feasible at this time to develop an anvil forecasting technique that will significantly contribute to the confidence in anvil forecasts.

  3. Flare forecasting at the Met Office Space Weather Operations Centre

    NASA Astrophysics Data System (ADS)

    Murray, S. A.; Bingham, S.; Sharpe, M.; Jackson, D. R.

    2017-04-01

    The Met Office Space Weather Operations Centre produces 24/7/365 space weather guidance, alerts, and forecasts to a wide range of government and commercial end-users across the United Kingdom. Solar flare forecasts are one of its products, which are issued multiple times a day in two forms: forecasts for each active region on the solar disk over the next 24 h and full-disk forecasts for the next 4 days. Here the forecasting process is described in detail, as well as first verification of archived forecasts using methods commonly used in operational weather prediction. Real-time verification available for operational flare forecasting use is also described. The influence of human forecasters is highlighted, with human-edited forecasts outperforming original model results and forecasting skill decreasing over longer forecast lead times.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be either an intermediate forecast between the extremes of the ensemble spread or a manually selected forecast based on a meteorologists advice. 2. Downstream catchments with low influence of weather forecast In downstream catchments with strong human impact on discharge (e.g. by reservoir operation) and large influence of upstream gauge observation quality on forecast quality, the 'overall error' may in most cases be larger than the combination of the 'model error' and an ensemble spread. Therefore, the overall forecast uncertainty bounds are calculated differently: a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. Here, additionally the corresponding inflow hydrograph from all upstream catchments must be used. b) As for an upstream catchment, the uncertainty range is determined by combination of 'model error' and the ensemble member forecasts c) In addition, the 'overall error' is superimposed on the 'lead forecast'. For reasons of consistency, the lead forecast must be based on the same meteorological forecast in the downstream and all upstream catchments. d) From the resulting two uncertainty ranges (one from the ensemble forecast and 'model error', one from the 'lead forecast' and 'overall error'), the envelope is taken as the most prudent uncertainty range. In sum, the uncertainty associated with each forecast run is calculated and communicated to the public in the form of 10% and 90% percentiles. As in part I of this study, the methodology as well as the useful- or uselessness of the resulting uncertainty ranges will be presented and discussed by typical examples.

  5. The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Finley, Cathy

    2014-04-30

    This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements inmore » wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times.« less

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

    NASA Astrophysics Data System (ADS)

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

    2018-07-01

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

  7. Uses and Applications of Climate Forecasts for Power Utilities.

    NASA Astrophysics Data System (ADS)

    Changnon, Stanley A.; Changnon, Joyce M.; Changnon, David

    1995-05-01

    The uses and potential applications of climate forecasts for electric and gas utilities were assessed 1) to discern needs for improving climate forecasts and guiding future research, and 2) to assist utilities in making wise use of forecasts. In-depth structured interviews were conducted with 56 decision makers in six utilities to assess existing and potential uses of climate forecasts. Only 3 of the 56 use forecasts. Eighty percent of those sampled envisioned applications of climate forecasts, given certain changes and additional information. Primary applications exist in power trading, load forecasting, fuel acquisition, and systems planning, with slight differences in interests between utilities. Utility staff understand probability-based forecasts but desire climatological information related to forecasted outcomes, including analogs similar to the forecasts, and explanations of the forecasts. Desired lead times vary from a week to three months, along with forecasts of up to four seasons ahead. The new NOAA forecasts initiated in 1995 provide the lead times and longer-term forecasts desired. Major hindrances to use of forecasts are hard-to-understand formats, lack of corporate acceptance, and lack of access to expertise. Recent changes in government regulations altered the utility industry, leading to a more competitive world wherein information about future weather conditions assumes much more value. Outreach efforts by government forecast agencies appear valuable to help achieve the appropriate and enhanced use of climate forecasts by the utility industry. An opportunity for service exists also for the private weather sector.

  8. Multi-model seasonal forecast of Arctic sea-ice: forecast uncertainty at pan-Arctic and regional scales

    NASA Astrophysics Data System (ADS)

    Blanchard-Wrigglesworth, E.; Barthélemy, A.; Chevallier, M.; Cullather, R.; Fučkar, N.; Massonnet, F.; Posey, P.; Wang, W.; Zhang, J.; Ardilouze, C.; Bitz, C. M.; Vernieres, G.; Wallcraft, A.; Wang, M.

    2017-08-01

    Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or forecast post-processing (bias correction) techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

  9. An overview of health forecasting.

    PubMed

    Soyiri, Ireneous N; Reidpath, Daniel D

    2013-01-01

    Health forecasting is a novel area of forecasting, and a valuable tool for predicting future health events or situations such as demands for health services and healthcare needs. It facilitates preventive medicine and health care intervention strategies, by pre-informing health service providers to take appropriate mitigating actions to minimize risks and manage demand. Health forecasting requires reliable data, information and appropriate analytical tools for the prediction of specific health conditions or situations. There is no single approach to health forecasting, and so various methods have often been adopted to forecast aggregate or specific health conditions. Meanwhile, there are no defined health forecasting horizons (time frames) to match the choices of health forecasting methods/approaches that are often applied. The key principles of health forecasting have not also been adequately described to guide the process. This paper provides a brief introduction and theoretical analysis of health forecasting. It describes the key issues that are important for health forecasting, including: definitions, principles of health forecasting, and the properties of health data, which influence the choices of health forecasting methods. Other matters related to the value of health forecasting, and the general challenges associated with developing and using health forecasting services are discussed. This overview is a stimulus for further discussions on standardizing health forecasting approaches and methods that will facilitate health care and health services delivery.

  10. Individual versus superensemble forecasts of seasonal influenza outbreaks in the United States.

    PubMed

    Yamana, Teresa K; Kandula, Sasikiran; Shaman, Jeffrey

    2017-11-01

    Recent research has produced a number of methods for forecasting seasonal influenza outbreaks. However, differences among the predicted outcomes of competing forecast methods can limit their use in decision-making. Here, we present a method for reconciling these differences using Bayesian model averaging. We generated retrospective forecasts of peak timing, peak incidence, and total incidence for seasonal influenza outbreaks in 48 states and 95 cities using 21 distinct forecast methods, and combined these individual forecasts to create weighted-average superensemble forecasts. We compared the relative performance of these individual and superensemble forecast methods by geographic location, timing of forecast, and influenza season. We find that, overall, the superensemble forecasts are more accurate than any individual forecast method and less prone to producing a poor forecast. Furthermore, we find that these advantages increase when the superensemble weights are stratified according to the characteristics of the forecast or geographic location. These findings indicate that different competing influenza prediction systems can be combined into a single more accurate forecast product for operational delivery in real time.

  11. Individual versus superensemble forecasts of seasonal influenza outbreaks in the United States

    PubMed Central

    Kandula, Sasikiran; Shaman, Jeffrey

    2017-01-01

    Recent research has produced a number of methods for forecasting seasonal influenza outbreaks. However, differences among the predicted outcomes of competing forecast methods can limit their use in decision-making. Here, we present a method for reconciling these differences using Bayesian model averaging. We generated retrospective forecasts of peak timing, peak incidence, and total incidence for seasonal influenza outbreaks in 48 states and 95 cities using 21 distinct forecast methods, and combined these individual forecasts to create weighted-average superensemble forecasts. We compared the relative performance of these individual and superensemble forecast methods by geographic location, timing of forecast, and influenza season. We find that, overall, the superensemble forecasts are more accurate than any individual forecast method and less prone to producing a poor forecast. Furthermore, we find that these advantages increase when the superensemble weights are stratified according to the characteristics of the forecast or geographic location. These findings indicate that different competing influenza prediction systems can be combined into a single more accurate forecast product for operational delivery in real time. PMID:29107987

  12. Short-term ensemble streamflow forecasting using operationally-produced single-valued streamflow forecasts - A Hydrologic Model Output Statistics (HMOS) approach

    NASA Astrophysics Data System (ADS)

    Regonda, Satish Kumar; Seo, Dong-Jun; Lawrence, Bill; Brown, James D.; Demargne, Julie

    2013-08-01

    We present a statistical procedure for generating short-term ensemble streamflow forecasts from single-valued, or deterministic, streamflow forecasts produced operationally by the U.S. National Weather Service (NWS) River Forecast Centers (RFCs). The resulting ensemble streamflow forecast provides an estimate of the predictive uncertainty associated with the single-valued forecast to support risk-based decision making by the forecasters and by the users of the forecast products, such as emergency managers. Forced by single-valued quantitative precipitation and temperature forecasts (QPF, QTF), the single-valued streamflow forecasts are produced at a 6-h time step nominally out to 5 days into the future. The single-valued streamflow forecasts reflect various run-time modifications, or "manual data assimilation", applied by the human forecasters in an attempt to reduce error from various sources in the end-to-end forecast process. The proposed procedure generates ensemble traces of streamflow from a parsimonious approximation of the conditional multivariate probability distribution of future streamflow given the single-valued streamflow forecast, QPF, and the most recent streamflow observation. For parameter estimation and evaluation, we used a multiyear archive of the single-valued river stage forecast produced operationally by the NWS Arkansas-Red River Basin River Forecast Center (ABRFC) in Tulsa, Oklahoma. As a by-product of parameter estimation, the procedure provides a categorical assessment of the effective lead time of the operational hydrologic forecasts for different QPF and forecast flow conditions. To evaluate the procedure, we carried out hindcasting experiments in dependent and cross-validation modes. The results indicate that the short-term streamflow ensemble hindcasts generated from the procedure are generally reliable within the effective lead time of the single-valued forecasts and well capture the skill of the single-valued forecasts. For smaller basins, however, the effective lead time is significantly reduced by short basin memory and reduced skill in the single-valued QPF.

  13. U.S. High Seas Marine Text Forecasts by Area

    Science.gov Websites

    Flooding Tsunamis 406 EPIRB's U.S. High Seas Marine Text Forecasts by Area OPC N.Atlantic High Seas Forecast NHC N.Atlantic High Seas Forecast OPC N.Pacific High Seas Forecast HFO N.Pacific High Seas Forecast NHC N.Pacific High Seas Forecast HFO S.Pacific High Seas Forecast U.S. High Seas Marine Text

  14. An advance forecasting system for ship originated oil spills in the Mediterranean

    NASA Astrophysics Data System (ADS)

    Zodiatis, G.; Lardner, R.; De Dominicis, M.; Coppini, G.; Pinardi, N.

    2012-04-01

    One of the permanent risks from an oil spill incident in the Mediterranean is associated with the heavy traffic in maritime transport, as well nowadays with the coastal and offshore installations related to the oil and gas industry. Such dense activity imposes on the coastal countries the need for preparing an operational response to major oil spill incidents. In the recent past, several policies related to oil spill response have been adopted internationally. At the regional level the Barcelona convention, recognizing pollution from oil spills as one of the major threats to the marine environment of the Mediterranean, initiated the preparedness for responding to major oil spill incidents, through various national and sub-regional contingency plans. At the European level the Member States was obliged to implement the EU Directive 2005/35, aimed at identifying the polluter and bringing them to prosecution. The response to an oil spill incident employs various measures and equipment. However, the success of such response depends greatly on the prediction of the movement and weathering of the oil spills. Such predictions may obtained through the operational application of advanced numerical oil spill models integrated with met-ocean forecasting data. A well established operational system for oil spill predictions in the Mediterranean is the MEDSLIK three dimensional model that predicts the transport, diffusion and spreading of oil spill and incorporates the fate processes of evaporation, emulsification, viscosity changes, dispersion into the water column and coastal impact and adhesion. MEDSLIK is integrated with the MyOCEAN regional and several downscaled ocean forecasting systems in the Mediterranean, contributing to the development of the GMES marine services. Moreover, MEDSLIK has been coupled with EMSA-CSN and ESA ASAR imageries, for short forward and backward predictions, to assist the response agencies in the implementation of the EU Directive 2005/35. From 2007 to 2011 more than a thousand possible ship originated oil slicks were detected by ASAR imageries in the Levantine Basin and then used for operational predictions by MEDSLIK. The successful operation of the MEDSLIK oil spill prediction system in the Levantine Basin has initiated efforts to implement a multi model approach to oil spill predictions in the Mediterranean through the realization of the recently approved project known as MedDESS4MS-Mediterranean Decision Support System for Maritime Safety, funded under the MED program. MEDESS4MS project is dedicated to the prevention of maritime risks and strengthening of maritime safety related to oil spill pollution in the Mediterranean. MEDESS4MS will deliver an integrated operational multi model oil spill prediction service in the Mediterranean, connected to existing monitoring platforms (EMSA-CSN, REMPEC, AIS), using the well established oil spill modeling systems, the data from the GMES Marine Core Services and the national ocean forecasting systems.

  15. A Diagnostics Tool to detect ensemble forecast system anomaly and guide operational decisions

    NASA Astrophysics Data System (ADS)

    Park, G. H.; Srivastava, A.; Shrestha, E.; Thiemann, M.; Day, G. N.; Draijer, S.

    2017-12-01

    The hydrologic community is moving toward using ensemble forecasts to take uncertainty into account during the decision-making process. The New York City Department of Environmental Protection (DEP) implements several types of ensemble forecasts in their decision-making process: ensemble products for a statistical model (Hirsch and enhanced Hirsch); the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) forecasts based on the classical Ensemble Streamflow Prediction (ESP) technique; and the new NWS Hydrologic Ensemble Forecasting Service (HEFS) forecasts. To remove structural error and apply the forecasts to additional forecast points, the DEP post processes both the AHPS and the HEFS forecasts. These ensemble forecasts provide mass quantities of complex data, and drawing conclusions from these forecasts is time-consuming and difficult. The complexity of these forecasts also makes it difficult to identify system failures resulting from poor data, missing forecasts, and server breakdowns. To address these issues, we developed a diagnostic tool that summarizes ensemble forecasts and provides additional information such as historical forecast statistics, forecast skill, and model forcing statistics. This additional information highlights the key information that enables operators to evaluate the forecast in real-time, dynamically interact with the data, and review additional statistics, if needed, to make better decisions. We used Bokeh, a Python interactive visualization library, and a multi-database management system to create this interactive tool. This tool compiles and stores data into HTML pages that allows operators to readily analyze the data with built-in user interaction features. This paper will present a brief description of the ensemble forecasts, forecast verification results, and the intended applications for the diagnostic tool.

  16. Intermediate-term forecasting of aftershocks from an early aftershock sequence: Bayesian and ensemble forecasting approaches

    NASA Astrophysics Data System (ADS)

    Omi, Takahiro; Ogata, Yosihiko; Hirata, Yoshito; Aihara, Kazuyuki

    2015-04-01

    Because aftershock occurrences can cause significant seismic risks for a considerable time after the main shock, prospective forecasting of the intermediate-term aftershock activity as soon as possible is important. The epidemic-type aftershock sequence (ETAS) model with the maximum likelihood estimate effectively reproduces general aftershock activity including secondary or higher-order aftershocks and can be employed for the forecasting. However, because we cannot always expect the accurate parameter estimation from incomplete early aftershock data where many events are missing, such forecasting using only a single estimated parameter set (plug-in forecasting) can frequently perform poorly. Therefore, we here propose Bayesian forecasting that combines the forecasts by the ETAS model with various probable parameter sets given the data. By conducting forecasting tests of 1 month period aftershocks based on the first 1 day data after the main shock as an example of the early intermediate-term forecasting, we show that the Bayesian forecasting performs better than the plug-in forecasting on average in terms of the log-likelihood score. Furthermore, to improve forecasting of large aftershocks, we apply a nonparametric (NP) model using magnitude data during the learning period and compare its forecasting performance with that of the Gutenberg-Richter (G-R) formula. We show that the NP forecast performs better than the G-R formula in some cases but worse in other cases. Therefore, robust forecasting can be obtained by employing an ensemble forecast that combines the two complementary forecasts. Our proposed method is useful for a stable unbiased intermediate-term assessment of aftershock probabilities.

  17. Traffic safety facts 1999 : state traffic data

    DOT National Transportation Integrated Search

    2000-01-01

    This traffic safety fact sheet presents state traffic data in a figure showing 1999 Traffic Fatalities by State and Percent Change from 1998 and in 11 tables showing: (1) Traffic Fatalities and Fatality Rates, 1999; (2) Traffic Fatalities and Percent...

  18. Quantifying model uncertainty in seasonal Arctic sea-ice forecasts

    NASA Astrophysics Data System (ADS)

    Blanchard-Wrigglesworth, Edward; Barthélemy, Antoine; Chevallier, Matthieu; Cullather, Richard; Fučkar, Neven; Massonnet, François; Posey, Pamela; Wang, Wanqiu; Zhang, Jinlun; Ardilouze, Constantin; Bitz, Cecilia; Vernieres, Guillaume; Wallcraft, Alan; Wang, Muyin

    2017-04-01

    Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or post-processing techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

  19. Model-free aftershock forecasts constructed from similar sequences in the past

    NASA Astrophysics Data System (ADS)

    van der Elst, N.; Page, M. T.

