WorldWideScience

Sample records for networks precipitation model

  1. Application of deep learning in determining IR precipitation occurrence: a Convolutional Neural Network model

    Science.gov (United States)

    Wang, C.; Hong, Y.

    2017-12-01

    Infrared (IR) information from Geostationary satellites can be used to retrieve precipitation at pretty high spatiotemporal resolutions. Traditional artificial intelligence (AI) methodologies, such as artificial neural networks (ANN), have been designed to build the relationship between near-surface precipitation and manually derived IR features in products including PERSIANN and PERSIANN-CCS. This study builds an automatic precipitation detection model based on IR data using Convolutional Neural Network (CNN) which is implemented by the newly developed deep learning framework, Caffe. The model judges whether there is rain or no rain at pixel level. Compared with traditional ANN methods, CNN can extract features inside the raw data automatically and thoroughly. In this study, IR data from GOES satellites and precipitation estimates from the next generation QPE (Q2) over the central United States are used as inputs and labels, respectively. The whole datasets during the study period (June to August in 2012) are randomly partitioned to three sub datasets (train, validation and test) to establish the model at the spatial resolution of 0.08°×0.08° and the temporal resolution of 1 hour. The experiments show great improvements of CNN in rain identification compared to the widely used IR-based precipitation product, i.e., PERSIANN-CCS. The overall gain in performance is about 30% for critical success index (CSI), 32% for probability of detection (POD) and 12% for false alarm ratio (FAR). Compared to other recent IR-based precipitation retrieval methods (e.g., PERSIANN-DL developed by University of California Irvine), our model is simpler with less parameters, but achieves equally or even better results. CNN has been applied in computer vision domain successfully, and our results prove the method is suitable for IR precipitation detection. Future studies can expand the application of CNN from precipitation occurrence decision to precipitation amount retrieval.

  2. Bayesian networks precipitation model based on hidden Markov analysis and its application

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Surface precipitation estimation is very important in hydrologic forecast. To account for the influence of the neighbors on the precipitation of an arbitrary grid in the network, Bayesian networks and Markov random field were adopted to estimate surface precipitation. Spherical coordinates and the expectation-maximization (EM) algorithm were used for region interpolation, and for estimation of the precipitation of arbitrary point in the region. Surface precipitation estimation of seven precipitation stations in Qinghai Lake region was performed. By comparing with other surface precipitation methods such as Thiessen polygon method, distance weighted mean method and arithmetic mean method, it is shown that the proposed method can judge the relationship of precipitation among different points in the area under complicated circumstances and the simulation results are more accurate and rational.

  3. Precipitation Nowcast using Deep Recurrent Neural Network

    Science.gov (United States)

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

    2016-12-01

    An accurate precipitation nowcast (0-6 hours) with a fine temporal and spatial resolution has always been an important prerequisite for flood warning, streamflow prediction and risk management. Most of the popular approaches used for forecasting precipitation can be categorized into two groups. One type of precipitation forecast relies on numerical modeling of the physical dynamics of atmosphere and another is based on empirical and statistical regression models derived by local hydrologists or meteorologists. Given the recent advances in artificial intelligence, in this study a powerful Deep Recurrent Neural Network, termed as Long Short-Term Memory (LSTM) model, is creatively used to extract the patterns and forecast the spatial and temporal variability of Cloud Top Brightness Temperature (CTBT) observed from GOES satellite. Then, a 0-6 hours precipitation nowcast is produced using a Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN) algorithm, in which the CTBT nowcast is used as the PERSIANN algorithm's raw inputs. Two case studies over the continental U.S. have been conducted that demonstrate the improvement of proposed approach as compared to a classical Feed Forward Neural Network and a couple simple regression models. The advantages and disadvantages of the proposed method are summarized with regard to its capability of pattern recognition through time, handling of vanishing gradient during model learning, and working with sparse data. The studies show that the LSTM model performs better than other methods, and it is able to learn the temporal evolution of the precipitation events through over 1000 time lags. The uniqueness of PERSIANN's algorithm enables an alternative precipitation nowcast approach as demonstrated in this study, in which the CTBT prediction is produced and used as the inputs for generating precipitation nowcast.

  4. Pore-network model of evaporation-induced salt precipitation in porous media: The effect of correlations and heterogeneity

    Science.gov (United States)

    Dashtian, Hassan; Shokri, Nima; Sahimi, Muhammad

    2018-02-01

    Salt transport and precipitation in porous media constitute a set of complex and fascinating phenomena that are of considerable interest to several important problems, ranging from storage of CO2 in geological formations, to soil fertility, and protection of pavements and roads, as well as historical monuments. The phenomena occur at the pore scale and are greatly influenced by the heterogeneity of the pore space morphology. We present a pore-network (PN) model to study the phenomena. Vapor diffusion, capillary effect at the brine-vapor interface, flow of brine, and transport of salt and its precipitation in the pores that plug the pores partially or completely are all accounted for. The drying process is modeled by the invasion percolation, while transport of salt in brine is accounted for by the convective-diffusion equation. We demonstrate that the drying patterns, the clustering and connectivity of the pore throats in which salt precipitation occurs, the saturation distribution, and the drying rate are all strongly dependent upon the pore-size distribution, the correlations among the pore sizes, and the anisotropy of the pore space caused by stratification that most natural porous media contain. In particular, if the strata are more or less parallel to the direction of injection of the gas that dries out the pore space (air, for example) and/or causes salt precipitation (CO2, for example), the drying rate increases significantly. Moreover, salt tends to precipitate in clusters of neighboring pores that are parallel to the open surface of the porous medium.

  5. Forecasting Monsoon Precipitation Using Artificial Neural Networks

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper explores the application of Artificial Intelligent (AI) techniques for climate forecast. It pres ents a study on modelling the monsoon precipitation forecast by means of Artificial Neural Networks (ANNs). Using the historical data of the total amount of summer rainfall over the Delta Area of Yangtze River in China, three ANNs models have been developed to forecast the monsoon precipitation in the corre sponding area one year, five-year, and ten-year forward respectively. Performances of the models have been validated using a 'new' data set that has not been exposed to the models during the processes of model development and test. The experiment results are promising, indicating that the proposed ANNs models have good quality in terms of the accuracy, stability and generalisation ability.

  6. Using Artificial Intelligence to Retrieve the Optimal Parameters and Structures of Adaptive Network-Based Fuzzy Inference System for Typhoon Precipitation Forecast Modeling

    Directory of Open Access Journals (Sweden)

    Chien-Lin Huang

    2015-01-01

    Full Text Available This study aims to construct a typhoon precipitation forecast model providing forecasts one to six hours in advance using optimal model parameters and structures retrieved from a combination of the adaptive network-based fuzzy inference system (ANFIS and artificial intelligence. To enhance the accuracy of the precipitation forecast, two structures were then used to establish the precipitation forecast model for a specific lead-time: a single-model structure and a dual-model hybrid structure where the forecast models of higher and lower precipitation were integrated. In order to rapidly, automatically, and accurately retrieve the optimal parameters and structures of the ANFIS-based precipitation forecast model, a tabu search was applied to identify the adjacent radius in subtractive clustering when constructing the ANFIS structure. The coupled structure was also employed to establish a precipitation forecast model across short and long lead-times in order to improve the accuracy of long-term precipitation forecasts. The study area is the Shimen Reservoir, and the analyzed period is from 2001 to 2009. Results showed that the optimal initial ANFIS parameters selected by the tabu search, combined with the dual-model hybrid method and the coupled structure, provided the favors in computation efficiency and high-reliability predictions in typhoon precipitation forecasts regarding short to long lead-time forecasting horizons.

  7. Modelled Precipitation Over Greenland

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the annual total precipitation from 1985 to 1999 and monthly total precipitation from January 1985 to December 1999. The data is derived from...

  8. Optimum Neural Network Architecture for Precipitation Prediction of Myanmar

    OpenAIRE

    Khaing Win Mar; Thinn Thu Naing

    2008-01-01

    Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a s...

  9. Variability of multifractal parameters in an urban precipitation monitoring network

    Science.gov (United States)

    Licznar, Paweł; De Michele, Carlo; Dżugaj, Dagmara; Niesobska, Maria

    2014-05-01

    Precipitation especially over urban areas is considered a highly non-linear process, with wide variability over a broad range of temporal and spatial scales. Despite obvious limitations of rainfall gauges location at urban sites, rainfall monitoring by gauge networks is a standard solution of urban hydrology. Often urban precipitation gauge networks are formed by modern electronic gauges and connected to control units of centralized urban drainage systems. Precipitation data, recorded online through these gauge networks, are used in so called Real-Time-Control (RTC) systems for the development of optimal strategies of urban drainage outflows management. As a matter of fact, the operation of RTC systems is motivated mainly by the urge of reducing the severity of urban floods and combined sewerage overflows, but at the same time, it creates new valuable precipitation data sources. The variability of precipitation process could be achieved by investigating multifractal behavior displayed by the temporal structure of precipitation data. There are multiply scientific communications concerning multifractal properties of point-rainfall data from different worldwide locations. However, very little is known about the close variability of multifractal parameters among closely located gauges, at the distances of single kilometers. Having this in mind, here we assess the variability of multifractal parameters among gauges of the urban precipitation monitoring network in Warsaw, Poland. We base our analysis on the set of 1-minute rainfall time series recorded in the period 2008-2011 by 25 electronic weighing type gauges deployed around the city by the Municipal Water Supply and Sewerage Company in Warsaw as a part of local RTC system. The presence of scale invariance and multifractal properties in the precipitation process was investigated with spectral analysis, functional box counting method and studying the probability distributions and statistical moments of the rainfall

  10. Multi-scale Quantitative Precipitation Forecasting Using Nonlinear and Nonstationary Teleconnection Signals and Artificial Neural Network Models

    Science.gov (United States)

    Global sea surface temperature (SST) anomalies can affect terrestrial precipitation via ocean-atmosphere interaction known as climate teleconnection. Non-stationary and non-linear characteristics of the ocean-atmosphere system make the identification of the teleconnection signals...

  11. The Global Climatology Network Precipitation data

    International Nuclear Information System (INIS)

    Peterson, T.C.; Easterling, D.R.; Eischeid, J.K.

    1993-01-01

    Several years ago, in response to growing concern about global climate change, the US National Climatic Data Center and the Carbon Dioxide Information Analysis Center undertook an effort to create a baseline global land surface climate data set called the Global Historical Climatology Network (GHCN, Vose et al., 1992). GHCN was created by merging several large existing climate data sets into one data base. Fifteen separate data sets went into the creation of the GHCN version 1.0. GHCN version 1.0 was released in 1992. It has 7,533 precipitation stations, but the number of stations varies with time. A slight majority (55%) have records in excess of 50 years, and a significant proportion (13%) have records in excess of 100 years. The longest period of record for any given station is 291 years (1697--1987 for Kew, United Kingdom)

  12. Neural network based daily precipitation generator (NNGEN-P)

    Energy Technology Data Exchange (ETDEWEB)

    Boulanger, Jean-Philippe [LODYC, UMR CNRS/IRD/UPMC, Paris (France); University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Martinez, Fernando; Segura, Enrique C. [University of Buenos Aires, Departamento de Computacion, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Penalba, Olga [University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina)

    2007-02-15

    Daily weather generators are used in many applications and risk analyses. The present paper explores the potential of neural network architectures to design daily weather generator models. Focusing this first paper on precipitation, we design a collection of neural networks (multi-layer perceptrons in the present case), which are trained so as to approximate the empirical cumulative distribution (CDF) function for the occurrence of wet and dry spells and for the precipitation amounts. This approach contributes to correct some of the biases of the usual two-step weather generator models. As compared to a rainfall occurrence Markov model, NNGEN-P represents fairly well the mean and standard deviation of the number of wet days per month, and it significantly improves the simulation of the longest dry and wet periods. Then, we compared NNGEN-P to three parametric distribution functions usually applied to fit rainfall cumulative distribution functions (Gamma, Weibull and double-exponential). A data set of 19 Argentine stations was used. Also, data corresponding to stations in the United States, in Europe and in the Tropics were included to confirm the results. One of the advantages of NNGEN-P is that it is non-parametric. Unlike other parametric function, which adapt to certain types of climate regimes, NNGEN-P is fully adaptive to the observed cumulative distribution functions, which, on some occasions, may present complex shapes. On-going works will soon produce an extended version of NNGEN to temperature and radiation. (orig.)