    2017-12-01

    The basic premise behind aftershock forecasting is that sequences in the future will be similar to those in the past. Forecast models typically use empirically tuned parametric distributions to approximate past sequences, and project those distributions into the future to make a forecast. While parametric models do a good job of describing average outcomes, they are not explicitly designed to capture the full range of variability between sequences, and can suffer from over-tuning of the parameters. In particular, parametric forecasts may produce a high rate of "surprises" - sequences that land outside the forecast range. Here we present a non-parametric forecast method that cuts out the parametric "middleman" between training data and forecast. The method is based on finding past sequences that are similar to the target sequence, and evaluating their outcomes. We quantify similarity as the Poisson probability that the observed event count in a past sequence reflects the same underlying intensity as the observed event count in the target sequence. Event counts are defined in terms of differential magnitude relative to the mainshock. The forecast is then constructed from the distribution of past sequences outcomes, weighted by their similarity. We compare the similarity forecast with the Reasenberg and Jones (RJ95) method, for a set of 2807 global aftershock sequences of M≥6 mainshocks. We implement a sequence-specific RJ95 forecast using a global average prior and Bayesian updating, but do not propagate epistemic uncertainty. The RJ95 forecast is somewhat more precise than the similarity forecast: 90% of observed sequences fall within a factor of two of the median RJ95 forecast value, whereas the fraction is 85% for the similarity forecast. However, the surprise rate is much higher for the RJ95 forecast; 10% of observed sequences fall in the upper 2.5% of the (Poissonian) forecast range. The surprise rate is less than 3% for the similarity forecast. The similarity forecast may be useful to emergency managers and non-specialists when confidence or expertise in parametric forecasting may be lacking. The method makes over-tuning impossible, and minimizes the rate of surprises. At the least, this forecast constitutes a useful benchmark for more precisely tuned parametric forecasts.

  20. A study for systematic errors of the GLA forecast model in tropical regions

    NASA Technical Reports Server (NTRS)

    Chen, Tsing-Chang; Baker, Wayman E.; Pfaendtner, James; Corrigan, Martin

    1988-01-01

    From the sensitivity studies performed with the Goddard Laboratory for Atmospheres (GLA) analysis/forecast system, it was revealed that the forecast errors in the tropics affect the ability to forecast midlatitude weather in some cases. Apparently, the forecast errors occurring in the tropics can propagate to midlatitudes. Therefore, the systematic error analysis of the GLA forecast system becomes a necessary step in improving the model's forecast performance. The major effort of this study is to examine the possible impact of the hydrological-cycle forecast error on dynamical fields in the GLA forecast system.

  1. Experimental Study on Fatigue Performance of Foamed Lightweight Soil

    NASA Astrophysics Data System (ADS)

    Qiu, Youqiang; Yang, Ping; Li, Yongliang; Zhang, Liujun

    2017-12-01

    In order to study fatigue performance of foamed lightweight soil and forecast its fatigue life in the supporting project, on the base of preliminary tests, beam fatigue tests on foamed lightweight soil is conducted by using UTM-100 test system. Based on Weibull distribution and lognormal distribution, using the mathematical statistics method, fatigue equations of foamed lightweight soil are obtained. At the same time, according to the traffic load on real road surface of the supporting project, fatigue life of formed lightweight soil is analyzed and compared with the cumulative equivalent axle loads during the design period of the pavement. The results show that even the fatigue life of foamed lightweight soil has discrete property, the linear relationship between logarithmic fatigue life and stress ratio still performs well. Especially, the fatigue life of Weibull distribution is more close to that derived from the lognormal distribution, in the instance of 50% guarantee ratio. In addition, the results demonstrated that foamed lightweight soil as subgrade filler has good anti-fatigue performance, which can be further adopted by other projects in the similar research domain.

  2. Preliminary design of four aircraft to service the California Corridor in the year 2010: The California Condor, California Sky-Hopper, high capacity short range transport tilt rotor aircraft needed to simplify intercity transportation

    NASA Technical Reports Server (NTRS)

    1989-01-01

    The major objective of this project was to design an aircraft for use in the California Corridor in the year 2010. The design process, completed by students in a senior design class at California Polytechnic State University, San Luis Obispo, used a Class 1 airplane design analysis from Jan Roskam's Airplane Design. The California Condor (CC-38), a 38 passenger, 400 mph aircraft, was designed to meet the needs of tomorrow's passengers while conforming to the California Corridor's restrictions. Assumptions were made using today's technology with forecasts into 21st Century technology. Doubling today's commuter aircraft passenger capacity, travelling at Mach .57 with improved cruise efficiencies of over 10 percent, with the ability to land within field lengths of 4000 feet, are the CC-38's strongest points. The California Condor has a very promising future in helping to relieve the air traffic and airport congestion in the 21st Century.

  3. Comparing Two Independent Satellite-Based Algorithms for Detecting and Tracking Ash Clouds by Using SEVIRI Sensor.

    PubMed

    Falconieri, Alfredo; Cooke, Michael C; Filizzola, Carolina; Marchese, Francesco; Pergola, Nicola; Tramutoli, Valerio

    2018-01-27

    The Eyjafjallajökull (Iceland) volcanic eruption of April-May 2010 caused unprecedented air-traffic disruption in Northern Europe, revealing some important weaknesses of current operational ash-monitoring and forecasting systems and encouraging the improvement of methods and procedures for supporting the activities of Volcanic Ash Advisory Centers (VAACs) better. In this work, we compare two established satellite-based algorithms for ash detection, namely RST ASH and the operational London VAAC method, both exploiting sensor data of the spinning enhanced visible and infrared imager (SEVIRI). We analyze similarities and differences in the identification of ash clouds during the different phases of the Eyjafjallajökull eruption. The work reveals, in some cases, a certain complementary behavior of the two techniques, whose combination might improve the identification of ash-affected areas in specific conditions. This is indicated by the quantitative comparison of the merged SEVIRI ash product, achieved integrating outputs of the RST ASH and London VAAC methods, with independent atmospheric infrared sounder (AIRS) DDA (dust-detection algorithm) observations.

  4. Comparing Two Independent Satellite-Based Algorithms for Detecting and Tracking Ash Clouds by Using SEVIRI Sensor

    PubMed Central

    Cooke, Michael C.; Filizzola, Carolina

    2018-01-01

    The Eyjafjallajökull (Iceland) volcanic eruption of April–May 2010 caused unprecedented air-traffic disruption in Northern Europe, revealing some important weaknesses of current operational ash-monitoring and forecasting systems and encouraging the improvement of methods and procedures for supporting the activities of Volcanic Ash Advisory Centers (VAACs) better. In this work, we compare two established satellite-based algorithms for ash detection, namely RSTASH and the operational London VAAC method, both exploiting sensor data of the spinning enhanced visible and infrared imager (SEVIRI). We analyze similarities and differences in the identification of ash clouds during the different phases of the Eyjafjallajökull eruption. The work reveals, in some cases, a certain complementary behavior of the two techniques, whose combination might improve the identification of ash-affected areas in specific conditions. This is indicated by the quantitative comparison of the merged SEVIRI ash product, achieved integrating outputs of the RSTASH and London VAAC methods, with independent atmospheric infrared sounder (AIRS) DDA (dust-detection algorithm) observations. PMID:29382058

  5. High-order computational fluid dynamics tools for aircraft design

    PubMed Central

    Wang, Z. J.

    2014-01-01

    Most forecasts predict an annual airline traffic growth rate between 4.5 and 5% in the foreseeable future. To sustain that growth, the environmental impact of aircraft cannot be ignored. Future aircraft must have much better fuel economy, dramatically less greenhouse gas emissions and noise, in addition to better performance. Many technical breakthroughs must take place to achieve the aggressive environmental goals set up by governments in North America and Europe. One of these breakthroughs will be physics-based, highly accurate and efficient computational fluid dynamics and aeroacoustics tools capable of predicting complex flows over the entire flight envelope and through an aircraft engine, and computing aircraft noise. Some of these flows are dominated by unsteady vortices of disparate scales, often highly turbulent, and they call for higher-order methods. As these tools will be integral components of a multi-disciplinary optimization environment, they must be efficient to impact design. Ultimately, the accuracy, efficiency, robustness, scalability and geometric flexibility will determine which methods will be adopted in the design process. This article explores these aspects and identifies pacing items. PMID:25024419

  6. Multi-Year Revenue and Expenditure Forecasting for Small Municipal Governments.

    DTIC Science & Technology

    1981-03-01

    Management Audit Econometric Revenue Forecast Gap and Impact Analysis Deterministic Expenditure Forecast Municipal Forecasting Municipal Budget Formlto...together with a multi-year revenue and expenditure forecasting model for the City of Monterey, California. The Monterey model includes an econometric ...65 5 D. FORECAST BASED ON THE ECONOMETRIC MODEL ------- 67 E. FORECAST BASED ON EXPERT JUDGMENT AND TREND ANALYSIS

  7. Development of a real-time crash risk prediction model incorporating the various crash mechanisms across different traffic states.

    PubMed

    Xu, Chengcheng; Wang, Wei; Liu, Pan; Zhang, Fangwei

    2015-01-01

    This study aimed to identify the traffic flow variables contributing to crash risks under different traffic states and to develop a real-time crash risk model incorporating the varying crash mechanisms across different traffic states. The crash, traffic, and geometric data were collected on the I-880N freeway in California in 2008 and 2009. This study considered 4 different traffic states in Wu's 4-phase traffic theory. They are free fluid traffic, bunched fluid traffic, bunched congested traffic, and standing congested traffic. Several different statistical methods were used to accomplish the research objective. The preliminary analysis showed that traffic states significantly affected crash likelihood, collision type, and injury severity. Nonlinear canonical correlation analysis (NLCCA) was conducted to identify the underlying phenomena that made certain traffic states more hazardous than others. The results suggested that different traffic states were associated with various collision types and injury severities. The matching of traffic flow characteristics and crash characteristics in NLCCA revealed how traffic states affected traffic safety. The logistic regression analyses showed that the factors contributing to crash risks were quite different across various traffic states. To incorporate the varying crash mechanisms across different traffic states, random parameters logistic regression was used to develop a real-time crash risk model. Bayesian inference based on Markov chain Monte Carlo simulations was used for model estimation. The parameters of traffic flow variables in the model were allowed to vary across different traffic states. Compared with the standard logistic regression model, the proposed model significantly improved the goodness-of-fit and predictive performance. These results can promote a better understanding of the relationship between traffic flow characteristics and crash risks, which is valuable knowledge in the pursuit of improving traffic safety on freeways through the use of dynamic safety management systems.

  8. Evaluation of the impacts of traffic states on crash risks on freeways.

    PubMed

    Xu, Chengcheng; Liu, Pan; Wang, Wei; Li, Zhibin

    2012-07-01

    The primary objective of this study is to divide freeway traffic flow into different states, and to evaluate the safety performance associated with each state. Using traffic flow data and crash data collected from a northbound segment of the I-880 freeway in the state of California, United States, K-means clustering analysis was conducted to classify traffic flow into five different states. Conditional logistic regression models using case-controlled data were then developed to study the relationship between crash risks and traffic states. Traffic flow characteristics in each traffic state were compared to identify the underlying phenomena that made certain traffic states more hazardous than others. Crash risk models were also developed for different traffic states to identify how traffic flow characteristics such as speed and speed variance affected crash risks in different traffic states. The findings of this study demonstrate that the operations of freeway traffic can be divided into different states using traffic occupancy measured from nearby loop detector stations, and each traffic state can be assigned with a certain safety level. The impacts of traffic flow parameters on crash risks are different across different traffic flow states. A method based on discriminant analysis was further developed to identify traffic states given real-time freeway traffic flow data. Validation results showed that the method was of reasonably high accuracy for identifying freeway traffic states. Copyright © 2012 Elsevier Ltd. All rights reserved.

  9. A Sarsa(λ)-based control model for real-time traffic light coordination.

    PubMed

    Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

    2014-01-01

    Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

  10. A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments

    NASA Astrophysics Data System (ADS)

    Schepen, Andrew; Zhao, Tongtiegang; Wang, Quan J.; Robertson, David E.

    2018-03-01

    Rainfall forecasts are an integral part of hydrological forecasting systems at sub-seasonal to seasonal timescales. In seasonal forecasting, global climate models (GCMs) are now the go-to source for rainfall forecasts. For hydrological applications however, GCM forecasts are often biased and unreliable in uncertainty spread, and calibration is therefore required before use. There are sophisticated statistical techniques for calibrating monthly and seasonal aggregations of the forecasts. However, calibration of seasonal forecasts at the daily time step typically uses very simple statistical methods or climate analogue methods. These methods generally lack the sophistication to achieve unbiased, reliable and coherent forecasts of daily amounts and seasonal accumulated totals. In this study, we propose and evaluate a Rainfall Post-Processing method for Seasonal forecasts (RPP-S), which is based on the Bayesian joint probability modelling approach for calibrating daily forecasts and the Schaake Shuffle for connecting the daily ensemble members of different lead times. We apply the method to post-process ACCESS-S forecasts for 12 perennial and ephemeral catchments across Australia and for 12 initialisation dates. RPP-S significantly reduces bias in raw forecasts and improves both skill and reliability. RPP-S forecasts are also more skilful and reliable than forecasts derived from ACCESS-S forecasts that have been post-processed using quantile mapping, especially for monthly and seasonal accumulations. Several opportunities to improve the robustness and skill of RPP-S are identified. The new RPP-S post-processed forecasts will be used in ensemble sub-seasonal to seasonal streamflow applications.

  11. Bayesian analyses of seasonal runoff forecasts

    NASA Astrophysics Data System (ADS)

    Krzysztofowicz, R.; Reese, S.

    1991-12-01

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

  12. 32 CFR 634.26 - Traffic law enforcement principles.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... safely within traffic laws and regulations and maintain an effective and efficient flow of traffic... 32 National Defense 4 2013-07-01 2013-07-01 false Traffic law enforcement principles. 634.26... ENFORCEMENT AND CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.26 Traffic...

  13. 32 CFR 634.26 - Traffic law enforcement principles.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... safely within traffic laws and regulations and maintain an effective and efficient flow of traffic... 32 National Defense 4 2012-07-01 2011-07-01 true Traffic law enforcement principles. 634.26... ENFORCEMENT AND CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.26 Traffic...

  14. 32 CFR 634.26 - Traffic law enforcement principles.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... safely within traffic laws and regulations and maintain an effective and efficient flow of traffic... 32 National Defense 4 2014-07-01 2013-07-01 true Traffic law enforcement principles. 634.26... ENFORCEMENT AND CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.26 Traffic...

  15. A short-term ensemble wind speed forecasting system for wind power applications

    NASA Astrophysics Data System (ADS)

    Baidya Roy, S.; Traiteur, J. J.; Callicutt, D.; Smith, M.

    2011-12-01

    This study develops an adaptive, blended forecasting system to provide accurate wind speed forecasts 1 hour ahead of time for wind power applications. The system consists of an ensemble of 21 forecasts with different configurations of the Weather Research and Forecasting Single Column Model (WRFSCM) and a persistence model. The ensemble is calibrated against observations for a 2 month period (June-July, 2008) at a potential wind farm site in Illinois using the Bayesian Model Averaging (BMA) technique. The forecasting system is evaluated against observations for August 2008 at the same site. The calibrated ensemble forecasts significantly outperform the forecasts from the uncalibrated ensemble while significantly reducing forecast uncertainty under all environmental stability conditions. The system also generates significantly better forecasts than persistence, autoregressive (AR) and autoregressive moving average (ARMA) models during the morning transition and the diurnal convective regimes. This forecasting system is computationally more efficient than traditional numerical weather prediction models and can generate a calibrated forecast, including model runs and calibration, in approximately 1 minute. Currently, hour-ahead wind speed forecasts are almost exclusively produced using statistical models. However, numerical models have several distinct advantages over statistical models including the potential to provide turbulence forecasts. Hence, there is an urgent need to explore the role of numerical models in short-term wind speed forecasting. This work is a step in that direction and is likely to trigger a debate within the wind speed forecasting community.

  16. Communicating uncertainty in hydrological forecasts: mission impossible?

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

    Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted scenarios, is essential. We believe that the efficient communication of uncertainty in hydro-meteorological forecasts is not a mission impossible. Questions remaining unanswered in probabilistic hydrological forecasting should not neutralize the goal of such a mission, and the suspense kept should instead act as a catalyst for overcoming the remaining challenges.

  17. Bayesian flood forecasting methods: A review

    NASA Astrophysics Data System (ADS)

    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 developed and widely applied, but there is still room for improvements. Future research in the context of Bayesian flood forecasting should be on assimilation of various sources of newly available information and improvement of predictive performance assessment methods.