  13. Prediction of ferric iron precipitation in bioleaching process using partial least squares and artificial neural network

    Directory of Open Access Journals (Sweden)

    Golmohammadi Hassan

    2013-01-01

    Full Text Available A quantitative structure-property relationship (QSPR study based on partial least squares (PLS and artificial neural network (ANN was developed for the prediction of ferric iron precipitation in bioleaching process. The leaching temperature, initial pH, oxidation/reduction potential (ORP, ferrous concentration and particle size of ore were used as inputs to the network. The output of the model was ferric iron precipitation. The optimal condition of the neural network was obtained by adjusting various parameters by trial-and-error. After optimization and training of the network according to back-propagation algorithm, a 5-5-1 neural network was generated for prediction of ferric iron precipitation. The root mean square error for the neural network calculated ferric iron precipitation for training, prediction and validation set are 32.860, 40.739 and 35.890, respectively, which are smaller than those obtained by PLS model (180.972, 165.047 and 149.950, respectively. Results obtained reveal the reliability and good predictivity of neural network model for the prediction of ferric iron precipitation in bioleaching process.

  14. Investigation of wax precipitation in crude oil: Experimental and modeling

    Directory of Open Access Journals (Sweden)

    Taraneh Jafari Behbahani

    2015-09-01

    Full Text Available In this work, a series of experiments were carried to investigation of rheological behavior of crude oil using waxy crude oil sample in the absence/presence of flow improver such as ethylene-vinyl acetate copolymer. The rheological data covered the temperature range of 5–30 °C. The results indicated that the performance of flow improver was dependent on its molecular weight. Addition of small quantities of flow improver, can improve viscosity and pour point of crude oil. Also, an Artificial Neural Network (ANN model using Multi-Layer Perceptron (MLP topology has been developed to account wax appearance temperature and the amount of precipitated wax and the model was verified using experimental data given in this work and reported in the literature. In order to compare the performance of the proposed model based on Artificial Neural Network, the wax precipitation experimental data at different temperatures were predicted using solid solution model and multi-solid phase model. The results showed that the developed model based on Artificial Neural Network can predict more accurately the wax precipitation experimental data in comparison to the previous models such as solid solution and multi-solid phase model with AADs less than 0.5%. Furthermore, the number of parameters required for the Artificial Neural Network (ANN model is less than the studied thermodynamic models.

  15. Modeling winter precipitation over the Juneau Icefield, Alaska, using a linear model of orographic precipitation

    Science.gov (United States)

    Roth, Aurora; Hock, Regine; Schuler, Thomas V.; Bieniek, Peter A.; Pelto, Mauri; Aschwanden, Andy

    2018-03-01

    Assessing and modeling precipitation in mountainous areas remains a major challenge in glacier mass balance modeling. Observations are typically scarce and reanalysis data and similar climate products are too coarse to accurately capture orographic effects. Here we use the linear theory of orographic precipitation model (LT model) to downscale winter precipitation from a regional climate model over the Juneau Icefield, one of the largest ice masses in North America (>4000 km2), for the period 1979-2013. The LT model is physically-based yet computationally efficient, combining airflow dynamics and simple cloud microphysics. The resulting 1 km resolution precipitation fields show substantially reduced precipitation on the northeastern portion of the icefield compared to the southwestern side, a pattern that is not well captured in the coarse resolution (20 km) WRF data. Net snow accumulation derived from the LT model precipitation agrees well with point observations across the icefield. To investigate the robustness of the LT model results, we perform a series of sensitivity experiments varying hydrometeor fall speeds, the horizontal resolution of the underlying grid, and the source of the meteorological forcing data. The resulting normalized spatial precipitation pattern is similar for all sensitivity experiments, but local precipitation amounts vary strongly, with greatest sensitivity to variations in snow fall speed. Results indicate that the LT model has great potential to provide improved spatial patterns of winter precipitation for glacier mass balance modeling purposes in complex terrain, but ground observations are necessary to constrain model parameters to match total amounts.

  16. A Survey of Precipitation Data for Environmental Modeling

    Science.gov (United States)

    This report explores the types of precipitation data available for environmental modeling. Precipitation is the main driver in the hydrological cycle and modelers use this information to understand water quality and water availability. Models use observed precipitation informatio...

  17. Daily precipitation statistics in regional climate models

    DEFF Research Database (Denmark)

    Frei, Christoph; Christensen, Jens Hesselbjerg; Déqué, Michel

    2003-01-01

    An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km...

  18. Precipitates/Salts Model Sensitivity Calculation

    International Nuclear Information System (INIS)

    Mariner, P.

    2001-01-01

    The objective and scope of this calculation is to assist Performance Assessment Operations and the Engineered Barrier System (EBS) Department in modeling the geochemical effects of evaporation on potential seepage waters within a potential repository drift. This work is developed and documented using procedure AP-3.12Q, ''Calculations'', in support of ''Technical Work Plan For Engineered Barrier System Department Modeling and Testing FY 02 Work Activities'' (BSC 2001a). The specific objective of this calculation is to examine the sensitivity and uncertainties of the Precipitates/Salts model. The Precipitates/Salts model is documented in an Analysis/Model Report (AMR), ''In-Drift Precipitates/Salts Analysis'' (BSC 2001b). The calculation in the current document examines the effects of starting water composition, mineral suppressions, and the fugacity of carbon dioxide (CO 2 ) on the chemical evolution of water in the drift

  19. The Use of Convolutional Neural Network in Relating Precipitation to Circulation

    Science.gov (United States)

    Pan, B.; Hsu, K. L.; AghaKouchak, A.; Sorooshian, S.

    2017-12-01

    Precipitation prediction in dynamical weather and climate models depends on 1) the predictability of pressure or geopotential height for the forecasting period and 2) the successive work of interpreting the pressure field in terms of precipitation events. The later task is represented as parameterization schemes in numerical models, where detailed computing inevitably blurs the hidden cause-and-effect relationship in precipitation generation. The "big data" provided by numerical simulation, reanalysis and observation networks requires better causation analysis for people to digest and realize their use. While classic synoptical analysis methods are very-often insufficient for spatially distributed high dimensional data, a Convolutional Neural Network(CNN) is developed here to directly relate precipitation with circulation. Case study carried over west coast United States during boreal winter showed that CNN can locate and capture key pressure zones of different structures to project precipitation spatial distribution with high accuracy across hourly to monthly scales. This direct connection between atmospheric circulation and precipitation offers a probe for attributing precipitation to the coverage, location, intensity and spatial structure of characteristic pressure zones, which can be used for model diagnosis and improvement.

  20. A stochastic space-time model for intermittent precipitation occurrences

    KAUST Repository

    Sun, Ying; Stein, Michael L.

    2016-01-01

    Modeling a precipitation field is challenging due to its intermittent and highly scale-dependent nature. Motivated by the features of high-frequency precipitation data from a network of rain gauges, we propose a threshold space-time t random field (tRF) model for 15-minute precipitation occurrences. This model is constructed through a space-time Gaussian random field (GRF) with random scaling varying along time or space and time. It can be viewed as a generalization of the purely spatial tRF, and has a hierarchical representation that allows for Bayesian interpretation. Developing appropriate tools for evaluating precipitation models is a crucial part of the model-building process, and we focus on evaluating whether models can produce the observed conditional dry and rain probabilities given that some set of neighboring sites all have rain or all have no rain. These conditional probabilities show that the proposed space-time model has noticeable improvements in some characteristics of joint rainfall occurrences for the data we have considered.

  1. A stochastic space-time model for intermittent precipitation occurrences

    KAUST Repository

    Sun, Ying

    2016-01-28

    Modeling a precipitation field is challenging due to its intermittent and highly scale-dependent nature. Motivated by the features of high-frequency precipitation data from a network of rain gauges, we propose a threshold space-time t random field (tRF) model for 15-minute precipitation occurrences. This model is constructed through a space-time Gaussian random field (GRF) with random scaling varying along time or space and time. It can be viewed as a generalization of the purely spatial tRF, and has a hierarchical representation that allows for Bayesian interpretation. Developing appropriate tools for evaluating precipitation models is a crucial part of the model-building process, and we focus on evaluating whether models can produce the observed conditional dry and rain probabilities given that some set of neighboring sites all have rain or all have no rain. These conditional probabilities show that the proposed space-time model has noticeable improvements in some characteristics of joint rainfall occurrences for the data we have considered.

  2. Dilution physics modeling: Dissolution/precipitation chemistry

    International Nuclear Information System (INIS)

    Onishi, Y.; Reid, H.C.; Trent, D.S.

    1995-09-01

    This report documents progress made to date on integrating dilution/precipitation chemistry and new physical models into the TEMPEST thermal-hydraulics computer code. Implementation of dissolution/precipitation chemistry models is necessary for predicting nonhomogeneous, time-dependent, physical/chemical behavior of tank wastes with and without a variety of possible engineered remediation and mitigation activities. Such behavior includes chemical reactions, gas retention, solids resuspension, solids dissolution and generation, solids settling/rising, and convective motion of physical and chemical species. Thus this model development is important from the standpoint of predicting the consequences of various engineered activities, such as mitigation by dilution, retrieval, or pretreatment, that can affect safe operations. The integration of a dissolution/precipitation chemistry module allows the various phase species concentrations to enter into the physical calculations that affect the TEMPEST hydrodynamic flow calculations. The yield strength model of non-Newtonian sludge correlates yield to a power function of solids concentration. Likewise, shear stress is concentration-dependent, and the dissolution/precipitation chemistry calculations develop the species concentration evolution that produces fluid flow resistance changes. Dilution of waste with pure water, molar concentrations of sodium hydroxide, and other chemical streams can be analyzed for the reactive species changes and hydrodynamic flow characteristics

  3. Reconstructing missing daily precipitation data using regression trees and artificial neural networks

    Science.gov (United States)

    Incomplete meteorological data has been a problem in environmental modeling studies. The objective of this work was to develop a technique to reconstruct missing daily precipitation data in the central part of Chesapeake Bay Watershed using regression trees (RT) and artificial neural networks (ANN)....