  18. Verification of Space Weather Forecasts using Terrestrial Weather Approaches

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    The Met Office Space Weather Operations Centre (MOSWOC) provides a range of 24/7 operational space weather forecasts, alerts, and warnings, which provide valuable information on space weather that can degrade electricity grids, radio communications, and satellite electronics. Forecasts issued include arrival times of coronal mass ejections (CMEs), and probabilistic forecasts for flares, geomagnetic storm indices, and energetic particle fluxes and fluences. These forecasts are produced twice daily using a combination of output from models such as Enlil, near-real-time observations, and forecaster experience. Verification of forecasts is crucial for users, researchers, and forecasters to understand the strengths and limitations of forecasters, and to assess forecaster added value. To this end, the Met Office (in collaboration with Exeter University) has been adapting verification techniques from terrestrial weather, and has been working closely with the International Space Environment Service (ISES) to standardise verification procedures. We will present the results of part of this work, analysing forecast and observed CME arrival times, assessing skill using 2x2 contingency tables. These MOSWOC forecasts can be objectively compared to those produced by the NASA Community Coordinated Modelling Center - a useful benchmark. This approach cannot be taken for the other forecasts, as they are probabilistic and categorical (e.g., geomagnetic storm forecasts give probabilities of exceeding levels from minor to extreme). We will present appropriate verification techniques being developed to address these forecasts, such as rank probability skill score, and comparing forecasts against climatology and persistence benchmarks. As part of this, we will outline the use of discrete time Markov chains to assess and improve the performance of our geomagnetic storm forecasts. We will also discuss work to adapt a terrestrial verification visualisation system to space weather, to help MOSWOC forecasters view verification results in near real-time; plans to objectively assess flare forecasts under the EU Horizon 2020 FLARECAST project; and summarise ISES efforts to achieve consensus on verification.

  19. A framework for improving a seasonal hydrological forecasting system using sensitivity analysis

    NASA Astrophysics Data System (ADS)

    Arnal, Louise; Pappenberger, Florian; Smith, Paul; Cloke, Hannah

    2017-04-01

    Seasonal streamflow forecasts are of great value for the socio-economic sector, for applications such as navigation, flood and drought mitigation and reservoir management for hydropower generation and water allocation to agriculture and drinking water. However, as we speak, the performance of dynamical seasonal hydrological forecasting systems (systems based on running seasonal meteorological forecasts through a hydrological model to produce seasonal hydrological forecasts) is still limited in space and time. In this context, the ESP (Ensemble Streamflow Prediction) remains an attractive forecasting method for seasonal streamflow forecasting as it relies on forcing a hydrological model (starting from the latest observed or simulated initial hydrological conditions) with historical meteorological observations. This makes it cheaper to run than a standard dynamical seasonal hydrological forecasting system, for which the seasonal meteorological forecasts will first have to be produced, while still producing skilful forecasts. There is thus the need to focus resources and time towards improvements in dynamical seasonal hydrological forecasting systems which will eventually lead to significant improvements in the skill of the streamflow forecasts generated. Sensitivity analyses are a powerful tool that can be used to disentangle the relative contributions of the two main sources of errors in seasonal streamflow forecasts, namely the initial hydrological conditions (IHC; e.g., soil moisture, snow cover, initial streamflow, among others) and the meteorological forcing (MF; i.e., seasonal meteorological forecasts of precipitation and temperature, input to the hydrological model). Sensitivity analyses are however most useful if they inform and change current operational practices. To this end, we propose a method to improve the design of a seasonal hydrological forecasting system. This method is based on sensitivity analyses, informing the forecasters as to which element of the forecasting chain (i.e., IHC or MF) could potentially lead to the highest increase in seasonal hydrological forecasting performance, after each forecast update.

  20. Real-time Volcanic Cloud Products and Predictions for Aviation Alerts

    NASA Astrophysics Data System (ADS)

    Krotkov, N. A.; Hughes, E. J.; da Silva, A. M., Jr.; Seftor, C. J.; Brentzel, K. W.; Hassinen, S.; Heinrichs, T. A.; Schneider, D. J.; Hoffman, R.; Myers, T.; Flynn, L. E.; Niu, J.; Theys, N.; Brenot, H. H.

    2016-12-01

    We will discuss progress of the NASA ASP project, which promotes the use of satellite volcanic SO2 (VSO2) and Ash (VA) data, and forecasting tools that enhance VA Decision Support Systems (DSS) at the VA Advisory Centers (VAACs) for prompt aviation warnings. The goals are: (1) transition NASA algorithms to NOAA for global NRT processing and integration into DSS at Washington VAAC for operational users and public dissemination; (2) Utilize Direct Broadcast capability of the Aura and SNPP satellites to process Direct Readout (DR) data at two high latitude locations in Finland and Fairbanks, Alaska to enhance VA DSS in Europe and at USGS's Alaska Volcano Observatory (AVO) and Alaska-VAAC; (3) Improve global Eulerian model-based VA/VSO2 forecasting and risk/cost assessments with Metron Aviation. Our global NRT OMI and OMPS data have been fully integrated into European Support to Aviation Control Service and NOAA operational web sites. We are transitioning OMPS processing to our partners at NOAA/NESDIS to integrate into operational processing environment. NASA's Suomi NPP Ozone Science Team, in conjunction with GSFC's Direct Readout Laboratory (DRL), have implemented Version 2 of the OMPS real-time DR processing package to generate VSO2 and VA products at the Geographic Information Network of Alaska (GINA) and the Finnish Meteorological Institute (FMI). The system provides real-time coverage over some of the most congested airspace and over many of the most active volcanoes in the world. The OMPS real time capability is now publicly available via DRL's IPOPP package. We use satellite observations to define volcanic source term estimates in the NASA GOES-5 model, which was updated allowing for the simulation of VA and VSO2 clouds. Column SO2 observations from SNPP/OMPS provide an initial estimate of the total cloud SO2 mass, and are used with backward transport analysis to make an initial cloud height estimate. Later VSO2 observations are used to "nudge" the SO2 mass within the model. The GEOS-5 simulations provide qualitative forecasts, which locate the extent of regions hazardous to aviation. Air traffic flow algorithms have been developed by Metron Aviation to use GEOS-5 volcanic simulations to determine the most cost-effective rerouting paths around hazardous volcanic clouds.

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

    ERIC Educational Resources Information Center

    Klopfenstein, Bruce C.

    1989-01-01

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

  2. Uncertainties in Forecasting Streamflow using Entropy Theory

    NASA Astrophysics Data System (ADS)

    Cui, H.; Singh, V. P.

    2017-12-01

    Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.

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

    NASA Astrophysics Data System (ADS)

    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 skill (mostly in areas of high rainfall to the north and west) and only 30 % of the skill arises from hydrological memory (typically groundwater-dominated areas). Given the high spatial heterogeneity in typical patterns of UK rainfall and evaporation, future development of skilful spatially distributed seasonal forecasts could lead to substantial improvements in seasonal flow forecast capability, potentially benefitting practitioners interested in predicting hydrological extremes, not only in the UK but also across Europe.

  4. Improving medium-range and seasonal hydroclimate forecasts in the southeast USA

    NASA Astrophysics Data System (ADS)

    Tian, Di

    Accurate hydro-climate forecasts are important for decision making by water managers, agricultural producers, and other stake holders. Numerical weather prediction models and general circulation models may have potential for improving hydro-climate forecasts at different scales. In this study, forecast analogs of the Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS) based on different approaches were evaluated for medium-range reference evapotranspiration (ETo), irrigation scheduling, and urban water demand forecasts in the southeast United States; the Climate Forecast System version 2 (CFSv2) and the North American national multi-model ensemble (NMME) were statistically downscaled for seasonal forecasts of ETo, precipitation (P) and 2-m temperature (T2M) at the regional level. The GFS mean temperature (Tmean), relative humidity, and wind speed (Wind) reforecasts combined with the climatology of Reanalysis 2 solar radiation (Rs) produced higher skill than using the direct GFS output only. Constructed analogs showed slightly higher skill than natural analogs for deterministic forecasts. Both irrigation scheduling driven by the GEFS-based ETo forecasts and GEFS-based ETo forecast skill were generally positive up to one week throughout the year. The GEFS improved ETo forecast skill compared to the GFS. The GEFS-based analog forecasts for the input variables of an operational urban water demand model were skillful when applied in the Tampa Bay area. The modified operational models driven by GEFS analog forecasts showed higher forecast skill than the operational model based on persistence. The results for CFSv2 seasonal forecasts showed maximum temperature (Tmax) and Rs had the greatest influence on ETo. The downscaled Tmax showed the highest predictability, followed by Tmean, Tmin, Rs, and Wind. The CFSv2 model could better predict ETo in cold seasons during El Nino Southern Oscillation (ENSO) events only when the forecast initial condition was in ENSO. Downscaled P and T2M forecasts were produced by directly downscaling the NMME P and T2M output or indirectly using the NMME forecasts of Nino3.4 sea surface temperatures to predict local-scale P and T2M. The indirect method generally showed the highest forecast skill which occurs in cold seasons. The bias-corrected NMME ensemble forecast skill did not outperform the best single model.

  5. A Sarsa(λ)-Based Control Model for Real-Time Traffic Light Coordination

    PubMed Central

    Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

    2014-01-01

    Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control. PMID:24592183

  6. Traffic jams induced by fluctuation of a leading car.

    PubMed

    Nagatani, T

    2000-04-01

    We present a phase diagram of the different kinds of congested traffic triggered by fluctuation of a leading car in an open system without sources and sinks. Traffic states and density waves are investigated numerically by varying the amplitude of fluctuation using a car following model. The phase transitions among the free traffic, oscillatory congested traffic, and homogeneous congested traffic occur by fluctuation of a leading car. With increasing the amplitude of fluctuation, the transition between the free traffic and oscillatory traffic occurs at lower density and the transition between the homogeneous congested traffic and the oscillatory traffic occurs at higher density. The oscillatory congested traffic corresponds to the coexisting phase. Also, the moving localized clusters appear just above the transition lines.

  7. Android-based E-Traffic law enforcement system in Surakarta City

    NASA Astrophysics Data System (ADS)

    Yulianto, Budi; Setiono

    2018-03-01

    The urban advancement is always overpowered by the increasing number of vehicles as the need for movement of people and goods. This can lead to traffic problems if there is no effort on the implementation of traffic management and engineering, and traffic law enforcement. In this case, the Government of Surakarta City has implemented various policies and regulations related to traffic management and engineering in order to run traffic in an orderly, safe and comfortable manner according to the applicable law. However, conditions in the field shows that traffic violations still occurred frequently due to the weakness of traffic law enforcement in terms of human resources and the system. In this connection, a tool is needed to support traffic law enforcement, especially in relation to the reporting system of traffic violations. This study aims to develop an Android-based traffic violations reporting application (E-Traffic Law Enforcement) as part of the traffic law enforcement system in Surakarta City. The Android-apps records the location and time of the traffic violations incident along with the visual evidence of the infringement. This information will be connected to the database system to detect offenders and to do the traffic law enforcement process.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  9. The potential of radar-based ensemble forecasts for flash-flood early warning in the southern Swiss Alps

    NASA Astrophysics Data System (ADS)

    Liechti, K.; Panziera, L.; Germann, U.; Zappa, M.

    2013-10-01

    This study explores the limits of radar-based forecasting for hydrological runoff prediction. Two novel radar-based ensemble forecasting chains for flash-flood early warning are investigated in three catchments in the southern Swiss Alps and set in relation to deterministic discharge forecasts for the same catchments. The first radar-based ensemble forecasting chain is driven by NORA (Nowcasting of Orographic Rainfall by means of Analogues), an analogue-based heuristic nowcasting system to predict orographic rainfall for the following eight hours. The second ensemble forecasting system evaluated is REAL-C2, where the numerical weather prediction COSMO-2 is initialised with 25 different initial conditions derived from a four-day nowcast with the radar ensemble REAL. Additionally, three deterministic forecasting chains were analysed. The performance of these five flash-flood forecasting systems was analysed for 1389 h between June 2007 and December 2010 for which NORA forecasts were issued, due to the presence of orographic forcing. A clear preference was found for the ensemble approach. Discharge forecasts perform better when forced by NORA and REAL-C2 rather then by deterministic weather radar data. Moreover, it was observed that using an ensemble of initial conditions at the forecast initialisation, as in REAL-C2, significantly improved the forecast skill. These forecasts also perform better then forecasts forced by ensemble rainfall forecasts (NORA) initialised form a single initial condition of the hydrological model. Thus the best results were obtained with the REAL-C2 forecasting chain. However, for regions where REAL cannot be produced, NORA might be an option for forecasting events triggered by orographic precipitation.

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

    NASA Astrophysics Data System (ADS)

    Danhelka, Jan; Vlasak, Tomas

    2010-05-01

    Czech Hydrometeorological Institute (CHMI) is responsible for flood forecasting and warning in the Czech Republic. To meet that issue CHMI operates hydrological forecasting systems and publish flow forecast in selected profiles. Flood forecast and warning is an output of system that links observation (flow and atmosphere), data processing, weather forecast (especially NWP's QPF), hydrological modeling and modeled outputs evaluation and interpretation by forecaster. Forecast users are interested in final output without separating uncertainties of separate steps of described process. Therefore an evaluation of final operational forecasts was done for profiles within Elbe river basin produced by AquaLog forecasting system during period 2002 to 2008. Effects of uncertainties of observation, data processing and especially meteorological forecasts were not accounted separately. Forecast of flood levels exceedance (peak over the threshold) during forecasting period was the main criterion as flow increase forecast is of the highest importance. Other evaluation criteria included peak flow and volume difference. In addition Nash-Sutcliffe was computed separately for each time step (1 to 48 h) of forecasting period to identify its change with the lead time. Textual flood warnings are issued for administrative regions to initiate flood protection actions in danger of flood. Flood warning hit rate was evaluated at regions level and national level. Evaluation found significant differences of model forecast skill between forecasting profiles, particularly less skill was evaluated at small headwater basins due to domination of QPF uncertainty in these basins. The average hit rate was 0.34 (miss rate = 0.33, false alarm rate = 0.32). However its explored spatial difference is likely to be influenced also by different fit of parameters sets (due to different basin characteristics) and importantly by different impact of human factor. Results suggest that the practice of interactive model operation, experience and forecasting strategy differs between responsible forecasting offices. Warning is based on model outputs interpretation by hydrologists-forecaster. Warning hit rate reached 0.60 for threshold set to lowest flood stage of which 0.11 was underestimation of flood degree (miss 0.22, false alarm 0.28). Critical success index of model forecast was 0.34, while the same criteria for warning reached 0.55. We assume that the increase accounts not only to change of scale from single forecasting point to region for warning, but partly also to forecaster's added value. There is no official warning strategy preferred in the Czech Republic (f.e. tolerance towards higher false alarm rate). Therefore forecaster decision and personal strategy is of great importance. Results show quite successful warning for 1st flood level exceedance, over-warning for 2nd flood level, but under-warning for 3rd (highest) flood level. That suggests general forecaster's preference of medium level warning (2nd flood level is legally determined to be the start of the flood and flood protection activities). In conclusion human forecaster's experience and analysis skill increases flood warning performance notably. However society preference should be specifically addressed in the warning strategy definition to support forecaster's decision making.

  11. An Optimization of Inventory Demand Forecasting in University Healthcare Centre

    NASA Astrophysics Data System (ADS)

    Bon, A. T.; Ng, T. K.

    2017-01-01

    Healthcare industry becomes an important field for human beings nowadays as it concerns about one’s health. With that, forecasting demand for health services is an important step in managerial decision making for all healthcare organizations. Hence, a case study was conducted in University Health Centre to collect historical demand data of Panadol 650mg for 68 months from January 2009 until August 2014. The aim of the research is to optimize the overall inventory demand through forecasting techniques. Quantitative forecasting or time series forecasting model was used in the case study to forecast future data as a function of past data. Furthermore, the data pattern needs to be identified first before applying the forecasting techniques. Trend is the data pattern and then ten forecasting techniques are applied using Risk Simulator Software. Lastly, the best forecasting techniques will be find out with the least forecasting error. Among the ten forecasting techniques include single moving average, single exponential smoothing, double moving average, double exponential smoothing, regression, Holt-Winter’s additive, Seasonal additive, Holt-Winter’s multiplicative, seasonal multiplicative and Autoregressive Integrated Moving Average (ARIMA). According to the forecasting accuracy measurement, the best forecasting technique is regression analysis.

  12. Air Pollution Forecasts: An Overview

    PubMed Central

    Bai, Lu; Wang, Jianzhou; Lu, Haiyan

    2018-01-01

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

  13. Air Pollution Forecasts: An Overview.

    PubMed

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

    2018-04-17

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

  14. Analog-Based Postprocessing of Navigation-Related Hydrological Ensemble Forecasts

    NASA Astrophysics Data System (ADS)

    Hemri, S.; Klein, B.