  4. Statistical downscaling of precipitation using long short-term memory recurrent neural networks

    Science.gov (United States)

    Misra, Saptarshi; Sarkar, Sudeshna; Mitra, Pabitra

    2017-11-01

    Hydrological impacts of global climate change on regional scale are generally assessed by downscaling large-scale climatic variables, simulated by General Circulation Models (GCMs), to regional, small-scale hydrometeorological variables like precipitation, temperature, etc. In this study, we propose a new statistical downscaling model based on Recurrent Neural Network with Long Short-Term Memory which captures the spatio-temporal dependencies in local rainfall. The previous studies have used several other methods such as linear regression, quantile regression, kernel regression, beta regression, and artificial neural networks. Deep neural networks and recurrent neural networks have been shown to be highly promising in modeling complex and highly non-linear relationships between input and output variables in different domains and hence we investigated their performance in the task of statistical downscaling. We have tested this model on two datasets—one on precipitation in Mahanadi basin in India and the second on precipitation in Campbell River basin in Canada. Our autoencoder coupled long short-term memory recurrent neural network model performs the best compared to other existing methods on both the datasets with respect to temporal cross-correlation, mean squared error, and capturing the extremes.

  5. Precipitates/Salts Model Sensitivity Calculation

    Energy Technology Data Exchange (ETDEWEB)

    P. Mariner

    2001-12-20

    The objective and scope of this calculation is to assist Performance Assessment Operations and the Engineered Barrier System (EBS) Department in modeling the geochemical effects of evaporation on potential seepage waters within a potential repository drift. This work is developed and documented using procedure AP-3.12Q, ''Calculations'', in support of ''Technical Work Plan For Engineered Barrier System Department Modeling and Testing FY 02 Work Activities'' (BSC 2001a). The specific objective of this calculation is to examine the sensitivity and uncertainties of the Precipitates/Salts model. The Precipitates/Salts model is documented in an Analysis/Model Report (AMR), ''In-Drift Precipitates/Salts Analysis'' (BSC 2001b). The calculation in the current document examines the effects of starting water composition, mineral suppressions, and the fugacity of carbon dioxide (CO{sub 2}) on the chemical evolution of water in the drift.

  6. Modeling of asphaltene and wax precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Chung, F.; Sarathi, P.; Jones, R.

    1991-01-01

    This research project was designed to focus on the development of a predictive technique for organic deposition during gas injection for petroleum EOR. A thermodynamic model has been developed to describe the effects of temperature, pressure, and composition on asphaltene precipitation. The proposed model combines regular solution theory with Flory-Huggins polymer solutions theory to predict maximum volume fractions of asphaltene dissolved in oil. The model requires evaluation of vapor-liquid equilibria, first using an equation of state followed by calculations of asphaltene solubility in the liquid-phase. A state-of-the-art technique for C{sub 7+} fraction characterization was employed in developing this model. The preliminary model developed in this work was able to predict qualitatively the trends of the effects of temperature, pressure, and composition. Since the mechanism of paraffinic wax deposition is different from that of asphaltene deposition, another thermodynamic model based on the solid-liquid solution theory was developed to predict the wax formation. This model is simple and can predict the wax appearance temperature with reasonable accuracy. Accompanying the modeling work, experimental studies were conducted to investigate the solubility of asphaltene in oil land solvents and to examine the effects of oil composition, CO{sub 2}, and solvent on asphaltene precipitation and its properties. This research focused on the solubility reversibility of asphaltene in oil and the precipitation caused by CO{sub 2} injection at simulated reservoir temperature and pressure conditions. These experiments have provided many observations about the properties of asphaltenes for further improvement of the model, but more detailed information about the properties of asphaltenes in solution is needed for the development of more reliable asphaltene characterization techniques. 50 refs., 8 figs., 7 tabs.

  7. Analysis of precipitation teleconnections in CMIP models as a measure of model fidelity in simulating precipitation

    Science.gov (United States)

    Langenbrunner, B.; Neelin, J.; Meyerson, J.

    2011-12-01

    The accurate representation of precipitation is a recurring issue in global climate models, especially in the tropics. Poor skill in modeling the variability and climate teleconnections associated with El Niño/Southern Oscillation (ENSO) also persisted in the latest Climate Model Intercomparison Project (CMIP) campaigns. Observed ENSO precipitation teleconnections provide a standard by which we can judge a given model's ability to reproduce precipitation and dynamic feedback processes originating in the tropical Pacific. Using CMIP3 Atmospheric Model Intercomparison Project (AMIP) runs as a baseline, we compare precipitation teleconnections between models and observations, and we evaluate these results against available CMIP5 historical and AMIP runs. Using AMIP simulations restricts evaluation to the atmospheric response, as sea surface temperatures (SSTs) in AMIP are prescribed by observations. We use a rank correlation between ENSO SST indices and precipitation to define teleconnections, since this method is robust to outliers and appropriate for non-Gaussian data. Spatial correlations of the modeled and observed teleconnections are then evaluated. We look at these correlations in regions of strong precipitation teleconnections, including equatorial S. America, the "horseshoe" region in the western tropical Pacific, and southern N. America. For each region and season, we create a "normalized projection" of a given model's teleconnection pattern onto that of the observations, a metric that assesses the quality of regional pattern simulations while rewarding signals of correct sign over the region. Comparing this to an area-averaged (i.e., more generous) metric suggests models do better when restrictions on exact spatial dependence are loosened and conservation constraints apply. Model fidelity in regional measures remains far from perfect, suggesting intrinsic issues with the models' regional sensitivities in moist processes.

  8. DeepRain: ConvLSTM Network for Precipitation Prediction using Multichannel Radar Data

    OpenAIRE

    Kim, Seongchan; Hong, Seungkyun; Joh, Minsu; Song, Sa-kwang

    2017-01-01

    Accurate rainfall forecasting is critical because it has a great impact on people's social and economic activities. Recent trends on various literatures show that Deep Learning (Neural Network) is a promising methodology to tackle many challenging tasks. In this study, we introduce a brand-new data-driven precipitation prediction model called DeepRain. This model predicts the amount of rainfall from weather radar data, which is three-dimensional and four-channel data, using convolutional LSTM...

  9. Collaborative networks: Reference modeling

    NARCIS (Netherlands)

    Camarinha-Matos, L.M.; Afsarmanesh, H.

    2008-01-01

    Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of

  10. Reproducibility of summertime diurnal precipitation over northern Eurasia simulated by CMIP5 climate models

    Science.gov (United States)

    Hirota, N.; Takayabu, Y. N.

    2015-12-01

    Reproducibility of diurnal precipitation over northern Eurasia simulated by CMIP5 climate models in their historical runs were evaluated, in comparison with station data (NCDC-9813) and satellite data (GSMaP-V5). We first calculated diurnal cycles by averaging precipitation at each local solar time (LST) in June-July-August during 1981-2000 over the continent of northern Eurasia (0-180E, 45-90N). Then we examined occurrence time of maximum precipitation and a contribution of diurnally varying precipitation to the total precipitation.The contribution of diurnal precipitation was about 21% in both NCDC-9813 and GSMaP-V5. The maximum precipitation occurred at 18LST in NCDC-9813 but 16LST in GSMaP-V5, indicating some uncertainties even in the observational datasets. The diurnal contribution of the CMIP5 models varied largely from 11% to 62%, and their timing of the precipitation maximum ranged from 11LST to 20LST. Interestingly, the contribution and the timing had strong negative correlation of -0.65. The models with larger diurnal precipitation showed precipitation maximum earlier around noon. Next, we compared sensitivity of precipitation to surface temperature and tropospheric humidity between 5 models with large diurnal precipitation (LDMs) and 5 models with small diurnal precipitation (SDMs). Precipitation in LDMs showed high sensitivity to surface temperature, indicating its close relationship with local instability. On the other hand, synoptic disturbances were more active in SDMs with a dominant role of the large scale condensation, and precipitation in SDMs was more related with tropospheric moisture. Therefore, the relative importance of the local instability and the synoptic disturbances was suggested to be an important factor in determining the contribution and timing of the diurnal precipitation. Acknowledgment: This study is supported by Green Network of Excellence (GRENE) Program by the Ministry of Education, Culture, Sports, Science and Technology

  11. Downsizing a long-term precipitation network: Using a quantitative approach to inform difficult decisions

    Science.gov (United States)

    Mark B. Green; John L. Campbell; Ruth D. Yanai; Scott W. Bailey; Amey S. Bailey; Nicholas Grant; Ian Halm; Eric P. Kelsey; Lindsey E. Rustad

    2018-01-01

    The design of a precipitation monitoring network must balance the demand for accurate estimates with the resources needed to build and maintain the network. If there are changes in the objectives of the monitoring or the availability of resources, network designs should be adjusted. At the Hubbard Brook Experimental Forest in New Hampshire, USA, precipitation has been...

  12. Self-organizing map network-based precipitation regionalization for the Tibetan Plateau and regional precipitation variability

    Science.gov (United States)

    Wang, Nini; Yin, Jianchuan

    2017-12-01

    A precipitation-based regionalization for the Tibetan Plateau (TP) was investigated for regional precipitation trend analysis and frequency analysis using data from 1113 grid points covering the period 1900-2014. The results utilizing self-organizing map (SOM) network suggest that four clusters of precipitation coherent zones can be identified, including the southwestern edge, the southern edge, the southeastern region, and the north central region. Regionalization results of the SOM network satisfactorily represent the influences of the atmospheric circulation systems such as the East Asian summer monsoon, the south Asian summer monsoon, and the mid-latitude westerlies. Regionalization results also well display the direct impacts of physical geographical features of the TP such as orography, topography, and land-sea distribution. Regional-scale annual precipitation trend as well as regional differences of annual and seasonal total precipitation were investigated by precipitation index such as precipitation concentration index (PCI) and Standardized Anomaly Index (SAI). Results demonstrate significant negative long-term linear trends in southeastern TP and the north central part of the TP, indicating arid and semi-arid regions in the TP are getting drier. The empirical mode decomposition (EMD) method shows an evolution of the main cycle with 4 and 12 months for all the representative grids of four sub-regions. The cross-wavelet analysis suggests that predominant and effective period of Indian Ocean Dipole (IOD) on monthly precipitation is around ˜12 months, except for the representative grid of the northwestern region.

  13. Continuum Model for River Networks

    Science.gov (United States)

    Giacometti, Achille; Maritan, Amos; Banavar, Jayanth R.

    1995-07-01

    The effects of erosion, avalanching, and random precipitation are captured in a simple stochastic partial differential equation for modeling the evolution of river networks. Our model leads to a self-organized structured landscape and to abstraction and piracy of the smaller tributaries as the evolution proceeds. An algebraic distribution of the average basin areas and a power law relationship between the drainage basin area and the river length are found.

  14. Oxidation and Precipitation of Sulfide in Sewer Networks

    DEFF Research Database (Denmark)

    Nielsen, A. H.

    risks and corrosion of concrete and metals. Most of the problems relate to the buildup of hydrogen sulfide in the atmosphere of sewer networks. In this respect, the processes of the sulfur cycle are of fundamental importance in ultimately determining the extent of such problems. This study focused...... calibrated and validated against field data. In the extension to the WATS model, sulfur transformations were described by six processes: 1. Sulfide production taking place in the biofilm and sediments covering the permanently wetted sewer walls; 2. Biological sulfide oxidation in the permanently wetted...... to the sewer atmosphere, potentially resulting in concrete corrosion. The extended WATS model represents a major improvement over previously developed models for prediction of sulfide buildup in sewer networks. Compared to such models, the major processes governing sulfide buildup in sewer networks...

  15. Modeling Precipitation Extremes using Log-Histospline

    Science.gov (United States)

    Huang, W. K.; Nychka, D. W.; Zhang, H.

    2017-12-01

    One of the commonly used approaches to modeling univariate extremes is the peaks-overthreshold (POT) method. The POT method models exceedances over a (sufficiently high/low) threshold as a generalized Pareto distribution (GPD). To apply this method, a threshold has to be chosen and the estimates might be sensitive to the chosen threshold. Here we propose an alternative, the "Log-Histospline", to explore modeling the tail behavior and the remainder of the density in one step using the full range of the data. Log-Histospline applies a smoothing spline model on a finely binned histogram of the log transformed data to estimate its log density. By construction, we are able to preserve the polynomial upper tail behavior, a feature commonly observed in geophysical observations. The Log-Histospline can be extended to the spatial setting by treating the marginal (log) density at each location as spatially indexed functional data, and perform a dimension reduction and spatial smoothing. We illustrate the proposed method by analyzing precipitation data from regional climate model output (North American Regional Climate Change and Assessment Program (NARCCAP)).

  16. In-Drift Precipitates/Salts Model

    International Nuclear Information System (INIS)

    Mariner, P.

    2003-01-01

    As directed by ''Technical Work Plan For: Engineered Barrier System Department Modeling and Testing FY03 Work Activities'' (BSC 2003 [165601]), the In-Drift Precipitates/Salts (IDPS) model is developed and refined to predict the aqueous geochemical effects of evaporation in the proposed repository. The purpose of this work is to provide a model for describing and predicting the postclosure effects of evaporation and deliquescence on the chemical composition of water within the proposed Engineered Barrier System (EBS). Application of this model is to be documented elsewhere for the Total System Performance Assessment License Application (TSPA-LA). The principal application of this model is to be documented in REV 02 of ''Engineered Barrier System: Physical and Chemical Environment Model'' (BSC 2003 [165601]). The scope of this document is to develop, describe, and validate the IDPS model. This model is a quasi-equilibrium model. All reactions proceed to equilibrium except for several suppressed minerals in the thermodynamic database not expected to form under the proposed repository conditions within the modeling timeframe. In this revision, upgrades to the EQ3/6 code (Version 8.0) and Pitzer thermodynamic database improve the applicable range of the model. These new additions allow equilibrium and reaction-path modeling of evaporation to highly concentrated brines for potential water compositions of the system Na-K-H-Mg-Ca-Al-Cl-F-NO 3 -SO 4 -Br-CO 3 -SiO 2 -CO 2 -O 2 -H 2 O at temperatures in the range of 0 C to 125 C, pressures in the atmospheric range, and relative humidity in the range of 0 to 100 percent. This system applies to oxidizing conditions only, and therefore limits the model to applications involving oxidizing conditions. A number of thermodynamic parameters in the Pitzer database have values that have not been determined or verified for the entire temperature range. In these cases, the known values are used to approximate the values for the rest of

  17. In-Drift Precipitates/Salts Model

    Energy Technology Data Exchange (ETDEWEB)

    P. Mariner

    2003-10-21

    As directed by ''Technical Work Plan For: Engineered Barrier System Department Modeling and Testing FY03 Work Activities'' (BSC 2003 [165601]), the In-Drift Precipitates/Salts (IDPS) model is developed and refined to predict the aqueous geochemical effects of evaporation in the proposed repository. The purpose of this work is to provide a model for describing and predicting the postclosure effects of evaporation and deliquescence on the chemical composition of water within the proposed Engineered Barrier System (EBS). Application of this model is to be documented elsewhere for the Total System Performance Assessment License Application (TSPA-LA). The principal application of this model is to be documented in REV 02 of ''Engineered Barrier System: Physical and Chemical Environment Model'' (BSC 2003 [165601]). The scope of this document is to develop, describe, and validate the IDPS model. This model is a quasi-equilibrium model. All reactions proceed to equilibrium except for several suppressed minerals in the thermodynamic database not expected to form under the proposed repository conditions within the modeling timeframe. In this revision, upgrades to the EQ3/6 code (Version 8.0) and Pitzer thermodynamic database improve the applicable range of the model. These new additions allow equilibrium and reaction-path modeling of evaporation to highly concentrated brines for potential water compositions of the system Na-K-H-Mg-Ca-Al-Cl-F-NO{sub 3}-SO{sub 4}-Br-CO{sub 3}-SiO{sub 2}-CO{sub 2}-O{sub 2}-H{sub 2}O at temperatures in the range of 0 C to 125 C, pressures in the atmospheric range, and relative humidity in the range of 0 to 100 percent. This system applies to oxidizing conditions only, and therefore limits the model to applications involving oxidizing conditions. A number of thermodynamic parameters in the Pitzer database have values that have not been determined or verified for the entire temperature range. In these cases

  18. Evaluation of Satellite and Model Precipitation Products Over Turkey

    Science.gov (United States)

    Yilmaz, M. T.; Amjad, M.

    2017-12-01

    Satellite-based remote sensing, gauge stations, and models are the three major platforms to acquire precipitation dataset. Among them satellites and models have the advantage of retrieving spatially and temporally continuous and consistent datasets, while the uncertainty estimates of these retrievals are often required for many hydrological studies to understand the source and the magnitude of the uncertainty in hydrological response parameters. In this study, satellite and model precipitation data products are validated over various temporal scales (daily, 3-daily, 7-daily, 10-daily and monthly) using in-situ measured precipitation observations from a network of 733 gauges from all over the Turkey. Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 and European Center of Medium-Range Weather Forecast (ECMWF) model estimates (daily, 3-daily, 7-daily and 10-daily accumulated forecast) are used in this study. Retrievals are evaluated for their mean and standard deviation and their accuracies are evaluated via bias, root mean square error, error standard deviation and correlation coefficient statistics. Intensity vs frequency analysis and some contingency table statistics like percent correct, probability of detection, false alarm ratio and critical success index are determined using daily time-series. Both ECMWF forecasts and TRMM observations, on average, overestimate the precipitation compared to gauge estimates; wet biases are 10.26 mm/month and 8.65 mm/month, respectively for ECMWF and TRMM. RMSE values of ECMWF forecasts and TRMM estimates are 39.69 mm/month and 41.55 mm/month, respectively. Monthly correlations between Gauges-ECMWF, Gauges-TRMM and ECMWF-TRMM are 0.76, 0.73 and 0.81, respectively. The model and the satellite error statistics are further compared against the gauges error statistics based on inverse distance weighting (IWD) analysis. Both the model and satellite data have less IWD errors (14

  19. Generation of a stochastic precipitation model for the tropical climate

    Science.gov (United States)

    Ng, Jing Lin; Abd Aziz, Samsuzana; Huang, Yuk Feng; Wayayok, Aimrun; Rowshon, MK

    2017-06-01

    A tropical country like Malaysia is characterized by intense localized precipitation with temperatures remaining relatively constant throughout the year. A stochastic modeling of precipitation in the flood-prone Kelantan River Basin is particularly challenging due to the high intermittency of precipitation events of the northeast monsoons. There is an urgent need to have long series of precipitation in modeling the hydrological responses. A single-site stochastic precipitation model that includes precipitation occurrence and an intensity model was developed, calibrated, and validated for the Kelantan River Basin. The simulation process was carried out separately for each station without considering the spatial correlation of precipitation. The Markov chains up to the fifth-order and six distributions were considered. The daily precipitation data of 17 rainfall stations for the study period of 1954-2013 were selected. The results suggested that second- and third-order Markov chains were suitable for simulating monthly and yearly precipitation occurrences, respectively. The fifth-order Markov chain resulted in overestimation of precipitation occurrences. For the mean, distribution, and standard deviation of precipitation amounts, the exponential, gamma, log-normal, skew normal, mixed exponential, and generalized Pareto distributions performed superiorly. However, for the extremes of precipitation, the exponential and log-normal distributions were better while the skew normal and generalized Pareto distributions tend to show underestimations. The log-normal distribution was chosen as the best distribution to simulate precipitation amounts. Overall, the stochastic precipitation model developed is considered a convenient tool to simulate the characteristics of precipitation in the Kelantan River Basin.

  20. In-Drift Precipitates/Salts Model

    International Nuclear Information System (INIS)

    P. Mariner

    2004-01-01

    This report documents the development and validation of the in-drift precipitates/salts (IDPS) model. The IDPS model is a geochemical model designed to predict the postclosure effects of evaporation and deliquescence on the chemical composition of water within the Engineered Barrier System (EBS) in support of the Total System Performance Assessment for the License Application (TSPA-LA). Application of the model in support of TSPA-LA is documented in ''Engineered Barrier System: Physical and Chemical Environment Model'' (BSC 2004 [DIRS 169860]). Technical Work Plan for: Near-Field Environment and Transport In-Drift Geochemistry Model Report Integration (BSC 2004 [DIRS 171156]) is the technical work plan (TWP) for this report. It called for a revision of the previous version of the report (BSC 2004 [DIRS 167734]) to achieve greater transparency, readability, data traceability, and report integration. The intended use of the IDPS model is to estimate and tabulate, within an appropriate level of confidence, the effects of evaporation, deliquescence, and potential environmental conditions on the pH, ionic strength, and chemical compositions of water and minerals on the drip shield or other location within the drift during the postclosure period. Specifically, the intended use is as follows: (1) To estimate, within an appropriate level of confidence, the effects of evaporation and deliquescence on the presence and composition of water occurring within the repository during the postclosure period (i.e., effects on pH, ionic strength, deliquescence relative humidity, total concentrations of dissolved components in the system Na-K-H-Mg-Ca-Al-Cl-F-NO 3 -SO 4 -Br-CO 3 -SiO 2 -CO 2 -O 2 -H 2 O, and concentrations of the following aqueous species that potentially affect acid neutralizing capacity: HCO 3 - , CO 3 2- , OH - , H + , HSO 4 - , Ca 2+ , Mg 2+ , CaHCO 3 + , MgHCO 3 + , HSiO 3 - , and MgOH + ); (2) To estimate, within an appropriate level of confidence, mineral

  1. In-Drift Precipitates/Salts Model

    Energy Technology Data Exchange (ETDEWEB)

    P. Mariner

    2004-11-09

    This report documents the development and validation of the in-drift precipitates/salts (IDPS) model. The IDPS model is a geochemical model designed to predict the postclosure effects of evaporation and deliquescence on the chemical composition of water within the Engineered Barrier System (EBS) in support of the Total System Performance Assessment for the License Application (TSPA-LA). Application of the model in support of TSPA-LA is documented in ''Engineered Barrier System: Physical and Chemical Environment Model'' (BSC 2004 [DIRS 169860]). Technical Work Plan for: Near-Field Environment and Transport In-Drift Geochemistry Model Report Integration (BSC 2004 [DIRS 171156]) is the technical work plan (TWP) for this report. It called for a revision of the previous version of the report (BSC 2004 [DIRS 167734]) to achieve greater transparency, readability, data traceability, and report integration. The intended use of the IDPS model is to estimate and tabulate, within an appropriate level of confidence, the effects of evaporation, deliquescence, and potential environmental conditions on the pH, ionic strength, and chemical compositions of water and minerals on the drip shield or other location within the drift during the postclosure period. Specifically, the intended use is as follows: (1) To estimate, within an appropriate level of confidence, the effects of evaporation and deliquescence on the presence and composition of water occurring within the repository during the postclosure period (i.e., effects on pH, ionic strength, deliquescence relative humidity, total concentrations of dissolved components in the system Na-K-H-Mg-Ca-Al-Cl-F-NO{sub 3}-SO{sub 4}-Br-CO{sub 3}-SiO{sub 2}-CO{sub 2}-O{sub 2}-H{sub 2}O, and concentrations of the following aqueous species that potentially affect acid neutralizing capacity: HCO{sub 3}{sup -}, CO{sub 3}{sup 2-}, OH{sup -}, H{sup +}, HSO{sub 4}{sup -}, Ca{sup 2+}, Mg{sup 2+}, CaHCO{sub 3}{sup +}, MgHCO{sub 3

  2. Application of physical scaling towards downscaling climate model precipitation data

    Science.gov (United States)

    Gaur, Abhishek; Simonovic, Slobodan P.