    2017-11-01

    Inland waterway transport benefits from probabilistic forecasts of water levels as they allow to optimize the ship load and, hence, to minimize the transport costs. Probabilistic state-of-the-art hydrologic ensemble forecasts inherit biases and dispersion errors from the atmospheric ensemble forecasts they are driven with. The use of statistical postprocessing techniques like ensemble model output statistics (EMOS) allows for a reduction of these systematic errors by fitting a statistical model based on training data. In this study, training periods for EMOS are selected based on forecast analogs, i.e., historical forecasts that are similar to the forecast to be verified. Due to the strong autocorrelation of water levels, forecast analogs have to be selected based on entire forecast hydrographs in order to guarantee similar hydrograph shapes. Custom-tailored measures of similarity for forecast hydrographs comprise hydrological series distance (SD), the hydrological matching algorithm (HMA), and dynamic time warping (DTW). Verification against observations reveals that EMOS forecasts for water level at three gauges along the river Rhine with training periods selected based on SD, HMA, and DTW compare favorably with reference EMOS forecasts, which are based on either seasonal training periods or on training periods obtained by dividing the hydrological forecast trajectories into runoff regimes.

  15. State Traffic Data: Traffic Safety Facts, 2001.

    ERIC Educational Resources Information Center

    National Center for Statistics and Analysis (NHTSA), Washington, DC.

    This brief provides statistical information on U.S. traffic accidents delineated by state. A map details the 2001 traffic fatalities by state and the percent change from 2000. Data tables include: (1) traffic fatalities and fatality rates, 2001; (2) traffic fatalities and percent change, 1975-2001; (3) alcohol involvement in fatal traffic crashes,…

  16. Forecasting, Forecasting

    Treesearch

    Michael A. Fosberg

    1987-01-01

    Future improvements in the meteorological forecasts used in fire management will come from improvements in three areas: observational systems, forecast techniques, and postprocessing of forecasts and better integration of this information into the fire management process.

  17. Traffic information computing platform for big data

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Duan, Zongtao, E-mail: ztduan@chd.edu.cn; Li, Ying, E-mail: ztduan@chd.edu.cn; Zheng, Xibin, E-mail: ztduan@chd.edu.cn

    Big data environment create data conditions for improving the quality of traffic information service. The target of this article is to construct a traffic information computing platform for big data environment. Through in-depth analysis the connotation and technology characteristics of big data and traffic information service, a distributed traffic atomic information computing platform architecture is proposed. Under the big data environment, this type of traffic atomic information computing architecture helps to guarantee the traffic safety and efficient operation, more intelligent and personalized traffic information service can be used for the traffic information users.

  18. Accuracy of short‐term sea ice drift forecasts using a coupled ice‐ocean model

    PubMed Central

    Zhang, Jinlun

    2015-01-01

    Abstract Arctic sea ice drift forecasts of 6 h–9 days for the summer of 2014 are generated using the Marginal Ice Zone Modeling and Assimilation System (MIZMAS); the model is driven by 6 h atmospheric forecasts from the Climate Forecast System (CFSv2). Forecast ice drift speed is compared to drifting buoys and other observational platforms. Forecast positions are compared with actual positions 24 h–8 days since forecast. Forecast results are further compared to those from the forecasts generated using an ice velocity climatology driven by multiyear integrations of the same model. The results are presented in the context of scheduling the acquisition of high‐resolution images that need to follow buoys or scientific research platforms. RMS errors for ice speed are on the order of 5 km/d for 24–48 h since forecast using the sea ice model compared with 9 km/d using climatology. Predicted buoy position RMS errors are 6.3 km for 24 h and 14 km for 72 h since forecast. Model biases in ice speed and direction can be reduced by adjusting the air drag coefficient and water turning angle, but the adjustments do not affect verification statistics. This suggests that improved atmospheric forecast forcing may further reduce the forecast errors. The model remains skillful for 8 days. Using the forecast model increases the probability of tracking a target drifting in sea ice with a 10 km × 10 km image from 60 to 95% for a 24 h forecast and from 27 to 73% for a 48 h forecast. PMID:27818852

  19. Two-step forecast of geomagnetic storm using coronal mass ejection and solar wind condition

    PubMed Central

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

    2014-01-01

    To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study (Bz ≤ −5 nT or Ey ≥ 3 mV/m for t≥ 2 h for moderate storms with minimum Dst less than −50 nT) and a Dst model developed by Temerin and Li (2002, 2006) (TL model). Using 55 CME-Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90%) than the forecasts based on the TL model (87%). However, the latter produces better forecasts for 24 nonstorm events (88%), while the former correctly forecasts only 71% of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80%) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (∩), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81%) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (∪), all geomagnetic storms are correctly forecasted. PMID:26213515

  20. Two-step forecast of geomagnetic storm using coronal mass ejection and solar wind condition.

    PubMed

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

    2014-04-01

    To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study ( B z  ≤ -5 nT or E y  ≥ 3 mV/m for t ≥ 2 h for moderate storms with minimum Dst less than -50 nT) and a Dst model developed by Temerin and Li (2002, 2006) (TL model). Using 55 CME- Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90%) than the forecasts based on the TL model (87%). However, the latter produces better forecasts for 24 nonstorm events (88%), while the former correctly forecasts only 71% of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80%) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (∩), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81%) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (∪), all geomagnetic storms are correctly forecasted.

  1. Medium-range fire weather forecasts

    Treesearch

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

    1991-01-01

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

  2. Probability fire weather forecasts .. show promise in 3-year trial

    Treesearch

    Paul G. Scowcroft

    1970-01-01

    Probability fire weather forecasts were compared with categorical and climatological forecasts in a trial in southern California during the 1965-1967 fire seasons. Equations were developed to express the reliability of forecasts and degree of skill shown by the forecaster. Evaluation of 336 daily reports suggests that probability forecasts were more reliable. For...

  3. NASA Products to Enhance Energy Utility Load Forecasting

    NASA Technical Reports Server (NTRS)

    Lough, G.; Zell, E.; Engel-Cox, J.; Fungard, Y.; Jedlovec, G.; Stackhouse, P.; Homer, R.; Biley, S.

    2012-01-01

    Existing energy load forecasting tools rely upon historical load and forecasted weather to predict load within energy company service areas. The shortcomings of load forecasts are often the result of weather forecasts that are not at a fine enough spatial or temporal resolution to capture local-scale weather events. This project aims to improve the performance of load forecasting tools through the integration of high-resolution, weather-related NASA Earth Science Data, such as temperature, relative humidity, and wind speed. Three companies are participating in operational testing one natural gas company, and two electric providers. Operational results comparing load forecasts with and without NASA weather forecasts have been generated since March 2010. We have worked with end users at the three companies to refine selection of weather forecast information and optimize load forecast model performance. The project will conclude in 2012 with transitioning documented improvements from the inclusion of NASA forecasts for sustained use by energy utilities nationwide in a variety of load forecasting tools. In addition, Battelle has consulted with energy companies nationwide to document their information needs for long-term planning, in light of climate change and regulatory impacts.

  4. Optimizing Tsunami Forecast Model Accuracy

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  5. Seasonal Water Balance Forecasts for Drought Early Warning in Ethiopia

    NASA Astrophysics Data System (ADS)

    Spirig, Christoph; Bhend, Jonas; Liniger, Mark

    2016-04-01

    Droughts severely impact Ethiopian agricultural production. Successful early warning for drought conditions in the upcoming harvest season therefore contributes to better managing food shortages arising from adverse climatic conditions. So far, however, meteorological seasonal forecasts have not been used in Ethiopia's national food security early warning system (i.e. the LEAP platform). Here we analyse the forecast quality of seasonal forecasts of total rainfall and of the meteorological water balance as a proxy for plant available water. We analyse forecast skill of June to September rainfall and water balance from dynamical seasonal forecast systems, the ECMWF System4 and EC-EARTH global forecasting systems. Rainfall forecasts outperform forecasts assuming a stationary climate mainly in north-eastern Ethiopia - an area that is particularly vulnerable to droughts. Forecasts of the water balance index seem to be even more skilful and thus more useful than pure rainfall forecasts. The results vary though for different lead times and skill measures employed. We further explore the potential added value of dynamically downscaling the forecasts through several dynamical regional climate models made available through the EU FP7 project EUPORIAS. Preliminary results suggest that dynamically downscaled seasonal forecasts are not significantly better compared with seasonal forecasts from the global models. We conclude that seasonal forecasts of a simple climate index such as the water balance have the potential to benefit drought early warning in Ethiopia, both due to its positive predictive skill and higher usefulness than seasonal mean quantities.

  6. A Decision Support System for effective use of probability forecasts

    NASA Astrophysics Data System (ADS)

    De Kleermaeker, Simone; Verkade, Jan

    2013-04-01

    Often, water management decisions are based on hydrological forecasts. These forecasts, however, are affected by inherent uncertainties. It is increasingly common for forecasting agencies to make explicit estimates of these uncertainties and thus produce probabilistic forecasts. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a stricter separation of responsibilities between forecasters and decision maker can be made. However, simply having probabilistic forecasts available is not sufficient to realise the associated benefits. Additional effort is required in areas such as forecast visualisation and communication, decision making in uncertainty and forecast verification. Also, revised separation of responsibilities requires a shift in institutional arrangements and responsibilities. A recent study identified a number of additional issues related to the effective use of probability forecasts. When moving from deterministic to probability forecasting, a dimension is added to an already multi-dimensional problem; this makes it increasingly difficult for forecast users to extract relevant information from a forecast. A second issue is that while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be present. For example, in many cases no estimates of flood damage, of costs of management measures and of damage reduction are available. This paper presents the results of the study, including some suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development of the DSS is outlined.

  7. Evaluation of statistical models for forecast errors from the HBV model

    NASA Astrophysics Data System (ADS)

    Engeland, Kolbjørn; Renard, Benjamin; Steinsland, Ingelin; Kolberg, Sjur

    2010-04-01

    SummaryThree statistical models for the forecast errors for inflow into the Langvatn reservoir in Northern Norway have been constructed and tested according to the agreement between (i) the forecast distribution and the observations and (ii) median values of the forecast distribution and the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order auto-regressive model was constructed for the forecast errors. The parameters were conditioned on weather classes. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order auto-regressive model was constructed for the forecast errors. For the third model positive and negative errors were modeled separately. The errors were first NQT-transformed before conditioning the mean error values on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: we wanted (a) the forecast distribution to be reliable; (b) the forecast intervals to be narrow; (c) the median values of the forecast distribution to be close to the observed values. Models 1 and 2 gave almost identical results. The median values improved the forecast with Nash-Sutcliffe R eff increasing from 0.77 for the original forecast to 0.87 for the corrected forecasts. Models 1 and 2 over-estimated the forecast intervals but gave the narrowest intervals. Their main drawback was that the distributions are less reliable than Model 3. For Model 3 the median values did not fit well since the auto-correlation was not accounted for. Since Model 3 did not benefit from the potential variance reduction that lies in bias estimation and removal it gave on average wider forecasts intervals than the two other models. At the same time Model 3 on average slightly under-estimated the forecast intervals, probably explained by the use of average measures to evaluate the fit.

  8. Moving beyond the cost-loss ratio: economic assessment of streamflow forecasts for a risk-averse decision maker

    NASA Astrophysics Data System (ADS)

    Matte, Simon; Boucher, Marie-Amélie; Boucher, Vincent; Fortier Filion, Thomas-Charles

    2017-06-01

    A large effort has been made over the past 10 years to promote the operational use of probabilistic or ensemble streamflow forecasts. Numerous studies have shown that ensemble forecasts are of higher quality than deterministic ones. Many studies also conclude that decisions based on ensemble rather than deterministic forecasts lead to better decisions in the context of flood mitigation. Hence, it is believed that ensemble forecasts possess a greater economic and social value for both decision makers and the general population. However, the vast majority of, if not all, existing hydro-economic studies rely on a cost-loss ratio framework that assumes a risk-neutral decision maker. To overcome this important flaw, this study borrows from economics and evaluates the economic value of early warning flood systems using the well-known Constant Absolute Risk Aversion (CARA) utility function, which explicitly accounts for the level of risk aversion of the decision maker. This new framework allows for the full exploitation of the information related to a forecasts' uncertainty, making it especially suited for the economic assessment of ensemble or probabilistic forecasts. Rather than comparing deterministic and ensemble forecasts, this study focuses on comparing different types of ensemble forecasts. There are multiple ways of assessing and representing forecast uncertainty. Consequently, there exist many different means of building an ensemble forecasting system for future streamflow. One such possibility is to dress deterministic forecasts using the statistics of past error forecasts. Such dressing methods are popular among operational agencies because of their simplicity and intuitiveness. Another approach is the use of ensemble meteorological forecasts for precipitation and temperature, which are then provided as inputs to one or many hydrological model(s). In this study, three concurrent ensemble streamflow forecasting systems are compared: simple statistically dressed deterministic forecasts, forecasts based on meteorological ensembles, and a variant of the latter that also includes an estimation of state variable uncertainty. This comparison takes place for the Montmorency River, a small flood-prone watershed in southern central Quebec, Canada. The assessment of forecasts is performed for lead times of 1 to 5 days, both in terms of forecasts' quality (relative to the corresponding record of observations) and in terms of economic value, using the new proposed framework based on the CARA utility function. It is found that the economic value of a forecast for a risk-averse decision maker is closely linked to the forecast reliability in predicting the upper tail of the streamflow distribution. Hence, post-processing forecasts to avoid over-forecasting could help improve both the quality and the value of forecasts.

  9. Intelligent Traffic Light Based on PLC Control

    NASA Astrophysics Data System (ADS)

    Mei, Lin; Zhang, Lijian; Wang, Lingling

    2017-11-01

    The traditional traffic light system with a fixed control mode and single control function is contradicted with the current traffic section. The traditional one has been unable to meet the functional requirements of the existing flexible traffic control system. This paper research and develop an intelligent traffic light called PLC control system. It uses PLC as control core, using a sensor module for receiving real-time information of vehicles, traffic control mode for information to select the traffic lights. Of which control mode is flexible and changeable, and it also set the countdown reminder to improve the effectiveness of traffic lights, which can realize the goal of intelligent traffic diversion, intelligent traffic diversion.

  10. A hybrid approach EMD-HW for short-term forecasting of daily stock market time series data

    NASA Astrophysics Data System (ADS)

    Awajan, Ahmad Mohd; Ismail, Mohd Tahir

    2017-08-01

    Recently, forecasting time series has attracted considerable attention in the field of analyzing financial time series data, specifically within the stock market index. Moreover, stock market forecasting is a challenging area of financial time-series forecasting. In this study, a hybrid methodology between Empirical Mode Decomposition with the Holt-Winter method (EMD-HW) is used to improve forecasting performances in financial time series. The strength of this EMD-HW lies in its ability to forecast non-stationary and non-linear time series without a need to use any transformation method. Moreover, EMD-HW has a relatively high accuracy and offers a new forecasting method in time series. The daily stock market time series data of 11 countries is applied to show the forecasting performance of the proposed EMD-HW. Based on the three forecast accuracy measures, the results indicate that EMD-HW forecasting performance is superior to traditional Holt-Winter forecasting method.

  11. Using a Software Tool in Forecasting: a Case Study of Sales Forecasting Taking into Account Data Uncertainty

    NASA Astrophysics Data System (ADS)

    Fabianová, Jana; Kačmáry, Peter; Molnár, Vieroslav; Michalik, Peter

    2016-10-01

    Forecasting is one of the logistics activities and a sales forecast is the starting point for the elaboration of business plans. Forecast accuracy affects the business outcomes and ultimately may significantly affect the economic stability of the company. The accuracy of the prediction depends on the suitability of the use of forecasting methods, experience, quality of input data, time period and other factors. The input data are usually not deterministic but they are often of random nature. They are affected by uncertainties of the market environment, and many other factors. Taking into account the input data uncertainty, the forecast error can by reduced. This article deals with the use of the software tool for incorporating data uncertainty into forecasting. Proposals are presented of a forecasting approach and simulation of the impact of uncertain input parameters to the target forecasted value by this case study model. The statistical analysis and risk analysis of the forecast results is carried out including sensitivity analysis and variables impact analysis.

  12. Enhancing the Quality of Service for Real Time Traffic over Optical Burst Switching (OBS) Networks with Ensuring the Fairness for Other Traffics.

    PubMed

    Al-Shargabi, Mohammed A; Shaikh, Asadullah; Ismail, Abdulsamad S

    2016-01-01

    Optical burst switching (OBS) networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS) for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS' QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR) scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate) ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50-60%, 30-40%, and 10-20% for high, normal, and low traffic loads respectively.

  13. A Local Forecast of Land Surface Wetness Conditions, Drought, and St. Louis Encephalitis Virus Transmission Derived from Seasonal Climate Predictions

    NASA Astrophysics Data System (ADS)

    Shaman, J.; Stieglitz, M.; Zebiak, S.; Cane, M.; Day, J. F.

    2002-12-01

    We present an ensemble local hydrologic forecast derived from the seasonal forecasts of the International Research Institute (IRI) for Climate Prediction. Three- month seasonal forecasts were used to resample historical meteorological conditions and generate ensemble forcing datasets for a TOPMODEL-based hydrology model. Eleven retrospective forecasts were run at a Florida and New York site. Forecast skill was assessed for mean area modeled water table depth (WTD), i.e. near surface soil wetness conditions, and compared with WTD simulated with observed data. Hydrology model forecast skill was evident at the Florida site but not at the New York site. At the Florida site, persistence of hydrologic conditions and local skill of the IRI seasonal forecast contributed to the local hydrologic forecast skill. This forecast will permit probabilistic prediction of future hydrologic conditions. At the Florida site, we have also quantified the link between modeled WTD (i.e. drought) and the amplification and transmission of St. Louis Encephalitis virus (SLEV). We derive an empirical relationship between modeled land surface wetness and levels of SLEV transmission associated with human clinical cases. We then combine the seasonal forecasts of local, modeled WTD with this empirical relationship and produce retrospective probabilistic seasonal forecasts of epidemic SLEV transmission in Florida. Epidemic SLEV transmission forecast skill is demonstrated. These findings will permit real-time forecast of drought and resultant SLEV transmission in Florida.

  14. Exploring the interactions between forecast accuracy, risk perception and perceived forecast reliability in reservoir operator's decision to use forecast

    NASA Astrophysics Data System (ADS)

    Shafiee-Jood, M.; Cai, X.

    2017-12-01

    Advances in streamflow forecasts at different time scales offer a promise for proactive flood management and improved risk management. Despite the huge potential, previous studies have found that water resources managers are often not willing to incorporate streamflow forecasts information in decisions making, particularly in risky situations. While low accuracy of forecasts information is often cited as the main reason, some studies have found that implementation of streamflow forecasts sometimes is impeded by institutional obstacles and behavioral factors (e.g., risk perception). In fact, a seminal study by O'Connor et al. (2005) found that risk perception is the strongest determinant of forecast use while managers' perception about forecast reliability is not significant. In this study, we aim to address this issue again. However, instead of using survey data and regression analysis, we develop a theoretical framework to assess the user-perceived value of streamflow forecasts. The framework includes a novel behavioral component which incorporates both risk perception and perceived forecast reliability. The framework is then used in a hypothetical problem where reservoir operator should react to probabilistic flood forecasts with different reliabilities. The framework will allow us to explore the interactions among risk perception and perceived forecast reliability, and among the behavioral components and information accuracy. The findings will provide insights to improve the usability of flood forecasts information through better communication and education.

  15. Parametric decadal climate forecast recalibration (DeFoReSt 1.0)

    NASA Astrophysics Data System (ADS)

    Pasternack, Alexander; Bhend, Jonas; Liniger, Mark A.; Rust, Henning W.; Müller, Wolfgang A.; Ulbrich, Uwe

    2018-01-01

    Near-term climate predictions such as decadal climate forecasts are increasingly being used to guide adaptation measures. For near-term probabilistic predictions to be useful, systematic errors of the forecasting systems have to be corrected. While methods for the calibration of probabilistic forecasts are readily available, these have to be adapted to the specifics of decadal climate forecasts including the long time horizon of decadal climate forecasts, lead-time-dependent systematic errors (drift) and the errors in the representation of long-term changes and variability. These features are compounded by small ensemble sizes to describe forecast uncertainty and a relatively short period for which typically pairs of reforecasts and observations are available to estimate calibration parameters. We introduce the Decadal Climate Forecast Recalibration Strategy (DeFoReSt), a parametric approach to recalibrate decadal ensemble forecasts that takes the above specifics into account. DeFoReSt optimizes forecast quality as measured by the continuous ranked probability score (CRPS). Using a toy model to generate synthetic forecast observation pairs, we demonstrate the positive effect on forecast quality in situations with pronounced and limited predictability. Finally, we apply DeFoReSt to decadal surface temperature forecasts from the MiKlip prototype system and find consistent, and sometimes considerable, improvements in forecast quality compared with a simple calibration of the lead-time-dependent systematic errors.

  16. Analysis of vehicular traffic flow in the major areas of Kuala Lumpur utilizing open-traffic

    NASA Astrophysics Data System (ADS)

    Manogaran, Saargunawathy; Ali, Muhammad; Yusof, Kamaludin Mohamad; Suhaili, Ramdhan

    2017-09-01

    Vehicular traffic congestion occurs when a large number of drivers are overcrowded on the road and the traffic flow does not run smoothly. Traffic congestion causes chaos on the road and interruption to daily activities of users. Time consumed on road give lots of negative effects on productivity, social behavior, environmental and cost to economy. Congestion is worsens and leads to havoc during the emergency such as flood, accidents, road maintenance and etc., where behavior of traffic flow is always unpredictable and uncontrollable. Real-time and historical traffic data are critical inputs for most traffic flow analysis applications. Researcher attempt to predict traffic using simulations as there is no exact model of traffic flow exists due to its high complexity. Open Traffic is an open source platform available for traffic data analysis linked to Open Street Map (OSM). This research is aimed to study and understand the Open Traffic platform. The real-time traffic flow pattern in Kuala Lumpur area was successfully been extracted and analyzed using Open Traffic. It was observed that the congestion occurs on every major road in Kuala Lumpur and most of it owes to the offices and the economic and commercial centers during rush hours. At some roads the congestion occurs at night due to the tourism activities.

  17. 40 CFR Appendix A to Part 57 - Primary Nonferrous Smelter Order (NSO) Application

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... Profit and Loss Summary A.4 Historical Capital Investment Summary B.1 Pre-Control Revenue Forecast B.2 Pre-Control Cost Forecast B.3 Pre-Control Forecast Profit and Loss Summary B.4 Constant Controls Revenue Forecast B.5 Constant Controls Cost Forecast B.6 Constant Controls Forecast Profit and Loss...

  18. Proceedings of the Annual Federal Forecasters Conference (2nd, Washington, D.C., September 6-7, 1989).

    ERIC Educational Resources Information Center

    Sonnenberg, William; And Others

    The Second Annual Federal Forecasters Conference, "Forecasting and Public Policy", provided a forum where forecasters from various Federal agencies could meet and discuss aspects of forecasting in the U.S. Government. A total of 140 forecasters from 42 Federal agencies and other organizations attended the conference. Opening remarks by…

  19. The Federal Forecasters Conference-1997. Papers and Proceedings (9th, Washington, D.C., September 11, 1997).

    ERIC Educational Resources Information Center

    Gerald, Debra E., Ed.

    The Ninth Federal Forecasters Conference provided a forum in which forecasters from different federal agencies and other organizations could meet to discuss various aspects of forecasting in the United States. The theme was "Forecasting in an Era of Diminishing Resources." The conference was attended by 150 forecasters. A keynote address by…

  20. Properties of Traffic Risk Coefficient

    NASA Astrophysics Data System (ADS)

    Tang, Tie-Qiao; Huang, Hai-Jun; Shang, Hua-Yan; Xue, Yu

    2009-10-01

    We use the model with the consideration of the traffic interruption probability (Physica A 387(2008)6845) to study the relationship between the traffic risk coefficient and the traffic interruption probability. The analytical and numerical results show that the traffic interruption probability will reduce the traffic risk coefficient and that the reduction is related to the density, which shows that this model can improve traffic security.

  1. GloFAS-Seasonal: Operational Seasonal Ensemble River Flow Forecasts at the Global Scale

    NASA Astrophysics Data System (ADS)

    Emerton, Rebecca; Zsoter, Ervin; Smith, Paul; Salamon, Peter

    2017-04-01

    Seasonal hydrological forecasting has potential benefits for many sectors, including agriculture, water resources management and humanitarian aid. At present, no global scale seasonal hydrological forecasting system exists operationally; although smaller scale systems have begun to emerge around the globe over the past decade, a system providing consistent global scale seasonal forecasts would be of great benefit in regions where no other forecasting system exists, and to organisations operating at the global scale, such as disaster relief. We present here a new operational global ensemble seasonal hydrological forecast, currently under development at ECMWF as part of the Global Flood Awareness System (GloFAS). The proposed system, which builds upon the current version of GloFAS, takes the long-range forecasts from the ECMWF System4 ensemble seasonal forecast system (which incorporates the HTESSEL land surface scheme) and uses this runoff as input to the Lisflood routing model, producing a seasonal river flow forecast out to 4 months lead time, for the global river network. The seasonal forecasts will be evaluated using the global river discharge reanalysis, and observations where available, to determine the potential value of the forecasts across the globe. The seasonal forecasts will be presented as a new layer in the GloFAS interface, which will provide a global map of river catchments, indicating whether the catchment-averaged discharge forecast is showing abnormally high or low flows during the 4-month lead time. Each catchment will display the corresponding forecast as an ensemble hydrograph of the weekly-averaged discharge forecast out to 4 months, with percentile thresholds shown for comparison with the discharge climatology. The forecast visualisation is based on a combination of the current medium-range GloFAS forecasts and the operational EFAS (European Flood Awareness System) seasonal outlook, and aims to effectively communicate the nature of a seasonal outlook while providing useful information to users and partners. We demonstrate the first version of an operational GloFAS seasonal outlook, outlining the model set-up and presenting a first look at the seasonal forecasts that will be displayed in the GloFAS interface, and discuss the initial results of the forecast evaluation.

  2. Dynamic Density: An Air Traffic Management Metric

    NASA Technical Reports Server (NTRS)

    Laudeman, I. V.; Shelden, S. G.; Branstrom, R.; Brasil, C. L.

    1998-01-01

    The definition of a metric of air traffic controller workload based on air traffic characteristics is essential to the development of both air traffic management automation and air traffic procedures. Dynamic density is a proposed concept for a metric that includes both traffic density (a count of aircraft in a volume of airspace) and traffic complexity (a measure of the complexity of the air traffic in a volume of airspace). It was hypothesized that a metric that includes terms that capture air traffic complexity will be a better measure of air traffic controller workload than current measures based only on traffic density. A weighted linear dynamic density function was developed and validated operationally. The proposed dynamic density function includes a traffic density term and eight traffic complexity terms. A unit-weighted dynamic density function was able to account for an average of 22% of the variance in observed controller activity not accounted for by traffic density alone. A comparative analysis of unit weights, subjective weights, and regression weights for the terms in the dynamic density equation was conducted. The best predictor of controller activity was the dynamic density equation with regression-weighted complexity terms.

  3. Congestion control strategy on complex network with privilege traffic

    NASA Astrophysics Data System (ADS)

    Li, Shi-Bao; He, Ya; Liu, Jian-Hang; Zhang, Zhi-Gang; Huang, Jun-Wei

    The congestion control of traffic is one of the most important studies in complex networks. In the previous congestion algorithms, all the network traffic is assumed to have the same priority, and the privilege of traffic is ignored. In this paper, a privilege and common traffic congestion control routing strategy (PCR) based on the different priority of traffic is proposed, which can be devised to cope with the different traffic congestion situations. We introduce the concept of privilege traffic in traffic dynamics for the first time and construct a new traffic model which taking into account requirements with different priorities. Besides, a new factor Ui is introduced by the theoretical derivation to characterize the interaction between different traffic routing selection, furthermore, Ui is related to the network throughput. Since the joint optimization among different kinds of traffic is accomplished by PCR, the maximum value of Ui can be significantly reduced and the network performance can be improved observably. The simulation results indicate that the network throughput with PCR has a better performance than the other strategies. Moreover, the network capacity is improved by 25% at least. Additionally, the network throughput is also influenced by privilege traffic number and traffic priority.

  4. Ensemble flare forecasting: using numerical weather prediction techniques to improve space weather operations

    NASA Astrophysics Data System (ADS)

    Murray, S.; Guerra, J. A.

    2017-12-01

    One essential component of operational space weather forecasting is the prediction of solar flares. Early flare forecasting work focused on statistical methods based on historical flaring rates, but more complex machine learning methods have been developed in recent years. A multitude of flare forecasting methods are now available, however it is still unclear which of these methods performs best, and none are substantially better than climatological forecasts. Current operational space weather centres cannot rely on automated methods, and generally use statistical forecasts with a little human intervention. Space weather researchers are increasingly looking towards methods used in terrestrial weather to improve current forecasting techniques. Ensemble forecasting has been used in numerical weather prediction for many years as a way to combine different predictions in order to obtain a more accurate result. It has proved useful in areas such as magnetospheric modelling and coronal mass ejection arrival analysis, however has not yet been implemented in operational flare forecasting. Here we construct ensemble forecasts for major solar flares by linearly combining the full-disk probabilistic forecasts from a group of operational forecasting methods (ASSA, ASAP, MAG4, MOSWOC, NOAA, and Solar Monitor). Forecasts from each method are weighted by a factor that accounts for the method's ability to predict previous events, and several performance metrics (both probabilistic and categorical) are considered. The results provide space weather forecasters with a set of parameters (combination weights, thresholds) that allow them to select the most appropriate values for constructing the 'best' ensemble forecast probability value, according to the performance metric of their choice. In this way different forecasts can be made to fit different end-user needs.

  5. Fuzzy logic-based analogue forecasting and hybrid modelling of horizontal visibility

    NASA Astrophysics Data System (ADS)

    Tuba, Zoltán; Bottyán, Zsolt

    2018-04-01

    Forecasting visibility is one of the greatest challenges in aviation meteorology. At the same time, high accuracy visibility forecasts can significantly reduce or make avoidable weather-related risk in aviation as well. To improve forecasting visibility, this research links fuzzy logic-based analogue forecasting and post-processed numerical weather prediction model outputs in hybrid forecast. Performance of analogue forecasting model was improved by the application of Analytic Hierarchy Process. Then, linear combination of the mentioned outputs was applied to create ultra-short term hybrid visibility prediction which gradually shifts the focus from statistical to numerical products taking their advantages during the forecast period. It gives the opportunity to bring closer the numerical visibility forecast to the observations even it is wrong initially. Complete verification of categorical forecasts was carried out; results are available for persistence and terminal aerodrome forecasts (TAF) as well in order to compare. The average value of Heidke Skill Score (HSS) of examined airports of analogue and hybrid forecasts shows very similar results even at the end of forecast period where the rate of analogue prediction in the final hybrid output is 0.1-0.2 only. However, in case of poor visibility (1000-2500 m), hybrid (0.65) and analogue forecasts (0.64) have similar average of HSS in the first 6 h of forecast period, and have better performance than persistence (0.60) or TAF (0.56). Important achievement that hybrid model takes into consideration physics and dynamics of the atmosphere due to the increasing part of the numerical weather prediction. In spite of this, its performance is similar to the most effective visibility forecasting methods and does not follow the poor verification results of clearly numerical outputs.

  6. Large-scale measurement and modeling of backbone Internet traffic

    NASA Astrophysics Data System (ADS)

    Roughan, Matthew; Gottlieb, Joel

    2002-07-01

    There is a brewing controversy in the traffic modeling community concerning how to model backbone traffic. The fundamental work on self-similarity in data traffic appears to be contradicted by recent findings that suggest that backbone traffic is smooth. The traffic analysis work to date has focused on high-quality but limited-scope packet trace measurements; this limits its applicability to high-speed backbone traffic. This paper uses more than one year's worth of SNMP traffic data covering an entire Tier 1 ISP backbone to address the question of how backbone network traffic should be modeled. Although the limitations of SNMP measurements do not permit us to comment on the fine timescale behavior of the traffic, careful analysis of the data suggests that irrespective of the variation at fine timescales, we can construct a simple traffic model that captures key features of the observed traffic. Furthermore, the model's parameters are measurable using existing network infrastructure, making this model practical in a present-day operational network. In addition to its practicality, the model verifies basic statistical multiplexing results, and thus sheds deep insight into how smooth backbone traffic really is.

  7. WPC Maximum Heat Index Forecasts

    Science.gov Websites

    Forecasts for Western US CLICK ON MAPS FOR MAXIMUM HEAT INDEX AND PROBABILITY FORECASTS FROM SUN MAY 27 2018 02 CLICK to view SAT JUN 02 forecast SUN JUN 03 CLICK to view SUN JUN 03 forecast SUN JUN 03 CLICK to view SUN JUN 03 forecast SUN JUN 03 CLICK to view SUN JUN 03 forecast SUN JUN 03 CLICK to view SUN JUN

  8. Comparative analysis of characteristics and risk factors of traffic injury in aged people from urban and rural areas in Chongqing.

    PubMed

    Zhang, Liang; Zhou, Ji-Hong; Qiu, Jun; Zhang, Xiu-Zhu; Yuan, Dan-Feng; Gao, Zhi-Ming; Dai, Wei

    2012-01-01

    To study the epidemiologic characteristics of traffic injuries among people over 60 years old in the Nan'an district (urban) and Jiangjin district (rural) of Chongqing, and to discuss the corresponding strategies for its prevention and cure. Records of traffic injuries in people over 60 years old registered by the traffic police between 2000 and 2006 in Nan'an district and Jiangjin district were collected in the Database of Road Traffic Accidents and Traffic Injuries. Epidemiologic characteristics of traffic injuries among the aged people were analyzed and compared. Between the year 2000 and 2006, the average annual incidence of traffic injuries and mortality rate in the aged people in Nan'an district were 124.62/100 000 and 13.85/ 100 000 respectively, higher than that in Jiangjin district (27.49/ 100 000, 7.13/100 000, P less than 0.01). However, the mortality rate for the aged people who were involved in traffic injuries in Jiangjin district was 20.60%, higher than that in Nan'an district (10.00%, P less than 0.01). Head injury was the primary cause of death. Totally 76.58% of casualties were pede-strians. Over 90% of the traffic accidents occurred in the areas with no traffic signal or traffic control system. The traffic environment is unfavorable to the aged people. It is important to enhance traffic safety consciousness of drivers and the elderly and to strengthen traffic safety system and traffic law, so as to provide a safe road traffic environment for the aged people.