    2018-04-01

    Physical scaling (SP) method downscales climate model data to local or regional scales taking into consideration physical characteristics of the area under analysis. In this study, multiple SP method based models are tested for their effectiveness towards downscaling North American regional reanalysis (NARR) daily precipitation data. Model performance is compared with two state-of-the-art downscaling methods: statistical downscaling model (SDSM) and generalized linear modeling (GLM). The downscaled precipitation is evaluated with reference to recorded precipitation at 57 gauging stations located within the study region. The spatial and temporal robustness of the downscaling methods is evaluated using seven precipitation based indices. Results indicate that SP method-based models perform best in downscaling precipitation followed by GLM, followed by the SDSM model. Best performing models are thereafter used to downscale future precipitations made by three global circulation models (GCMs) following two emission scenarios: representative concentration pathway (RCP) 2.6 and RCP 8.5 over the twenty-first century. The downscaled future precipitation projections indicate an increase in mean and maximum precipitation intensity as well as a decrease in the total number of dry days. Further an increase in the frequency of short (1-day), moderately long (2-4 day), and long (more than 5-day) precipitation events is projected.

  3. Multiresolution comparison of precipitation datasets for large-scale models

    Science.gov (United States)

    Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

    2014-12-01

    Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

  4. Modeling Network Interdiction Tasks

    Science.gov (United States)

    2015-09-17

    118 xiii Table Page 36 Computation times for weighted, 100-node random networks for GAND Approach testing in Python ...in Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 38 Accuracy measures for weighted, 100-node random networks for GAND...networks [15:p. 1]. A common approach to modeling network interdiction is to formulate the problem in terms of a two-stage strategic game between two

  5. High resolution modelling of extreme precipitation events in urban areas

    Science.gov (United States)

    Siemerink, Martijn; Volp, Nicolette; Schuurmans, Wytze; Deckers, Dave

    2015-04-01

    The present day society needs to adjust to the effects of climate change. More extreme weather conditions are expected, which can lead to longer periods of drought, but also to more extreme precipitation events. Urban water systems are not designed for such extreme events. Most sewer systems are not able to drain the excessive storm water, causing urban flooding. This leads to high economic damage. In order to take appropriate measures against extreme urban storms, detailed knowledge about the behaviour of the urban water system above and below the streets is required. To investigate the behaviour of urban water systems during extreme precipitation events new assessment tools are necessary. These tools should provide a detailed and integral description of the flow in the full domain of overland runoff, sewer flow, surface water flow and groundwater flow. We developed a new assessment tool, called 3Di, which provides detailed insight in the urban water system. This tool is based on a new numerical methodology that can accurately deal with the interaction between overland runoff, sewer flow and surface water flow. A one-dimensional model for the sewer system and open channel flow is fully coupled to a two-dimensional depth-averaged model that simulates the overland flow. The tool uses a subgrid-based approach in order to take high resolution information of the sewer system and of the terrain into account [1, 2]. The combination of using the high resolution information and the subgrid based approach results in an accurate and efficient modelling tool. It is now possible to simulate entire urban water systems using extreme high resolution (0.5m x 0.5m) terrain data in combination with a detailed sewer and surface water network representation. The new tool has been tested in several Dutch cities, such as Rotterdam, Amsterdam and The Hague. We will present the results of an extreme precipitation event in the city of Schiedam (The Netherlands). This city deals with

  6. A Thermodynamic Mixed-Solid Asphaltene Precipitation Model

    DEFF Research Database (Denmark)

    Lindeloff, Niels; Heidemann, R.A.; Andersen, Simon Ivar

    1998-01-01

    A simple model for the prediction of asphaltene precipitation is proposed. The model is based on an equation of state and uses standard thermodynamics, thus assuming that the precipitation phenomenon is a reversible process. The solid phase is treated as an ideal multicomponent mixture. An activity...

  7. Mathematical modeling and simulation of nanopore blocking by precipitation

    KAUST Repository

    Wolfram, M-T

    2010-10-29

    High surface charges of polymer pore walls and applied electric fields can lead to the formation and subsequent dissolution of precipitates in nanopores. These precipitates block the pore, leading to current fluctuations. We present an extended Poisson-Nernst-Planck system which includes chemical reactions of precipitation and dissolution. We discuss the mathematical modeling and present 2D numerical simulations. © 2010 IOP Publishing Ltd.

  8. Method for modeling the deposition of sulfur by precipitation over regional scales

    International Nuclear Information System (INIS)

    Hicks, B.B.; Shannon, J.D.

    1979-01-01

    Radioactive fallout data suggest that the concentration of pollutants in rainfall, while highly variable, might be described on the average by about an inverse half-power dependence on the amount of precipitation. Recent measurements of sulfur concentrations in summer rainfall collected at Argonne National Laboratory tend to support this contention, as do preliminary results derived from operations of the DOE precipitation chemistry network. The concept is extended to develop a bulk removal rate for airborne total sulfur by precipitation for use in regional dispersion modeling

  9. Improving Frozen Precipitation Density Estimation in Land Surface Modeling

    Science.gov (United States)

    Sparrow, K.; Fall, G. M.

    2017-12-01

    The Office of Water Prediction (OWP) produces high-value water supply and flood risk planning information through the use of operational land surface modeling. Improvements in diagnosing frozen precipitation density will benefit the NWS's meteorological and hydrological services by refining estimates of a significant and vital input into land surface models. A current common practice for handling the density of snow accumulation in a land surface model is to use a standard 10:1 snow-to-liquid-equivalent ratio (SLR). Our research findings suggest the possibility of a more skillful approach for assessing the spatial variability of precipitation density. We developed a 30-year SLR climatology for the coterminous US from version 3.22 of the Daily Global Historical Climatology Network - Daily (GHCN-D) dataset. Our methods followed the approach described by Baxter (2005) to estimate mean climatological SLR values at GHCN-D sites in the US, Canada, and Mexico for the years 1986-2015. In addition to the Baxter criteria, the following refinements were made: tests were performed to eliminate SLR outliers and frequent reports of SLR = 10, a linear SLR vs. elevation trend was fitted to station SLR mean values to remove the elevation trend from the data, and detrended SLR residuals were interpolated using ordinary kriging with a spherical semivariogram model. The elevation values of each station were based on the GMTED 2010 digital elevation model and the elevation trend in the data was established via linear least squares approximation. The ordinary kriging procedure was used to interpolate the data into gridded climatological SLR estimates for each calendar month at a 0.125 degree resolution. To assess the skill of this climatology, we compared estimates from our SLR climatology with observations from the GHCN-D dataset to consider the potential use of this climatology as a first guess of frozen precipitation density in an operational land surface model. The difference in

  10. The Global Network of Isotopes in Precipitation after 55 years: assessing past, present and future developments

    Science.gov (United States)

    Terzer, Stefan; Araguas-Araguas, Luis; Wassenaar, Leonard I.; Aggarwal, Pradeep K.

    2015-04-01

    The Global Network of Isotopes in Precipitation (GNIP) is a global observation programme operated by the International Atomic Energy Agency (IAEA), in cooperation with the World Meteorological Organization (WMO) and more than 100 contributing institutions worldwide. GNIP has been the primary repository for baseline stable (δ18O, δ2H) and radioactive (3H) isotope data since its foundation in 1960. The impetus for GNIP was the monitoring of radioactive fallout from atmospheric thermonuclear testing and resulting tritium levels of precipitation, but tritium together with stable isotopes was recognized as a key to understanding hydrological processes. Later, new applications were developed focusing on hydrometeorology and paleoclimatic research. Increasingly, GNIP data are being used more widely in ecological and forensic investigations, e.g. for tracking of migratory animals. The GNIP database comprises more than 135,000 isotopic records (δ18O: 63,000; δ2H: 55,000; 3H: 63,000) of monthly composite precipitation samples from more than 1,000 stations worldwide. About 300 stations are currently active for stable isotopes and ca. 100 for tritium. Data for most of the active stations is available up to 2013. Several national isotopic observation networks (e.g. in Austria, Australia, China or the United States of America) exist besides GNIP, complementing precipitation isotope data at national levels. The spatially and temporally discrete nature of the GNIP dataset induces coverage gaps. Recently, highly-resolved gridded datasets were established to help overcome this deficiency through geostatistical prediction models. These 'isoscape' (isotopic landscapes) are based on combinations of multiple regression and interpolation methods, with a range of parameterization available at regional and global levels. Attempts to bridge the gap between 'one-size-fits-all' global parameterization and improved predictions at regional and local levels led to the establishment of a

  11. Dynamic process model of a plutonium oxalate precipitator

    International Nuclear Information System (INIS)

    Borgonovi, G.M.; Hammelman, J.E.; Miller, C.L.

    1980-01-01

    A dynamic model of a plutonium oxalate precipitator is developed to provide a means of predicting plutonium inventory on a continuous basis. The model is based on state-of-the-art crystallization equations, which describe nucleation and growth phenomena. The model parameters were obtained through the use of batch experimental data. The model has been used to study the approach to steady state, to investigate the response to input transients, and to simulate the control of the precipitation process. 12 refs

  12. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

    OpenAIRE

    Shi, Xingjian; Chen, Zhourong; Wang, Hao; Yeung, Dit-Yan; Wong, Wai-kin; Woo, Wang-chun

    2015-01-01

    The goal of precipitation nowcasting is to predict the future rainfall intensity in a local region over a relatively short period of time. Very few previous studies have examined this crucial and challenging weather forecasting problem from the machine learning perspective. In this paper, we formulate precipitation nowcasting as a spatiotemporal sequence forecasting problem in which both the input and the prediction target are spatiotemporal sequences. By extending the fully connected LSTM (F...

  13. Functional Connectivity of Precipitation Networks in the Brazilian Rainforest-Savanna Transition Zone

    Science.gov (United States)

    Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

    2016-12-01

    In the Brazilian rainforest-savanna transition zone, vegetation change has the potential to significantly affect precipitation patterns. Deforestation, in particular, can affect precipitation patterns by increasing land surface albedo, increasing aerosol loading to the atmosphere, changing land surface roughness, and reducing transpiration. Understanding land surface-precipitation couplings in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching and agriculture, hydropower generation, and drinking water management. Simulations suggest complex, scale-dependent interactions between precipitation and land cover. For example, the size and distribution of deforested patches has been found to affect precipitation patterns. We take an empirical approach to ask: (1) what are the dominant spatial and temporal length scales of precipitation coupling in the Brazilian rainforest-savanna transition zone? (2) How do these length scales change over time? (3) How does the connectivity of precipitation change over time? The answers to these questions will help address fundamental questions about the impacts of deforestation on precipitation. We use rain gauge data from 1100 rain gauges intermittently covering the period 1980 - 2013, a period of intensive land cover change in the region. The dominant spatial and temporal length scales of precipitation coupling are resolved using transfer entropy, a metric from information theory. Connectivity of the emergent network of couplings is quantified using network statistics. Analyses using transfer entropy and network statistics reveal the spatial and temporal interdependencies of rainfall events occurring in different parts of the study domain.