  9. 32 CFR 634.26 - Traffic law enforcement principles.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 32 National Defense 4 2011-07-01 2011-07-01 false Traffic law enforcement principles. 634.26... ENFORCEMENT AND CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.26 Traffic law enforcement principles. (a) Traffic law enforcement should motivate drivers to operate vehicles...

  10. 32 CFR 634.26 - Traffic law enforcement principles.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 32 National Defense 4 2010-07-01 2010-07-01 true Traffic law enforcement principles. 634.26... ENFORCEMENT AND CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.26 Traffic law enforcement principles. (a) Traffic law enforcement should motivate drivers to operate vehicles...

  11. EnrollForecast for Excel: K-12 Enrollment Forecasting Program. Software & User's Guide. [Computer Diskette].

    ERIC Educational Resources Information Center

    Smith, Curtis A.

    "EnrollForecast for Excel" will generate a 5-year forecast of K-12 student enrollment. It will also work for any combination of grades between kindergarten and twelth. The forecasts can be printed as either a table or a graph. The user must provide birth history (only if forecasting kindergarten) and enrollment history information. The user also…

  12. On the reliability of seasonal climate forecasts.

    PubMed

    Weisheimer, A; Palmer, T N

    2014-07-06

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

  13. Software forecasting as it is really done: A study of JPL software engineers

    NASA Technical Reports Server (NTRS)

    Griesel, Martha Ann; Hihn, Jairus M.; Bruno, Kristin J.; Fouser, Thomas J.; Tausworthe, Robert C.

    1993-01-01

    This paper presents a summary of the results to date of a Jet Propulsion Laboratory internally funded research task to study the costing process and parameters used by internally recognized software cost estimating experts. Protocol Analysis and Markov process modeling were used to capture software engineer's forecasting mental models. While there is significant variation between the mental models that were studied, it was nevertheless possible to identify a core set of cost forecasting activities, and it was also found that the mental models cluster around three forecasting techniques. Further partitioning of the mental models revealed clustering of activities, that is very suggestive of a forecasting lifecycle. The different forecasting methods identified were based on the use of multiple-decomposition steps or multiple forecasting steps. The multiple forecasting steps involved either forecasting software size or an additional effort forecast. Virtually no subject used risk reduction steps in combination. The results of the analysis include: the identification of a core set of well defined costing activities, a proposed software forecasting life cycle, and the identification of several basic software forecasting mental models. The paper concludes with a discussion of the implications of the results for current individual and institutional practices.

  14. Utilizing Climate Forecasts for Improving Water and Power Systems Coordination

    NASA Astrophysics Data System (ADS)

    Arumugam, S.; Queiroz, A.; Patskoski, J.; Mahinthakumar, K.; DeCarolis, J.

    2016-12-01

    Climate forecasts, typically monthly-to-seasonal precipitation forecasts, are commonly used to develop streamflow forecasts for improving reservoir management. Irrespective of their high skill in forecasting, temperature forecasts in developing power demand forecasts are not often considered along with streamflow forecasts for improving water and power systems coordination. In this study, we consider a prototype system to analyze the utility of climate forecasts, both precipitation and temperature, for improving water and power systems coordination. The prototype system, a unit-commitment model that schedules power generation from various sources, is considered and its performance is compared with an energy system model having an equivalent reservoir representation. Different skill sets of streamflow forecasts and power demand forecasts are forced on both water and power systems representations for understanding the level of model complexity required for utilizing monthly-to-seasonal climate forecasts to improve coordination between these two systems. The analyses also identify various decision-making strategies - forward purchasing of fuel stocks, scheduled maintenance of various power systems and tradeoff on water appropriation between hydropower and other uses - in the context of various water and power systems configurations. Potential application of such analyses for integrating large power systems with multiple river basins is also discussed.

  15. Verification of temperature, precipitation, and streamflow forecasts from the NOAA/NWS Hydrologic Ensemble Forecast Service (HEFS): 1. Experimental design and forcing verification

    NASA Astrophysics Data System (ADS)

    Brown, James D.; Wu, Limin; He, Minxue; Regonda, Satish; Lee, Haksu; Seo, Dong-Jun

    2014-11-01

    Retrospective forecasts of precipitation, temperature, and streamflow were generated with the Hydrologic Ensemble Forecast Service (HEFS) of the U.S. National Weather Service (NWS) for a 20-year period between 1979 and 1999. The hindcasts were produced for two basins in each of four River Forecast Centers (RFCs), namely the Arkansas-Red Basin RFC, the Colorado Basin RFC, the California-Nevada RFC, and the Middle Atlantic RFC. Precipitation and temperature forecasts were produced with the HEFS Meteorological Ensemble Forecast Processor (MEFP). Inputs to the MEFP comprised ;raw; precipitation and temperature forecasts from the frozen (circa 1997) version of the NWS Global Forecast System (GFS) and a climatological ensemble, which involved resampling historical observations in a moving window around the forecast valid date (;resampled climatology;). In both cases, the forecast horizon was 1-14 days. This paper outlines the hindcasting and verification strategy, and then focuses on the quality of the temperature and precipitation forecasts from the MEFP. A companion paper focuses on the quality of the streamflow forecasts from the HEFS. In general, the precipitation forecasts are more skillful than resampled climatology during the first week, but comprise little or no skill during the second week. In contrast, the temperature forecasts improve upon resampled climatology at all forecast lead times. However, there are notable differences among RFCs and for different seasons, aggregation periods and magnitudes of the observed and forecast variables, both for precipitation and temperature. For example, the MEFP-GFS precipitation forecasts show the highest correlations and greatest skill in the California Nevada RFC, particularly during the wet season (November-April). While generally reliable, the MEFP forecasts typically underestimate the largest observed precipitation amounts (a Type-II conditional bias). As a statistical technique, the MEFP cannot detect, and thus appropriately correct for, conditions that are undetected by the GFS. The calibration of the MEFP to provide reliable and skillful forecasts of a range of precipitation amounts (not only large amounts) is a secondary factor responsible for these Type-II conditional biases. Interpretation of the verification results leads to guidance on the expected performance and limitations of the MEFP, together with recommendations on future enhancements.

  16. Assessing the skill of seasonal precipitation and streamflow forecasts in sixteen French catchments

    NASA Astrophysics Data System (ADS)

    Crochemore, Louise; Ramos, Maria-Helena; Pappenberger, Florian

    2015-04-01

    Meteorological centres make sustained efforts to provide seasonal forecasts that are increasingly skilful. Streamflow forecasting is one of the many applications than can benefit from these efforts. Seasonal flow forecasts generated using seasonal ensemble precipitation forecasts as input to a hydrological model can help to take anticipatory measures for water supply reservoir operation or drought risk management. The objective of the study is to assess the skill of seasonal precipitation and streamflow forecasts in France. First, we evaluated the skill of ECMWF SYS4 seasonal precipitation forecasts for streamflow forecasting in sixteen French catchments. Daily flow forecasts were produced using raw seasonal precipitation forecasts as input to the GR6J hydrological model. Ensemble forecasts are issued every month with 15 or 51 members according to the month of the year and evaluated for up to 90 days ahead. In a second step, we applied eight variants of bias correction approaches to the precipitation forecasts prior to generating the flow forecasts. The approaches were based on the linear scaling and the distribution mapping methods. The skill of the ensemble forecasts was assessed in accuracy (MAE), reliability (PIT Diagram) and overall performance (CRPS). The results show that, in most catchments, raw seasonal precipitation and streamflow forecasts are more skilful in terms of accuracy and overall performance than a reference prediction based on historic observed precipitation and watershed initial conditions at the time of forecast. Reliability is the only attribute that is not significantly improved. The skill of the forecasts is, in general, improved when applying bias correction. Two bias correction methods showed the best performance for the studied catchments: the simple linear scaling of monthly values and the empirical distribution mapping of daily values. L. Crochemore is funded by the Interreg IVB DROP Project (Benefit of governance in DROught adaPtation).

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

    NASA Astrophysics Data System (ADS)

    Lall, U.

    2012-12-01

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

  18. A quality assessment of the MARS crop yield forecasting system for the European Union

    NASA Astrophysics Data System (ADS)

    van der Velde, Marijn; Bareuth, Bettina

    2015-04-01

    Timely information on crop production forecasts can become of increasing importance as commodity markets are more and more interconnected. Impacts across large crop production areas due to (e.g.) extreme weather and pest outbreaks can create ripple effects that may affect food prices and availability elsewhere. The MARS Unit (Monitoring Agricultural ResourceS), DG Joint Research Centre, European Commission, has been providing forecasts of European crop production levels since 1993. The operational crop production forecasting is carried out with the MARS Crop Yield Forecasting System (M-CYFS). The M-CYFS is used to monitor crop growth development, evaluate short-term effects of anomalous meteorological events, and provide monthly forecasts of crop yield at national and European Union level. The crop production forecasts are published in the so-called MARS bulletins. Forecasting crop yield over large areas in the operational context requires quality benchmarks. Here we present an analysis of the accuracy and skill of past crop yield forecasts of the main crops (e.g. soft wheat, grain maize), throughout the growing season, and specifically for the final forecast before harvest. Two simple benchmarks to assess the skill of the forecasts were defined as comparing the forecasts to 1) a forecast equal to the average yield and 2) a forecast using a linear trend established through the crop yield time-series. These reveal a variability in performance as a function of crop and Member State. In terms of production, the yield forecasts of 67% of the EU-28 soft wheat production and 80% of the EU-28 maize production have been forecast superior to both benchmarks during the 1993-2013 period. In a changing and increasingly variable climate crop yield forecasts can become increasingly valuable - provided they are used wisely. We end our presentation by discussing research activities that could contribute to this goal.

  19. Understanding Farmers’ Forecast Use from Their Beliefs, Values, Social Norms, and Perceived Obstacles

    NASA Astrophysics Data System (ADS)

    Hu, Qi; Pytlik Zillig, Lisa M.; Lynne, Gary D.; Tomkins, Alan J.; Waltman, William J.; Hayes, Michael J.; Hubbard, Kenneth G.; Artikov, Ikrom; Hoffman, Stacey J.; Wilhite, Donald A.

    2006-09-01

    Although the accuracy of weather and climate forecasts is continuously improving and new information retrieved from climate data is adding to the understanding of climate variation, use of the forecasts and climate information by farmers in farming decisions has changed little. This lack of change may result from knowledge barriers and psychological, social, and economic factors that undermine farmer motivation to use forecasts and climate information. According to the theory of planned behavior (TPB), the motivation to use forecasts may arise from personal attitudes, social norms, and perceived control or ability to use forecasts in specific decisions. These attributes are examined using data from a survey designed around the TPB and conducted among farming communities in the region of eastern Nebraska and the western U.S. Corn Belt. There were three major findings: 1) the utility and value of the forecasts for farming decisions as perceived by farmers are, on average, around 3.0 on a 0 7 scale, indicating much room to improve attitudes toward the forecast value. 2) The use of forecasts by farmers to influence decisions is likely affected by several social groups that can provide “expert viewpoints” on forecast use. 3) A major obstacle, next to forecast accuracy, is the perceived identity and reliability of the forecast makers. Given the rapidly increasing number of forecasts in this growing service business, the ambiguous identity of forecast providers may have left farmers confused and may have prevented them from developing both trust in forecasts and skills to use them. These findings shed light on productive avenues for increasing the influence of forecasts, which may lead to greater farming productivity. In addition, this study establishes a set of reference points that can be used for comparisons with future studies to quantify changes in forecast use and influence.

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  1. Enhancing the Quality of Service for Real Time Traffic over Optical Burst Switching (OBS) Networks with Ensuring the Fairness for Other Traffics

    PubMed Central

    Al-Shargabi, Mohammed A.; Ismail, Abdulsamad S.

    2016-01-01

    Optical burst switching (OBS) networks have been attracting much consideration as a promising approach to build the next generation optical Internet. A solution for enhancing the Quality of Service (QoS) for high priority real time traffic over OBS with the fairness among the traffic types is absent in current OBS’ QoS schemes. In this paper we present a novel Real Time Quality of Service with Fairness Ratio (RT-QoSFR) scheme that can adapt the burst assembly parameters according to the traffic QoS needs in order to enhance the real time traffic QoS requirements and to ensure the fairness for other traffic. The results show that RT-QoSFR scheme is able to fulfill the real time traffic requirements (end to end delay, and loss rate) ensuring the fairness for other traffics under various conditions such as the type of real time traffic and traffic load. RT-QoSFR can guarantee that the delay of the real time traffic packets does not exceed the maximum packets transfer delay value. Furthermore, it can reduce the real time traffic packets loss, at the same time guarantee the fairness for non real time traffic packets by determining the ratio of real time traffic inside the burst to be 50–60%, 30–40%, and 10–20% for high, normal, and low traffic loads respectively. PMID:27583557

  2. Accuracy of forecasts in strategic intelligence

    PubMed Central

    Mandel, David R.; Barnes, Alan

    2014-01-01

    The accuracy of 1,514 strategic intelligence forecasts abstracted from intelligence reports was assessed. The results show that both discrimination and calibration of forecasts was very good. Discrimination was better for senior (versus junior) analysts and for easier (versus harder) forecasts. Miscalibration was mainly due to underconfidence such that analysts assigned more uncertainty than needed given their high level of discrimination. Underconfidence was more pronounced for harder (versus easier) forecasts and for forecasts deemed more (versus less) important for policy decision making. Despite the observed underconfidence, there was a paucity of forecasts in the least informative 0.4–0.6 probability range. Recalibrating the forecasts substantially reduced underconfidence. The findings offer cause for tempered optimism about the accuracy of strategic intelligence forecasts and indicate that intelligence producers aim to promote informativeness while avoiding overstatement. PMID:25024176

  3. Seasonal forecast of St. Louis encephalitis virus transmission, Florida.

    PubMed

    Shaman, Jeffrey; Day, Jonathan F; Stieglitz, Marc; Zebiak, Stephen; Cane, Mark

    2004-05-01

    Disease transmission forecasts can help minimize human and domestic animal health risks by indicating where disease control and prevention efforts should be focused. For disease systems in which weather-related variables affect pathogen proliferation, dispersal, or transmission, the potential for disease forecasting exists. We present a seasonal forecast of St. Louis encephalitis virus transmission in Indian River County, Florida. We derive an empiric relationship between modeled land surface wetness and levels of SLEV transmission in humans. We then use these data to forecast SLEV transmission with a seasonal lead. Forecast skill is demonstrated, and a real-time seasonal forecast of epidemic SLEV transmission is presented. This study demonstrates how weather and climate forecast skill-verification analyses may be applied to test the predictability of an empiric disease forecast model.

  4. Seasonal Forecast of St. Louis Encephalitis Virus Transmission, Florida

    PubMed Central

    Day, Jonathan F.; Stieglitz, Marc; Zebiak, Stephen; Cane, Mark

    2004-01-01

    Disease transmission forecasts can help minimize human and domestic animal health risks by indicating where disease control and prevention efforts should be focused. For disease systems in which weather-related variables affect pathogen proliferation, dispersal, or transmission, the potential for disease forecasting exists. We present a seasonal forecast of St. Louis encephalitis virus transmission in Indian River County, Florida. We derive an empirical relationship between modeled land surface wetness and levels of SLEV transmission in humans. We then use these data to forecast SLEV transmission with a seasonal lead. Forecast skill is demonstrated, and a real-time seasonal forecast of epidemic SLEV transmission is presented. This study demonstrates how weather and climate forecast skill verification analyses may be applied to test the predictability of an empirical disease forecast model. PMID:15200812

  5. Transition Characteristic Analysis of Traffic Evolution Process for Urban Traffic Network

    PubMed Central

    Chen, Hong; Li, Yang

    2014-01-01

    The characterization of the dynamics of traffic states remains fundamental to seeking for the solutions of diverse traffic problems. To gain more insights into traffic dynamics in the temporal domain, this paper explored temporal characteristics and distinct regularity in the traffic evolution process of urban traffic network. We defined traffic state pattern through clustering multidimensional traffic time series using self-organizing maps and construct a pattern transition network model that is appropriate for representing and analyzing the evolution progress. The methodology is illustrated by an application to data flow rate of multiple road sections from Network of Shenzhen's Nanshan District, China. Analysis and numerical results demonstrated that the methodology permits extracting many useful traffic transition characteristics including stability, preference, activity, and attractiveness. In addition, more information about the relationships between these characteristics was extracted, which should be helpful in understanding the complex behavior of the temporal evolution features of traffic patterns. PMID:24982969

  6. Scheduling logic for Miles-In-Trail traffic management

    NASA Technical Reports Server (NTRS)

    Synnestvedt, Robert G.; Swenson, Harry; Erzberger, Heinz

    1995-01-01

    This paper presents an algorithm which can be used for scheduling arrival air traffic in an Air Route Traffic Control Center (ARTCC or Center) entering a Terminal Radar Approach Control (TRACON) Facility . The algorithm aids a Traffic Management Coordinator (TMC) in deciding how to restrict traffic while the traffic expected to arrive in the TRACON exceeds the TRACON capacity. The restrictions employed fall under the category of Miles-in-Trail, one of two principal traffic separation techniques used in scheduling arrival traffic . The algorithm calculates aircraft separations for each stream of aircraft destined to the TRACON. The calculations depend upon TRACON characteristics, TMC preferences, and other parameters adapted to the specific needs of scheduling traffic in a Center. Some preliminary results of traffic simulations scheduled by this algorithm are presented, and conclusions are drawn as to the effectiveness of using this algorithm in different traffic scenarios.