  14. Predictive modelling of Fe(III) precipitation in iron removal process for bioleaching circuits.

    Science.gov (United States)

    Nurmi, Pauliina; Ozkaya, Bestamin; Kaksonen, Anna H; Tuovinen, Olli H; Puhakka, Jaakko A

    2010-05-01

    In this study, the applicability of three modelling approaches was determined in an effort to describe complex relationships between process parameters and to predict the performance of an integrated process, which consisted of a fluidized bed bioreactor for Fe(3+) regeneration and a gravity settler for precipitative iron removal. Self-organizing maps were used to visually evaluate the associations between variables prior to the comparison of two different modelling methods, the multiple regression modelling and artificial neural network (ANN) modelling, for predicting Fe(III) precipitation. With the ANN model, an excellent match between the predicted and measured data was obtained (R (2) = 0.97). The best-fitting regression model also gave a good fit (R (2) = 0.87). This study demonstrates that ANNs and regression models are robust tools for predicting iron precipitation in the integrated process and can thus be used in the management of such systems.

  15. Modelling the operation of precipitator with vortex effect

    International Nuclear Information System (INIS)

    Eysseric-Emile, C.

    1994-01-01

    In the Purex process which is implemented for the processing of irradiated fuels to eliminate fission products and to recover and valorise uranium and plutonium under the form of end products, a precipitation operation occurs to prepare the plutonium oxalate. This research thesis aims at analysing hydrodynamic characteristics of a specific apparatus used for this precipitation, the precipitator with vortex effect. In a first part, the author presents the problems associated with precipitation operations, their implementation in the processing of irradiated fuels, and compares the considered precipitator with other devices used for the precipitation of radioactive compounds. He proposes a review of literature on the vortex effect in agitated vessel, highlights the key parameter (the forced vortex radius), and reports some preliminary measurements performed on the precipitator. The author then reports the study of liquid phase flows in the precipitator, measurements of rate of suspension, and the study of micro-mixing with reactants. He finally reports attempts to validate trends noticed during flow analysis and a first simple modelling of the precipitator [fr

  16. Modelling computer networks

    International Nuclear Information System (INIS)

    Max, G

    2011-01-01

    Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.

  17. Modeling Precipitation Dependent Forest Resilience in India

    Science.gov (United States)

    Das, P.; Behera, M. D.; Roy, P. S.

    2018-04-01

    The impact of long term climate change that imparts stress on forest could be perceived by studying the regime shift of forest ecosystem. With the change of significant precipitation, forest may go through density change around globe at different spatial and temporal scale. The 100 class high resolution (60 meter spatial resolution) Indian vegetation type map was used in this study recoded into four broad categories depending on phrenology as (i) forest, (ii) scrubland, (iii) grassland and (iv) treeless area. The percentage occupancy of forest, scrub, grass and treeless were observed as 19.9 %, 5.05 %, 1.89 % and 7.79 % respectively. Rest of the 65.37 % land area was occupied by the cropland, built-up, water body and snow covers. The majority forest cover were appended into a 5 km × 5 km grid, along with the mean annual precipitation taken from Bioclim data. The binary presence and absence of different vegetation categories in relates to the annual precipitation was analyzed to calculate their resilience expressed in probability values ranging from 0 to 1. Forest cover observed having resilience probability (Pr) < 0.3 in only 0.3 % (200 km2) of total forest cover in India, which was 4.3 % < 0.5 Pr. Majority of the scrubs and grass (64.92 % Pr < 0.5) from North East India which were the shifting cultivation lands showing low resilience, having their high tendency to be transform to forest. These results have spatial explicitness to highlight the resilient and non-resilient distribution of forest, scrub and grass, and treeless areas in India.

  18. MODELING PRECIPITATION DEPENDENT FOREST RESILIENCE IN INDIA

    Directory of Open Access Journals (Sweden)

    P. Das

    2018-04-01

    Full Text Available The impact of long term climate change that imparts stress on forest could be perceived by studying the regime shift of forest ecosystem. With the change of significant precipitation, forest may go through density change around globe at different spatial and temporal scale. The 100 class high resolution (60 meter spatial resolution Indian vegetation type map was used in this study recoded into four broad categories depending on phrenology as (i forest, (ii scrubland, (iii grassland and (iv treeless area. The percentage occupancy of forest, scrub, grass and treeless were observed as 19.9 %, 5.05 %, 1.89 % and 7.79 % respectively. Rest of the 65.37 % land area was occupied by the cropland, built-up, water body and snow covers. The majority forest cover were appended into a 5 km × 5 km grid, along with the mean annual precipitation taken from Bioclim data. The binary presence and absence of different vegetation categories in relates to the annual precipitation was analyzed to calculate their resilience expressed in probability values ranging from 0 to 1. Forest cover observed having resilience probability (Pr < 0.3 in only 0.3 % (200 km2 of total forest cover in India, which was 4.3 % < 0.5 Pr. Majority of the scrubs and grass (64.92 % Pr < 0.5 from North East India which were the shifting cultivation lands showing low resilience, having their high tendency to be transform to forest. These results have spatial explicitness to highlight the resilient and non-resilient distribution of forest, scrub and grass, and treeless areas in India.

  19. California Wintertime Precipitation in Regional and Global Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Caldwell, P M

    2009-04-27

    In this paper, wintertime precipitation from a variety of observational datasets, regional climate models (RCMs), and general circulation models (GCMs) is averaged over the state of California (CA) and compared. Several averaging methodologies are considered and all are found to give similar values when model grid spacing is less than 3{sup o}. This suggests that CA is a reasonable size for regional intercomparisons using modern GCMs. Results show that reanalysis-forced RCMs tend to significantly overpredict CA precipitation. This appears to be due mainly to overprediction of extreme events; RCM precipitation frequency is generally underpredicted. Overprediction is also reflected in wintertime precipitation variability, which tends to be too high for RCMs on both daily and interannual scales. Wintertime precipitation in most (but not all) GCMs is underestimated. This is in contrast to previous studies based on global blended gauge/satellite observations which are shown here to underestimate precipitation relative to higher-resolution gauge-only datasets. Several GCMs provide reasonable daily precipitation distributions, a trait which doesn't seem tied to model resolution. GCM daily and interannual variability is generally underpredicted.

  20. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  1. Modeling the citation network by network cosmology.

    Science.gov (United States)

    Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing

    2015-01-01

    Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.

  2. Improved daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed

    International Nuclear Information System (INIS)

    Grimm, J.W.; Lynch, J.A.

    2005-01-01

    Daily precipitation nitrate and ammonium concentration models were developed for the Chesapeake Bay Watershed (USA) using a linear least-squares regression approach and precipitation chemistry data from 29 National Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites. Only weekly samples that comprised a single precipitation event were used in model development. The most significant variables in both ammonium and nitrate models included: precipitation volume, the number of days since the last event, a measure of seasonality, latitude, and the proportion of land within 8 km covered by forest or devoted to industry and transportation. Additional variables included in the nitrate model were the proportion of land within 0.8 km covered by water and/or forest. Local and regional ammonia and nitrogen oxide emissions were not as well correlated as land cover. Modeled concentrations compared very well with event chemistry data collected at six NADP/AirMoN sites within the Chesapeake Bay Watershed. Wet deposition estimates were also consistent with observed deposition at selected sites. Accurately describing the spatial distribution of precipitation volume throughout the watershed is important in providing critical estimates of wet-fall deposition of ammonium and nitrate. - A linear least-squares regression approach was used to develop daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed

  3. Brain Network Modelling

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther

    Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

  4. Climate dynamics: a network-based approach for the analysis of global precipitation.

    Science.gov (United States)

    Scarsoglio, Stefania; Laio, Francesco; Ridolfi, Luca

    2013-01-01

    Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can

  5. Climate dynamics: a network-based approach for the analysis of global precipitation.

    Directory of Open Access Journals (Sweden)

    Stefania Scarsoglio

    Full Text Available Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010. The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that

  6. Modeling Epidemic Network Failures

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Fagertun, Anna Manolova

    2013-01-01

    This paper presents the implementation of a failure propagation model for transport networks when multiple failures occur resulting in an epidemic. We model the Susceptible Infected Disabled (SID) epidemic model and validate it by comparing it to analytical solutions. Furthermore, we evaluate...... the SID model’s behavior and impact on the network performance, as well as the severity of the infection spreading. The simulations are carried out in OPNET Modeler. The model provides an important input to epidemic connection recovery mechanisms, and can due to its flexibility and versatility be used...... to evaluate multiple epidemic scenarios in various network types....

  7. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  8. Importance of resolution and model configuration when downscaling extreme precipitation

    Directory of Open Access Journals (Sweden)

    Adrian J. Champion

    2014-07-01

    Full Text Available Dynamical downscaling is frequently used to investigate the dynamical variables of extra-tropical cyclones, for example, precipitation, using very high-resolution models nested within coarser resolution models to understand the processes that lead to intense precipitation. It is also used in climate change studies, using long timeseries to investigate trends in precipitation, or to look at the small-scale dynamical processes for specific case studies. This study investigates some of the problems associated with dynamical downscaling and looks at the optimum configuration to obtain the distribution and intensity of a precipitation field to match observations. This study uses the Met Office Unified Model run in limited area mode with grid spacings of 12, 4 and 1.5 km, driven by boundary conditions provided by the ECMWF Operational Analysis to produce high-resolution simulations for the Summer of 2007 UK flooding events. The numerical weather prediction model is initiated at varying times before the peak precipitation is observed to test the importance of the initialisation and boundary conditions, and how long the simulation can be run for. The results are compared to raingauge data as verification and show that the model intensities are most similar to observations when the model is initialised 12 hours before the peak precipitation is observed. It was also shown that using non-gridded datasets makes verification more difficult, with the density of observations also affecting the intensities observed. It is concluded that the simulations are able to produce realistic precipitation intensities when driven by the coarser resolution data.

  9. Using Multiple Monthly Water Balance Models to Evaluate Gridded Precipitation Products over Peninsular Spain

    Directory of Open Access Journals (Sweden)

    Javier Senent-Aparicio

    2018-06-01

    Full Text Available The availability of precipitation data is the key driver in the application of hydrological models when simulating streamflow. Ground weather stations are regularly used to measure precipitation. However, spatial coverage is often limited in low-population areas and mountain areas. To overcome this limitation, gridded datasets from remote sensing have been widely used. This study evaluates four widely used global precipitation datasets (GPDs: The Tropical Rainfall Measuring Mission (TRMM 3B43, the Climate Forecast System Reanalysis (CFSR, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, and the Multi-Source Weighted-Ensemble Precipitation (MSWEP, against point gauge and gridded dataset observations using multiple monthly water balance models (MWBMs in four different meso-scale basins that cover the main climatic zones of Peninsular Spain. The volumes of precipitation obtained from the GPDs tend to be smaller than those from the gauged data. Results underscore the superiority of the national gridded dataset, although the TRMM provides satisfactory results in simulating streamflow, reaching similar Nash-Sutcliffe values, between 0.70 and 0.95, and an average total volume error of 12% when using the GR2M model. The performance of GPDs highly depends on the climate, so that the more humid the watershed is, the better results can be achieved. The procedures used can be applied in regions with similar case studies to more accurately assess the resources within a system in which there is scarcity of recorded data available.

  10. Spanish Network for Isotopes in Precipitation: Isotope Spatial distribution and contribution to the knowledge of the hydrological cycle

    International Nuclear Information System (INIS)

    Diaz-Teijeiro, M. F.; Rodriguez-Arevalo, J.; Castano, S.

    2009-01-01

    The results of seven years of operation of the Spanish Network for Isotopes ( 2 H, 1 8O y 3 H) in Precipitation (REVIP) are shown. this Network is managed since 2000 by the Centro de Estudios de Tecnicas Aplicadas of the Centro de Estudios y Experimentacion de Obras Publicas (CEDEX) in collaboration with the Agencia Estatal de Meteorologia (AEMET). The results of REVIP are sent to the International Atomic Energy Agency (IAEA) in order to be integrated in the Global Network for Isotopes in Precipitation (GNIP). The spatial distribution of stable isotopes ( 1 8O h 2 H) in precipitation in Spain follows a multiple regression model, based on two geographic factors: latitude and elevation, which is strongly correlated with temperature, an important factor controlling isotope fractionation. This information on 1 8O and 2 H is useful to trace surface and ground waters and, combined with the information, about the spatial and temporal distribution of the Tritium ( 3 H) concentration in precipitation, allows to date these waters in order to estimate flow directions and velocities, and to evaluate the residence time of water resources and aquifer vulnerability. (Author)

  11. Insights into mountain precipitation and snowpack from a basin-scale wireless-sensor network

    Science.gov (United States)

    Zhang, Z.; Glaser, S.; Bales, R.; Conklin, M.; Rice, R.; Marks, D.

    2017-08-01

    A spatially distributed wireless-sensor network, installed across the 2154 km2 portion of the 5311 km2 American River basin above 1500 m elevation, provided spatial measurements of temperature, relative humidity, and snow depth in the Sierra Nevada, California. The network consisted of 10 sensor clusters, each with 10 measurement nodes, distributed to capture the variability in topography and vegetation cover. The sensor network captured significant spatial heterogeneity in rain versus snow precipitation for water-year 2014, variability that was not apparent in the more limited operational data. Using daily dew-point temperature to track temporal elevational changes in the rain-snow transition, the amount of snow accumulation at each node was used to estimate the fraction of rain versus snow. This resulted in an underestimate of total precipitation below the 0°C dew-point elevation, which averaged 1730 m across 10 precipitation events, indicating that measuring snow does not capture total precipitation. We suggest blending lower elevation rain gauge data with higher-elevation sensor-node data for each event to estimate total precipitation. Blended estimates were on average 15-30% higher than using either set of measurements alone. Using data from the current operational snow-pillow sites gives even lower estimates of basin-wide precipitation. Given the increasing importance of liquid precipitation in a warming climate, a strategy that blends distributed measurements of both liquid and solid precipitation will provide more accurate basin-wide precipitation estimates, plus spatial and temporal patters of snow accumulation and melt in a basin.

  12. Development of Bread Board Model of TRMM precipitation radar

    Science.gov (United States)

    Okamoto, Ken'ichi; Ihara, Toshio; Kumagai, Hiroshi

    The active array radar was selected as a reliable candidate for the TRMM (Tropical Rainfall Measuring Mission) precipitation radar after the trade off studies performed by Communications Research Laboratory (CRL) in the US-Japan joint feasibility study of TRMM in 1987-1988. Main system parameters and block diagram for TRMM precipitation radar are shown as the result of feasibility study. CRL developed key devices for the active array precipitation radar such as 8-element slotted waveguide array antenna, the 5 bit PIN diode phase shifters, solid state power amplifiers and low noise amplifiers in 1988-1990. Integration of these key devices was made to compose 8-element Bread Board Model of TRMM precipitation radar.

  13. Scaling of Precipitation Extremes Modelled by Generalized Pareto Distribution

    Science.gov (United States)

    Rajulapati, C. R.; Mujumdar, P. P.

    2017-12-01

    Precipitation extremes are often modelled with data from annual maximum series or peaks over threshold series. The Generalized Pareto Distribution (GPD) is commonly used to fit the peaks over threshold series. Scaling of precipitation extremes from larger time scales to smaller time scales when the extremes are modelled with the GPD is burdened with difficulties arising from varying thresholds for different durations. In this study, the scale invariance theory is used to develop a disaggregation model for precipitation extremes exceeding specified thresholds. A scaling relationship is developed for a range of thresholds obtained from a set of quantiles of non-zero precipitation of different durations. The GPD parameters and exceedance rate parameters are modelled by the Bayesian approach and the uncertainty in scaling exponent is quantified. A quantile based modification in the scaling relationship is proposed for obtaining the varying thresholds and exceedance rate parameters for shorter durations. The disaggregation model is applied to precipitation datasets of Berlin City, Germany and Bangalore City, India. From both the applications, it is observed that the uncertainty in the scaling exponent has a considerable effect on uncertainty in scaled parameters and return levels of shorter durations.

  14. Spatial interpolation of precipitation in a dense gauge network for monsoon storm events in the southwestern United States

    Science.gov (United States)

    Garcia, Matthew; Peters-Lidard, Christa D.; Goodrich, David C.

    2008-05-01

    Inaccuracy in spatially distributed precipitation fields can contribute significantly to the uncertainty of hydrological states and fluxes estimated from land surface models. This paper examines the results of selected interpolation methods for both convective and mixed/stratiform events that occurred during the North American monsoon season over a dense gauge network at the U.S. Department of Agriculture Agricultural Research Service Walnut Gulch Experimental Watershed in the southwestern United States. The spatial coefficient of variation for the precipitation field is employed as an indicator of event morphology, and a gauge clustering factor CF is formulated as a new, scale-independent measure of network organization. We consider that CF 0 (clustering in the gauge network) will produce errors because of reduced areal representation of the precipitation field. Spatial interpolation is performed using both inverse-distance-weighted (IDW) and multiquadric-biharmonic (MQB) methods. We employ ensembles of randomly selected network subsets for the statistical evaluation of interpolation errors in comparison with the observed precipitation. The magnitude of interpolation errors and differences in accuracy between interpolation methods depend on both the density and the geometrical organization of the gauge network. Generally, MQB methods outperform IDW methods in terms of interpolation accuracy under all conditions, but it is found that the order of the IDW method is important to the results and may, under some conditions, be just as accurate as the MQB method. In almost all results it is demonstrated that the inverse-distance-squared method for spatial interpolation, commonly employed in operational analyses and for engineering assessments, is inferior to the ID-cubed method, which is also more computationally efficient than the MQB method in studies of large networks.

  15. Downsizing a long-term precipitation network: Using a quantitative approach to inform difficult decisions.

    Science.gov (United States)

    Green, Mark B; Campbell, John L; Yanai, Ruth D; Bailey, Scott W; Bailey, Amey S; Grant, Nicholas; Halm, Ian; Kelsey, Eric P; Rustad, Lindsey E

    2018-01-01

    The design of a precipitation monitoring network must balance the demand for accurate estimates with the resources needed to build and maintain the network. If there are changes in the objectives of the monitoring or the availability of resources, network designs should be adjusted. At the Hubbard Brook Experimental Forest in New Hampshire, USA, precipitation has been monitored with a network established in 1955 that has grown to 23 gauges distributed across nine small catchments. This high sampling intensity allowed us to simulate reduced sampling schemes and thereby evaluate the effect of decommissioning gauges on the quality of precipitation estimates. We considered all possible scenarios of sampling intensity for the catchments on the south-facing slope (2047 combinations) and the north-facing slope (4095 combinations), from the current scenario with 11 or 12 gauges to only 1 gauge remaining. Gauge scenarios differed by as much as 6.0% from the best estimate (based on all the gauges), depending on the catchment, but 95% of the scenarios gave estimates within 2% of the long-term average annual precipitation. The insensitivity of precipitation estimates and the catchment fluxes that depend on them under many reduced monitoring scenarios allowed us to base our reduction decision on other factors such as technician safety, the time required for monitoring, and co-location with other hydrometeorological measurements (snow, air temperature). At Hubbard Brook, precipitation gauges could be reduced from 23 to 10 with a change of <2% in the long-term precipitation estimates. The decision-making approach illustrated in this case study is applicable to the redesign of monitoring networks when reduction of effort seems warranted.

  16. Precipitation of metal sulphides using gaseous hydrogen sulphide: mathematical modelling

    NARCIS (Netherlands)

    Al Tarazi, M.Y.M.; Heesink, Albertus B.M.; Versteeg, Geert

    2004-01-01

    A mathematical model has been developed that describes the precipitation of metal sulffides in an aqueous solution containing two different heavy metal ions. The solution is assumed to consist of a well-mixed bulk and a boundary layer that is contacted with hydrogen sulphide gas. The model makes use

  17. Precipitation of metal sulphides using gaseous hydrogen sulphide : mathematical modelling

    NARCIS (Netherlands)

    Tarazi, Mousa Al-; Heesink, A. Bert M.; Versteeg, Geert F.

    2004-01-01

    A mathematical model has been developed that describes the precipitation of metal sulphides in an aqueous solution containing two different heavy metal ions. The solution is assumed to consist of a well-mixed bulk and a boundary layer that is contacted with hydrogen sulphide gas. The model makes use

  18. Improved daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed.

    Science.gov (United States)

    Grimm, J W; Lynch, J A

    2005-06-01

    Daily precipitation nitrate and ammonium concentration models were developed for the Chesapeake Bay Watershed (USA) using a linear least-squares regression approach and precipitation chemistry data from 29 National Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites. Only weekly samples that comprised a single precipitation event were used in model development. The most significant variables in both ammonium and nitrate models included: precipitation volume, the number of days since the last event, a measure of seasonality, latitude, and the proportion of land within 8km covered by forest or devoted to industry and transportation. Additional variables included in the nitrate model were the proportion of land within 0.8km covered by water and/or forest. Local and regional ammonia and nitrogen oxide emissions were not as well correlated as land cover. Modeled concentrations compared very well with event chemistry data collected at six NADP/AirMoN sites within the Chesapeake Bay Watershed. Wet deposition estimates were also consistent with observed deposition at selected sites. Accurately describing the spatial distribution of precipitation volume throughout the watershed is important in providing critical estimates of wet-fall deposition of ammonium and nitrate.

  19. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    Science.gov (United States)

    Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.

    2012-01-01

    Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

  20. United States Historical Climatology Network Daily Temperature and Precipitation Data (1871-1997)

    Energy Technology Data Exchange (ETDEWEB)

    Easterling, D.R.