  7. Comparative Analysis of NOAA REFM and SNB3GEO Tools for the Forecast of the Fluxes of High-Energy Electrons at GEO

    NASA Technical Reports Server (NTRS)

    Balikhin, M. A.; Rodriguez, J. V.; Boynton, R. J.; Walker, S. N.; Aryan, Homayon; Sibeck, D. G.; Billings, S. A.

    2016-01-01

    Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB3GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB3GEO forecasts use solar wind density and interplanetary magnetic field B(sub z) observations at L1. The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB3GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB3GEO forecast.

  8. Comparative analysis of NOAA REFM and SNB3GEO tools for the forecast of the fluxes of high-energy electrons at GEO.

    PubMed

    Balikhin, M A; Rodriguez, J V; Boynton, R J; Walker, S N; Aryan, H; Sibeck, D G; Billings, S A

    2016-01-01

    Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB 3 GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB 3 GEO forecasts use solar wind density and interplanetary magnetic field B z observations at L1.The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB 3 GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB 3 GEO forecast.

  9. 32 CFR 634.32 - Traffic violation reports.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 32 National Defense 4 2011-07-01 2011-07-01 false Traffic violation reports. 634.32 Section 634.32... CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.32 Traffic violation reports. (a) Most traffic violations occurring on DOD installations (within the UNITED STATES or its...

  10. 32 CFR 634.32 - Traffic violation reports.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 32 National Defense 4 2010-07-01 2010-07-01 true Traffic violation reports. 634.32 Section 634.32... CRIMINAL INVESTIGATIONS MOTOR VEHICLE TRAFFIC SUPERVISION Traffic Supervision § 634.32 Traffic violation reports. (a) Most traffic violations occurring on DOD installations (within the UNITED STATES or its...

  11. A refined and dynamic cellular automaton model for pedestrian-vehicle mixed traffic flow

    NASA Astrophysics Data System (ADS)

    Liu, Mianfang; Xiong, Shengwu

    2016-12-01

    Mixed traffic flow sharing the “same lane” and having no discipline on road is a common phenomenon in the developing countries. For example, motorized vehicles (m-vehicles) and nonmotorized vehicles (nm-vehicles) may share the m-vehicle lane or nm-vehicle lane and pedestrians may share the nm-vehicle lane. Simulating pedestrian-vehicle mixed traffic flow consisting of three kinds of traffic objects: m-vehicles, nm-vehicles and pedestrians, can be a challenge because there are some erratic drivers or pedestrians who fail to follow the lane disciplines. In the paper, we investigate various moving and interactive behavior associated with mixed traffic flow, such as lateral drift including illegal lane-changing and transverse crossing different lanes, overtaking and forward movement, and propose some new moving and interactive rules for pedestrian-vehicle mixed traffic flow based on a refined and dynamic cellular automaton (CA) model. Simulation results indicate that the proposed model can be used to investigate the traffic flow characteristic in a mixed traffic flow system and corresponding complicated traffic problems, such as, the moving characteristics of different traffic objects, interaction phenomenon between different traffic objects, traffic jam, traffic conflict, etc., which are consistent with the actual mixed traffic system. Therefore, the proposed model provides a solid foundation for the management, planning and evacuation of the mixed traffic flow.

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  13. Skillful Spring Forecasts of September Arctic Sea Ice Extent Using Passive Microwave Data

    NASA Technical Reports Server (NTRS)

    Petty, A. A.; Schroder, D.; Stroeve, J. C.; Markus, Thorsten; Miller, Jeffrey A.; Kurtz, Nathan Timothy; Feltham, D. L.; Flocco, D.

    2017-01-01

    In this study, we demonstrate skillful spring forecasts of detrended September Arctic sea ice extent using passive microwave observations of sea ice concentration (SIC) and melt onset (MO). We compare these to forecasts produced using data from a sophisticated melt pond model, and find similar to higher skill values, where the forecast skill is calculated relative to linear trend persistence. The MO forecasts shows the highest skill in March-May, while the SIC forecasts produce the highest skill in June-August, especially when the forecasts are evaluated over recent years (since 2008). The high MO forecast skill in early spring appears to be driven primarily by the presence and timing of open water anomalies, while the high SIC forecast skill appears to be driven by both open water and surface melt processes. Spatial maps of detrended anomalies highlight the drivers of the different forecasts, and enable us to understand regions of predictive importance. Correctly capturing sea ice state anomalies, along with changes in open water coverage appear to be key processes in skillfully forecasting summer Arctic sea ice.

  14. Traffic pollution and countermeasures of urban traffic environment

    NASA Astrophysics Data System (ADS)

    He, Yuhong; Zheng, Chaocheng

    2018-01-01

    Background: Traffic environment has become a serious social problem in China currently, therefore, urban traffic environment governance is the requirement to solve this issue because as an important place in people's social life, urban traffic environment shows a strong city's energy. Objective: Based on analysis on social function of city traffic environment and its influence of traffic on urban environment in this paper, the goal to establish a healthy urban traffic environment must be included under the aim of sustainable development eternally and feasible measures were put forward afterwards. Method, result, conclusion and possible applications.

  15. Why Don't We Learn to Accurately Forecast Feelings? How Misremembering Our Predictions Blinds Us to Past Forecasting Errors

    ERIC Educational Resources Information Center

    Meyvis, Tom; Ratner, Rebecca K.; Levav, Jonathan

    2010-01-01

    Why do affective forecasting errors persist in the face of repeated disconfirming evidence? Five studies demonstrate that people misremember their forecasts as consistent with their experience and thus fail to perceive the extent of their forecasting error. As a result, people do not learn from past forecasting errors and fail to adjust subsequent…

  16. Assessing the viability of `over-the-loop' real-time short-to-medium range ensemble streamflow forecasts

    NASA Astrophysics Data System (ADS)

    Wood, A. W.; Clark, E.; Mendoza, P. A.; Nijssen, B.; Newman, A. J.; Clark, M. P.; Arnold, J.; Nowak, K. C.

    2016-12-01

    Many if not most national operational short-to-medium range streamflow prediction systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow are automated, but others require the hands-on-effort of an experienced human forecaster. This approach evolved out of the need to correct for deficiencies in the models and datasets that were available for forecasting, and often leads to skillful predictions despite the use of relatively simple, conceptual models. On the other hand, the process is not reproducible, which limits opportunities to assess and incorporate process variations, 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 ensembles and hindcasts that can support verification. In the last decade, the hydrologic forecasting community has begun to 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, the operational streamflow forecasting and water management communities have little experience with the strengths and weaknesses of over-the-loop approaches, even as the systems are being rolled out in major operational forecasting centers. 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 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' (SHARP) to implement, assess and demonstrate real-time over-the-loop forecasts. We present early hindcast and verification results from SHARP for short to medium range streamflow forecasts in a number of US case study watersheds.

  17. Assessment of an ensemble seasonal streamflow forecasting system for Australia

    NASA Astrophysics Data System (ADS)

    Bennett, James C.; Wang, Quan J.; Robertson, David E.; Schepen, Andrew; Li, Ming; Michael, Kelvin

    2017-11-01

    Despite an increasing availability of skilful long-range streamflow forecasts, many water agencies still rely on simple resampled historical inflow sequences (stochastic scenarios) to plan operations over the coming year. We assess a recently developed forecasting system called forecast guided stochastic scenarios (FoGSS) as a skilful alternative to standard stochastic scenarios for the Australian continent. FoGSS uses climate forecasts from a coupled ocean-land-atmosphere prediction system, post-processed with the method of calibration, bridging and merging. Ensemble rainfall forecasts force a monthly rainfall-runoff model, while a staged hydrological error model quantifies and propagates hydrological forecast uncertainty through forecast lead times. FoGSS is able to generate ensemble streamflow forecasts in the form of monthly time series to a 12-month forecast horizon. FoGSS is tested on 63 Australian catchments that cover a wide range of climates, including 21 ephemeral rivers. In all perennial and many ephemeral catchments, FoGSS provides an effective alternative to resampled historical inflow sequences. FoGSS generally produces skilful forecasts at shorter lead times ( < 4 months), and transits to climatology-like forecasts at longer lead times. Forecasts are generally reliable and unbiased. However, FoGSS does not perform well in very dry catchments (catchments that experience zero flows more than half the time in some months), sometimes producing strongly negative forecast skill and poor reliability. We attempt to improve forecasts through the use of (i) ESP rainfall forcings, (ii) different rainfall-runoff models, and (iii) a Bayesian prior to encourage the error model to return climatology forecasts in months when the rainfall-runoff model performs poorly. Of these, the use of the prior offers the clearest benefit in very dry catchments, where it moderates strongly negative forecast skill and reduces bias in some instances. However, the prior does not remedy poor reliability in very dry catchments. Overall, FoGSS is an attractive alternative to historical inflow sequences in all but the driest catchments. We discuss ways in which forecast reliability in very dry catchments could be improved in future work.

  18. Evaluation of streamflow forecast for the National Water Model of U.S. National Weather Service

    NASA Astrophysics Data System (ADS)

    Rafieeinasab, A.; McCreight, J. L.; Dugger, A. L.; Gochis, D.; Karsten, L. R.; Zhang, Y.; Cosgrove, B.; Liu, Y.

    2016-12-01

    The National Water Model (NWM), an implementation of the community WRF-Hydro modeling system, is an operational hydrologic forecasting model for the contiguous United States. The model forecasts distributed hydrologic states and fluxes, including soil moisture, snowpack, ET, and ponded water. In particular, the NWM provides streamflow forecasts at more than 2.7 million river reaches for three forecast ranges: short (15 hr), medium (10 days), and long (30 days). In this study, we verify short and medium range streamflow forecasts in the context of the verification of their respective quantitative precipitation forecasts/forcing (QPF), the High Resolution Rapid Refresh (HRRR) and the Global Forecast System (GFS). The streamflow evaluation is performed for summer of 2016 at more than 6,000 USGS gauges. Both individual forecasts and forecast lead times are examined. Selected case studies of extreme events aim to provide insight into the quality of the NWM streamflow forecasts. A goal of this comparison is to address how much streamflow bias originates from precipitation forcing bias. To this end, precipitation verification is performed over the contributing areas above (and between assimilated) USGS gauge locations. Precipitation verification is based on the aggregated, blended StageIV/StageII data as the "reference truth". We summarize the skill of the streamflow forecasts, their skill relative to the QPF, and make recommendations for improving NWM forecast skill.

  19. Traffic Vehicle Counting in Jam Flow Conditions Using Low-Cost and Energy-Efficient Wireless Magnetic Sensors.

    PubMed

    Bao, Xu; Li, Haijian; Xu, Dongwei; Jia, Limin; Ran, Bin; Rong, Jian

    2016-11-06

    The jam flow condition is one of the main traffic states in traffic flow theory and the most difficult state for sectional traffic information acquisition. Since traffic information acquisition is the basis for the application of an intelligent transportation system, research on traffic vehicle counting methods for the jam flow conditions has been worthwhile. A low-cost and energy-efficient type of multi-function wireless traffic magnetic sensor was designed and developed. Several advantages of the traffic magnetic sensor are that it is suitable for large-scale deployment and time-sustainable detection for traffic information acquisition. Based on the traffic magnetic sensor, a basic vehicle detection algorithm (DWVDA) with less computational complexity was introduced for vehicle counting in low traffic volume conditions. To improve the detection performance in jam flow conditions with a "tailgating effect" between front vehicles and rear vehicles, an improved vehicle detection algorithm (SA-DWVDA) was proposed and applied in field traffic environments. By deploying traffic magnetic sensor nodes in field traffic scenarios, two field experiments were conducted to test and verify the DWVDA and the SA-DWVDA algorithms. The experimental results have shown that both DWVDA and the SA-DWVDA algorithms yield a satisfactory performance in low traffic volume conditions (scenario I) and both of their mean absolute percent errors are less than 1% in this scenario. However, for jam flow conditions with heavy traffic volumes (scenario II), the SA-DWVDA was proven to achieve better results, and the mean absolute percent error of the SA-DWVDA is 2.54% with corresponding results of the DWVDA 7.07%. The results conclude that the proposed SA-DWVDA can implement efficient and accurate vehicle detection in jam flow conditions and can be employed in field traffic environments.

  20. Did Chile's traffic law reform push police enforcement? Understanding Chile's traffic fatalities and injuries reduction.

    PubMed

    Nazif-Munoz, José Ignacio; Quesnel-Vallée, Amélie; van den Berg, Axel

    2015-06-01

    The objective of the current study is to determine to what extent the reduction of Chile's traffic fatalities and injuries during 2000-2012 was related to the police traffic enforcement increment registered after the introduction of its 2005 traffic law reform. A unique dataset with assembled information from public institutions and analyses based on ordinary least square and robust random effects models was carried out. Dependent variables were traffic fatality and severe injury rates per population and vehicle fleet. Independent variables were: (1) presence of new national traffic law; (2) police officers per population; (3) number of traffic tickets per police officer; and (4) interaction effect of number of traffic tickets per police officer with traffic law reform. Oil prices, alcohol consumption, proportion of male population 15-24 years old, unemployment, road infrastructure investment, years' effects and regions' effects represented control variables. Empirical estimates from instrumental variables suggest that the enactment of the traffic law reform in interaction with number of traffic tickets per police officer is significantly associated with a decrease of 8% in traffic fatalities and 7% in severe injuries. Piecewise regression model results for the 2007-2012 period suggest that police traffic enforcement reduced traffic fatalities by 59% and severe injuries by 37%. Findings suggest that traffic law reforms in order to have an effect on both traffic fatality and injury rates reduction require changes in police enforcement practices. Last, this case also illustrates how the diffusion of successful road safety practices globally promoted by WHO and World Bank can be an important influence for enhancing national road safety practices. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  1. Traffic Vehicle Counting in Jam Flow Conditions Using Low-Cost and Energy-Efficient Wireless Magnetic Sensors

    PubMed Central

    Bao, Xu; Li, Haijian; Xu, Dongwei; Jia, Limin; Ran, Bin; Rong, Jian

    2016-01-01

    The jam flow condition is one of the main traffic states in traffic flow theory and the most difficult state for sectional traffic information acquisition. Since traffic information acquisition is the basis for the application of an intelligent transportation system, research on traffic vehicle counting methods for the jam flow conditions has been worthwhile. A low-cost and energy-efficient type of multi-function wireless traffic magnetic sensor was designed and developed. Several advantages of the traffic magnetic sensor are that it is suitable for large-scale deployment and time-sustainable detection for traffic information acquisition. Based on the traffic magnetic sensor, a basic vehicle detection algorithm (DWVDA) with less computational complexity was introduced for vehicle counting in low traffic volume conditions. To improve the detection performance in jam flow conditions with a “tailgating effect” between front vehicles and rear vehicles, an improved vehicle detection algorithm (SA-DWVDA) was proposed and applied in field traffic environments. By deploying traffic magnetic sensor nodes in field traffic scenarios, two field experiments were conducted to test and verify the DWVDA and the SA-DWVDA algorithms. The experimental results have shown that both DWVDA and the SA-DWVDA algorithms yield a satisfactory performance in low traffic volume conditions (scenario I) and both of their mean absolute percent errors are less than 1% in this scenario. However, for jam flow conditions with heavy traffic volumes (scenario II), the SA-DWVDA was proven to achieve better results, and the mean absolute percent error of the SA-DWVDA is 2.54% with corresponding results of the DWVDA 7.07%. The results conclude that the proposed SA-DWVDA can implement efficient and accurate vehicle detection in jam flow conditions and can be employed in field traffic environments. PMID:27827974

  2. A Wind Forecasting System for Energy Application

    NASA Astrophysics Data System (ADS)

    Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

    2010-05-01

    Accurate forecasting of available energy is crucial for the efficient management and use of wind power in the national power grid. With energy output critically dependent upon wind strength there is a need to reduce the errors associated wind forecasting. The objective of this research is to get the best possible wind forecasts for the wind energy industry. To achieve this goal, three methods are being applied. First, a mesoscale numerical weather prediction (NWP) model called WRF (Weather Research and Forecasting) is being used to predict wind values over Ireland. Currently, a gird resolution of 10km is used and higher model resolutions are being evaluated to establish whether they are economically viable given the forecast skill improvement they produce. Second, the WRF model is being used in conjunction with ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble forecasts to produce a probabilistic weather forecasting product. Due to the chaotic nature of the atmosphere, a single, deterministic weather forecast can only have limited skill. The ECMWF ensemble methods produce an ensemble of 51 global forecasts, twice a day, by perturbing initial conditions of a 'control' forecast which is the best estimate of the initial state of the atmosphere. This method provides an indication of the reliability of the forecast and a quantitative basis for probabilistic forecasting. The limitation of ensemble forecasting lies in the fact that the perturbed model runs behave differently under different weather patterns and each model run is equally likely to be closest to the observed weather situation. Models have biases, and involve assumptions about physical processes and forcing factors such as underlying topography. Third, Bayesian Model Averaging (BMA) is being applied to the output from the ensemble forecasts in order to statistically post-process the results and achieve a better wind forecasting system. BMA is a promising technique that will offer calibrated probabilistic wind forecasts which will be invaluable in wind energy management. In brief, this method turns the ensemble forecasts into a calibrated predictive probability distribution. Each ensemble member is provided with a 'weight' determined by its relative predictive skill over a training period of around 30 days. Verification of data is carried out using observed wind data from operational wind farms. These are then compared to existing forecasts produced by ECMWF and Met Eireann in relation to skill scores. We are developing decision-making models to show the benefits achieved using the data produced by our wind energy forecasting system. An energy trading model will be developed, based on the rules currently used by the Single Electricity Market Operator for energy trading in Ireland. This trading model will illustrate the potential for financial savings by using the forecast data generated by this research.

  3. Evaluation and analysis of noise levels at traffic intersections of Nagpur city, India.

    PubMed

    Vijay, Ritesh; Popat, Rishabh; Pisode, Mayur; Sharma, Asheesh; Manoj, Kumar; Chakrabarti, T; Gupta, Rajesh

    2013-04-01

    The objective of the present study was to monitor and assess the noise levels at traffic intersections in Napgur city under heterogenic traffic activities. For this, traffic volume and noise level were measured at intersections on highways, major roads andring road during morning and evening peak hours. Traffic volume was categorized in light, medium and heavy vehicles while noise levels were measured for Lmin, Lmax, Leq , L10 and L90. Equivalent noise was observed in the range of 71.3 to 79.3 dB(A) at the traffic intersections. Due to heterogenic traffic conditions and activities at the intersection like honking, idling, gear noise, bearing noise, breaking noise, tyre-road noise and exhaust noise, no correlation was established between traffic volume and observed noise levels except West High Court road. A strong correlation was found at West High Court road due to controlled traffic flow and less impact of heavy vehicles. Impact of noisy vehicles on general traffic was also assessed at the traffic intersections based on noise pollution levels and traffic noise index. The study suggests that control measures are required at the traffic intersections to minimize noise pollution levels.

  4. Superensemble forecasts of dengue outbreaks

    PubMed Central

    Kandula, Sasikiran; Shaman, Jeffrey

    2016-01-01

    In recent years, a number of systems capable of predicting future infectious disease incidence have been developed. As more of these systems are operationalized, it is important that the forecasts generated by these different approaches be formally reconciled so that individual forecast error and bias are reduced. Here we present a first example of such multi-system, or superensemble, forecast. We develop three distinct systems for predicting dengue, which are applied retrospectively to forecast outbreak characteristics in San Juan, Puerto Rico. We then use Bayesian averaging methods to combine the predictions from these systems and create superensemble forecasts. We demonstrate that on average, the superensemble approach produces more accurate forecasts than those made from any of the individual forecasting systems. PMID:27733698

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

    USGS Publications Warehouse

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

    2004-01-01

    This paper examines an archive containing over 40 years of 8-day atmospheric forecasts over the contiguous United States from the NCEP reanalysis project to assess the possibilities for using medium-range numerical weather prediction model output for predictions of streamflow. This analysis shows the biases in the NCEP forecasts to be quite extreme. In many regions, systematic precipitation biases exceed 100% of the mean, with temperature biases exceeding 3??C. In some locations, biases are even higher. The accuracy of NCEP precipitation and 2-m maximum temperature forecasts is computed by interpolating the NCEP model output for each forecast day to the location of each station in the NWS cooperative network and computing the correlation with station observations. Results show that the accuracy of the NCEP forecasts is rather low in many areas of the country. Most apparent is the generally low skill in precipitation forecasts (particularly in July) and low skill in temperature forecasts in the western United States, the eastern seaboard, and the southern tier of states. These results outline a clear need for additional processing of the NCEP Medium-Range Forecast Model (MRF) output before it is used for hydrologic predictions. Techniques of model output statistics (MOS) are used in this paper to downscale the NCEP forecasts to station locations. Forecasted atmospheric variables (e.g., total column precipitable water, 2-m air temperature) are used as predictors in a forward screening multiple linear regression model to improve forecasts of precipitation and temperature for stations in the National Weather Service cooperative network. This procedure effectively removes all systematic biases in the raw NCEP precipitation and temperature forecasts. MOS guidance also results in substantial improvements in the accuracy of maximum and minimum temperature forecasts throughout the country. For precipitation, forecast improvements were less impressive. MOS guidance increases he accuracy of precipitation forecasts over the northeastern United States, but overall, the accuracy of MOS-based precipitation forecasts is slightly lower than the raw NCEP forecasts. Four basins in the United States were chosen as case studies to evaluate the value of MRF output for predictions of streamflow. Streamflow forecasts using MRF output were generated for one rainfall-dominated basin (Alapaha River at Statenville, Georgia) and three snowmelt-dominated basins (Animas River at Durango, Colorado: East Fork of the Carson River near Gardnerville, Nevada: and Cle Elum River near Roslyn, Washington). Hydrologic model output forced with measured-station data were used as "truth" to focus attention on the hydrologic effects of errors in the MRF forecasts. Eight-day streamflow forecasts produced using the MOS-corrected MRF output as input (MOS) were compared with those produced using the climatic Ensemble Streamflow Prediction (ESP) technique. MOS-based streamflow forecasts showed increased skill in the snowmelt-dominated river basins, where daily variations in streamflow are strongly forced by temperature. In contrast, the skill of MOS forecasts in the rainfall-dominated basin (the Alapaha River) were equivalent to the skill of the ESP forecasts. Further improvements in streamflow forecasts require more accurate local-scale forecasts of precipitation and temperature, more accurate specification of basin initial conditions, and more accurate model simulations of streamflow. ?? 2004 American Meteorological Society.

  6. HESS Opinions "On forecast (in)consistency in a hydro-meteorological chain: curse or blessing?"

    NASA Astrophysics Data System (ADS)

    Pappenberger, F.; Cloke, H. L.; Persson, A.; Demeritt, D.

    2011-07-01

    Flood forecasting increasingly relies on numerical weather prediction forecasts to achieve longer lead times. One of the key difficulties that is emerging in constructing a decision framework for these flood forecasts is what to dowhen consecutive forecasts are so different that they lead to different conclusions regarding the issuing of warnings or triggering other action. In this opinion paper we explore some of the issues surrounding such forecast inconsistency (also known as "Jumpiness", "Turning points", "Continuity" or number of "Swings"). In thsi opinion paper we define forecast inconsistency; discuss the reasons why forecasts might be inconsistent; how we should analyse inconsistency; and what we should do about it; how we should communicate it and whether it is a totally undesirable property. The property of consistency is increasingly emerging as a hot topic in many forecasting environments.

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

    PubMed

    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. Skill of a global seasonal ensemble streamflow forecasting system

    NASA Astrophysics Data System (ADS)

    Candogan Yossef, Naze; Winsemius, Hessel; Weerts, Albrecht; van Beek, Rens; Bierkens, Marc

    2013-04-01

    Forecasting of water availability and scarcity is a prerequisite for managing the risks and opportunities caused by the inter-annual variability of streamflow. Reliable seasonal streamflow forecasts are necessary to prepare for an appropriate response in disaster relief, management of hydropower reservoirs, water supply, agriculture and navigation. Seasonal hydrological forecasting on a global scale could be valuable especially for developing regions of the world, where effective hydrological forecasting systems are scarce. In this study, we investigate the forecasting skill of the global seasonal streamflow forecasting system FEWS-World, using the global hydrological model PCR-GLOBWB. FEWS-World has been setup within the European Commission 7th Framework Programme project Global Water Scarcity Information Service (GLOWASIS). Skill is assessed in historical simulation mode as well as retroactive forecasting mode. The assessment in historical simulation mode used a meteorological forcing based on observations from the Climate Research Unit of the University of East Anglia and the ERA-40 reanalysis of the European Center for Medium-Range Weather Forecasts (ECMWF). We assessed the skill of the global hydrological model PCR-GLOBWB in reproducing past discharge extremes in 20 large rivers of the world. This preliminary assessment concluded that the prospects for seasonal forecasting with PCR-GLOBWB or comparable models are positive. However this assessment did not include actual meteorological forecasts. Thus the meteorological forcing errors were not assessed. Yet, in a forecasting setup, the predictive skill of a hydrological forecasting system is affected by errors due to uncertainty from numerical weather prediction models. For the assessment in retroactive forecasting mode, the model is forced with actual ensemble forecasts from the seasonal forecast archives of ECMWF. Skill is assessed at 78 stations on large river basins across the globe, for all the months of the year and for lead times up to 6 months. The forecasted discharges are compared with observed monthly streamflow records using the ensemble verification measures Brier Skill Score (BSS) and Continuous Ranked Probability Score (CRPS). The eventual goal is to transfer FEWS-World to operational forecasting mode, where the system will use operational seasonal forecasts from ECMWF. The results will be disseminated on the internet, and hopefully provide information that is valuable for users in data and model-poor regions of the world.

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

    PubMed Central

    Gajowniczek, Krzysztof; Ząbkowski, Tomasz

    2017-01-01

    Leveraging smart metering solutions to support energy efficiency on the individual household level poses novel research challenges in monitoring usage and providing accurate load forecasting. Forecasting electricity usage is an especially important component that can provide intelligence to smart meters. In this paper, we propose an enhanced approach for load forecasting at the household level. The impacts of residents’ daily activities and appliance usages on the power consumption of the entire household are incorporated to improve the accuracy of the forecasting model. The contributions of this paper are threefold: (1) we addressed short-term electricity load forecasting for 24 hours ahead, not on the aggregate but on the individual household level, which fits into the Residential Power Load Forecasting (RPLF) methods; (2) for the forecasting, we utilized a household specific dataset of behaviors that influence power consumption, which was derived using segmentation and sequence mining algorithms; and (3) an extensive load forecasting study using different forecasting algorithms enhanced by the household activity patterns was undertaken. PMID:28423039

  10. Assimilation of lightning data by nudging tropospheric water vapor and applications to numerical forecasts of convective events

    NASA Astrophysics Data System (ADS)

    Dixon, Kenneth

    A lightning data assimilation technique is developed for use with observations from the World Wide Lightning Location Network (WWLLN). The technique nudges the water vapor mixing ratio toward saturation within 10 km of a lightning observation. This technique is applied to deterministic forecasts of convective events on 29 June 2012, 17 November 2013, and 19 April 2011 as well as an ensemble forecast of the 29 June 2012 event using the Weather Research and Forecasting (WRF) model. Lightning data are assimilated over the first 3 hours of the forecasts, and the subsequent impact on forecast quality is evaluated. The nudged deterministic simulations for all events produce composite reflectivity fields that are closer to observations. For the ensemble forecasts of the 29 June 2012 event, the improvement in forecast quality from lightning assimilation is more subtle than for the deterministic forecasts, suggesting that the lightning assimilation may improve ensemble convective forecasts where conventional observations (e.g., aircraft, surface, radiosonde, satellite) are less dense or unavailable.

  11. Combining forecast weights: Why and how?

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

  12. Algorithm aversion: people erroneously avoid algorithms after seeing them err.

    PubMed

    Dietvorst, Berkeley J; Simmons, Joseph P; Massey, Cade

    2015-02-01

    Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster. This phenomenon, which we call algorithm aversion, is costly, and it is important to understand its causes. We show that people are especially averse to algorithmic forecasters after seeing them perform, even when they see them outperform a human forecaster. This is because people more quickly lose confidence in algorithmic than human forecasters after seeing them make the same mistake. In 5 studies, participants either saw an algorithm make forecasts, a human make forecasts, both, or neither. They then decided whether to tie their incentives to the future predictions of the algorithm or the human. Participants who saw the algorithm perform were less confident in it, and less likely to choose it over an inferior human forecaster. This was true even among those who saw the algorithm outperform the human.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Optis, Michael; Scott, George N.; Draxl, Caroline

    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.more » 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.« less

  14. Verification of space weather forecasts at the UK Met Office

    NASA Astrophysics Data System (ADS)

    Bingham, S.; Sharpe, M.; Jackson, D.; Murray, S.

    2017-12-01

    The UK Met Office Space Weather Operations Centre (MOSWOC) has produced space weather guidance twice a day since its official opening in 2014. Guidance includes 4-day probabilistic forecasts of X-ray flares, geomagnetic storms, high-energy electron events and high-energy proton events. Evaluation of such forecasts is important to forecasters, stakeholders, model developers and users to understand the performance of these forecasts and also strengths and weaknesses to enable further development. Met Office terrestrial near real-time verification systems have been adapted to provide verification of X-ray flare and geomagnetic storm forecasts. Verification is updated daily to produce Relative Operating Characteristic (ROC) curves and Reliability diagrams, and rolling Ranked Probability Skill Scores (RPSSs) thus providing understanding of forecast performance and skill. Results suggest that the MOSWOC issued X-ray flare forecasts are usually not statistically significantly better than a benchmark climatological forecast (where the climatology is based on observations from the previous few months). By contrast, the issued geomagnetic storm activity forecast typically performs better against this climatological benchmark.

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

    PubMed

    Gajowniczek, Krzysztof; Ząbkowski, Tomasz

    2017-01-01

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

  16. Traffic signal synchronization.

    PubMed

    Huang, Ding-wei; Huang, Wei-neng

    2003-05-01

    The benefits of traffic signal synchronization are examined within the cellular automata approach. The microsimulations of traffic flow are obtained with different settings of signal period T and time delay delta. Both numerical results and analytical approximations are presented. For undersaturated traffic, the green-light wave solutions can be realized. For saturated traffic, the correlation among the traffic signals has no effect on the throughput. For oversaturated traffic, the benefits of synchronization are manifest only when stochastic noise is suppressed.

  17. Traffic management simulation development : summary.

    DOT National Transportation Integrated Search

    2011-01-01

    Increasingly, Florida traffic is monitored electronically by components of the Intelligent Traffic System (ITS), which send data to regional traffic management centers and assist management of traffic flows and incident response using software called...

  18. HESS Opinions "On forecast (in)consistency in a hydro-meteorological chain: curse or blessing?"

    NASA Astrophysics Data System (ADS)

    Pappenberger, F.; Cloke, H. L.; Persson, A.; Demeritt, D.

    2011-01-01

    Flood forecasting increasingly relies on Numerical Weather Prediction (NWP) forecasts to achieve longer lead times (see Cloke et al., 2009; Cloke and Pappenberger, 2009). One of the key difficulties that is emerging in constructing a decision framework for these flood forecasts is when consecutive forecasts are different, leading to different conclusions regarding the issuing of forecasts, and hence inconsistent. In this opinion paper we explore some of the issues surrounding such forecast inconsistency (also known as "jumpiness", "turning points", "continuity" or number of "swings"; Zoster et al., 2009; Mills and Pepper, 1999; Lashley et al., 2008). We begin by defining what forecast inconsistency is; why forecasts might be inconsistent; how we should analyse it; what we should do about it; how we should communicate it and whether it is a totally undesirable property. The property of consistency is increasingly emerging as a hot topic in many forecasting environments (for a limited discussion on NWP inconsistency see Persson, 2011). However, in this opinion paper we restrict the discussion to a hydro-meteorological forecasting chain in which river discharge forecasts are produced using inputs from NWP. In this area of research (in)consistency is receiving recent interest and application (see e.g., Bartholmes et al., 2008; Pappenberger et al., 2011).

  19. Wind power forecasting: IEA Wind Task 36 & future research issues

    NASA Astrophysics Data System (ADS)

    Giebel, G.; Cline, J.; Frank, H.; Shaw, W.; Pinson, P.; Hodge, B.-M.; Kariniotakis, G.; Madsen, J.; Möhrlen, C.

    2016-09-01

    This paper presents the new International Energy Agency Wind Task 36 on Forecasting, and invites to collaborate within the group. Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, MetOffice, met.no, DMI,...), operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. As first results, an overview of current issues for research in short-term forecasting of wind power is presented.

  20. On the reliability of seasonal climate forecasts

    PubMed Central

    Weisheimer, A.; Palmer, T. N.

    2014-01-01

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

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