    2002-10-28

    This document describes a database containing daily observations of maximum and minimum temperature, precipitation amount, snowfall amount, and snow depth from 1062 observing stations across the contiguous US. This database is an expansion and update of the original 138-station database previously released by the Carbon Dioxide Information Analysis Center (CDIAC) as CDIAC numeric data package NDP-042. These 1062 stations are a subset of the 1221-station US Historical Climatology Network (HCN), a monthly database compiled by the National Climatic Data Center (Asheville, North Carolina) that has been widely used in analyzing US climate. Data from 1050 of these daily records extend into the 1990s, while 990 of these extend through 1997. Most station records are essentially complete for at least 40 years; the latest beginning year of record is 1948. Records from 158 stations begin prior to 1900, with that of Charleston, South Carolina beginning the earliest (1871). The daily resolution of these data makes them extremely valuable for studies attempting to detect and monitor long-term climatic changes on a regional scale. Studies using daily data may be able to detect changes in regional climate that would not be apparent from analysis of monthly temperature and precipitation data. Such studies may include analyses of trends in maximum and minimum temperatures, temperature extremes, daily temperature range, precipitation ''event size'' frequency, and the magnitude and duration of wet and dry periods. The data are also valuable in areas such as regional climate model validation and climate change impact assessment. This database is available free of charge from CDIAC as a numeric data package (NDP).

  1. Modeling of present and Eemian stable water isotopes in precipitation

    DEFF Research Database (Denmark)

    Sjolte, Jesper

    The subject of this thesis is the modeling of the isotopic temperature proxies d18O, dD and deuterium excess in precipitation. Two modeling studies were carried out, one using the regional climate model, and one using a global climate model. In the regional study the model was run for the period ...... the modeled isotopes do not agree with ice core data. The discrepancy between the model output and the ice core data is attributed to the boundary conditions, where changes in ice sheets and vegetation have not been accounted for.......The subject of this thesis is the modeling of the isotopic temperature proxies d18O, dD and deuterium excess in precipitation. Two modeling studies were carried out, one using the regional climate model, and one using a global climate model. In the regional study the model was run for the period...... 1959 to 2001 using meteorological data and a domain including Greenland and the surrounding North Atlantic. The model was found to reproduce the observed seasonal variability of temperature and precipitation well. In comparison with ice core data from Greenland and observations from coastal stations...

  2. Environmental controls on stable isotopes of precipitation in Lanzhou, China: An enhanced network at city scale.

    Science.gov (United States)

    Chen, Fenli; Zhang, Mingjun; Wang, Shengjie; Qiu, Xue; Du, Mingxia

    2017-12-31

    Stable hydrogen and oxygen isotopes in precipitation are very sensitive to environmental changes, and can record evolution of water cycle. The Lanzhou city in northwestern China is jointly influenced by the monsoon and westerlies, which is considered as a vital platform to investigate the moisture regime for this region. Since 2011, an observation network of stable isotopes in precipitation was established across the city, and four stations were included in the network. In 2013, six more sampling stations were added, and the enhanced network might provide more meaningful information on spatial incoherence and synoptic process. This study focused on the variations of stable isotopes (δ 18 O and δD) in precipitation and the environmental controls based on the 1432 samples in this enhanced network from April 2011 to October 2014. The results showed that the precipitation isotopes had great spatial diversity, and the neighboring stations may present large difference in δD and δ 18 O. Based on the observation at ten sampling sites, an isoscape in precipitation was calculated, and the method is useful to produce isoscape for small domains. The temperature effect and amount effect was reconsidered based on the dataset. Taking meteorological parameters (temperature, precipitation amount, relative humidity, water vapor pressure and dew point temperature) as variables in a multi-linear regression, the result of coefficients for these meteorological parameters were calculated. Some cases were also involved in this study, and the isotopic characteristics during one event or continuous days were used to understand the environmental controls on precipitation isotopes. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Modeling of Jovian Auroral Polar Ion and Proton Precipitation

    Science.gov (United States)

    Houston, S. J.; Ozak, N. O.; Cravens, T.; Schultz, D. R.; Mauk, B.; Haggerty, D. K.; Young, J. T.

    2017-12-01

    Auroral particle precipitation dominates the chemical and physical environment of the upper atmospheres and ionospheres of the outer planets. Precipitation of energetic electrons from the middle magnetosphere is responsible for the main auroral oval at Jupiter, but energetic electron, proton, and ion precipitation take place in the polar caps. At least some of the ion precipitation is associated with soft X-ray emission with about 1 GW of power. Theoretical modeling has demonstrated that the incident sulfur and oxygen ion energies must exceed about 0.5 MeV/nucleon (u) in order to produce the measured X-ray emission. In this work we present a model of the transport of magnetospheric oxygen ions as they precipitate into Jupiter's polar atmosphere. We have revised and updated the hybrid Monte Carlo model originally developed by Ozak et al., 2010 to model the Jovian X-ray aurora. We now simulate a wider range of incident oxygen ion energies (10 keV/u - 5 MeV/u) and update the collision cross-sections to model the ionization of the atmospheric neutrals. The polar cap location of the emission and magnetosphere-ionosphere coupling both indicate the associated field-aligned currents must originate near the magnetopause or perhaps the distant tail. Secondary electrons produced in the upper atmosphere by ion precipitation could be accelerated upward to relativistic energies due to the same field-aligned potentials responsible for the downward ion acceleration. To further explore this, we simulate the effect of the secondary electrons generated from the heavy ion precipitation. We use a two-stream transport model that computes the secondary electron fluxes, their escape from the atmosphere, and characterization of the H2 Lyman-Werner band emission, including a predicted observable spectrum with the associated color ratio. Our model predicts that escaping electrons have an energy range from 1 eV to 6 keV, H2 band emission rates produced are on the order of 75 kR for an input

  4. Test particle modeling of wave-induced energetic electron precipitation

    International Nuclear Information System (INIS)

    Chang, H.C.; Inan, U.S.

    1985-01-01

    A test particle computer model of the precipitation of radiation belt electrons is extended to compute the dynamic energy spectrum of transient electron fluxes induced by short-duration VLF wave packets traveling along the geomagnetic field lines. The model is adapted to estimate the count rate and associated spectrum of precipitated electrons that would be observed by satellite-based particle detectors with given geometric factor and orientation with respect to the magnetic field. A constant-frequency wave pulse and a lightning-induced whistler wave packet are used as examples of the stimulating wave signals. The effects of asymmetry of particle mirror heights in the two hemispheres and the atmospheric backscatter of loss cone particles on the computed precipitated fluxes are discussed

  5. The Passive Microwave Neural Network Precipitation Retrieval (PNPR) for AMSU/MHS and ATMS cross-track scanning radiometers

    Science.gov (United States)

    Sano', Paolo; Casella, Daniele; Panegrossi, Giulia; Cinzia Marra, Anna; Dietrich, Stefano

    2016-04-01

    Spaceborne microwave cross-track scanning radiometers, originally developed for temperature and humidity sounding, have shown great capabilities to provide a significant contribution in precipitation monitoring both in terms of measurement quality and spatial/temporal coverage. The Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross-track scanning radiometers, originally developed for the Advanced Microwave Sounding Unit/Microwave Humidity Sounder (AMSU-A/MHS) radiometers (on board the European MetOp and U.S. NOAA satellites), was recently newly designed to exploit the Advanced Technology Microwave Sounder (ATMS) on board the Suomi-NPP satellite and the future JPSS satellites. The PNPR algorithm is based on the Artificial Neural Network (ANN) approach. The main PNPR-ATMS algorithm changes with respect to PNPR-AMSU/MHS are the design and implementation of a new ANN able to manage the information derived from the additional ATMS channels (respect to the AMSU-A/MHS radiometer) and a new screening procedure for not-precipitating pixels. In order to achieve maximum consistency of the retrieved surface precipitation, both PNPR algorithms are based on the same physical foundation. The PNPR is optimized for the European and the African area. The neural network was trained using a cloud-radiation database built upon 94 cloud-resolving simulations over Europe and the Mediterranean and over the African area and radiative transfer model simulations of TB vectors consistent with the AMSU-A/MHS and ATMS channel frequencies, viewing angles, and view-angle dependent IFOV sizes along the scan projections. As opposed to other ANN precipitation retrieval algorithms, PNPR uses a unique ANN that retrieves the surface precipitation rate for all types of surface backgrounds represented in the training database, i.e., land (vegetated or arid), ocean, snow/ice or coast. This approach prevents different precipitation estimates from being inconsistent with one

  6. Dynamic process model of a plutonium oxalate precipitator. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Miller, C.L.; Hammelman, J.E.; Borgonovi, G.M.

    1977-11-01

    In support of LLL material safeguards program, a dynamic process model was developed which simulates the performance of a plutonium (IV) oxalate precipitator. The plutonium oxalate precipitator is a component in the plutonium oxalate process for making plutonium oxide powder from plutonium nitrate. The model is based on state-of-the-art crystallization descriptive equations, the parameters of which are quantified through the use of batch experimental data. The dynamic model predicts performance very similar to general Hanford oxalate process experience. The utilization of such a process model in an actual plant operation could promote both process control and material safeguards control by serving as a baseline predictor which could give early warning of process upsets or material diversion. The model has been incorporated into a FORTRAN computer program and is also compatible with the DYNSYS 2 computer code which is being used at LLL for process modeling efforts.

  7. Dynamic process model of a plutonium oxalate precipitator. Final report

    International Nuclear Information System (INIS)

    Miller, C.L.; Hammelman, J.E.; Borgonovi, G.M.

    1977-11-01

    In support of LLL material safeguards program, a dynamic process model was developed which simulates the performance of a plutonium (IV) oxalate precipitator. The plutonium oxalate precipitator is a component in the plutonium oxalate process for making plutonium oxide powder from plutonium nitrate. The model is based on state-of-the-art crystallization descriptive equations, the parameters of which are quantified through the use of batch experimental data. The dynamic model predicts performance very similar to general Hanford oxalate process experience. The utilization of such a process model in an actual plant operation could promote both process control and material safeguards control by serving as a baseline predictor which could give early warning of process upsets or material diversion. The model has been incorporated into a FORTRAN computer program and is also compatible with the DYNSYS 2 computer code which is being used at LLL for process modeling efforts

  8. V and V Efforts of Auroral Precipitation Models: Preliminary Results

    Science.gov (United States)

    Zheng, Yihua; Kuznetsova, Masha; Rastaetter, Lutz; Hesse, Michael

    2011-01-01

    Auroral precipitation models have been valuable both in terms of space weather applications and space science research. Yet very limited testing has been performed regarding model performance. A variety of auroral models are available, including empirical models that are parameterized by geomagnetic indices or upstream solar wind conditions, now casting models that are based on satellite observations, or those derived from physics-based, coupled global models. In this presentation, we will show our preliminary results regarding V&V efforts of some of the models.

  9. A glacier runoff extension to the Precipitation Runoff Modeling System

    Science.gov (United States)

    A. E. Van Beusekom; R. J. Viger

    2016-01-01

    A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while...

  10. MAP3S precipitation chemistry network: fourth periodic summary report (1980)

    Energy Technology Data Exchange (ETDEWEB)

    1981-12-01

    This, the fourth in a series of summary reports, contains complete field and chemical data from the MAP3S/RAINE (Multistate Atmospheric Power Production Pollution Studies) Precipitation Chemistry Network for the year 1980. The 1980 data were added to the previous data base, and an update of the previous statistical summary completed. Included are basic statistics, time trend analyses, and monthly averages.

  11. Mesoscale modeling of solute precipitation and radiation damage

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yongfeng [Idaho National Lab. (INL), Idaho Falls, ID (United States); Schwen, Daniel [Idaho National Lab. (INL), Idaho Falls, ID (United States); Ke, Huibin [Idaho National Lab. (INL), Idaho Falls, ID (United States); Univ. of Wisconsin, Madison, WI (United States); Bai, Xianming [Idaho National Lab. (INL), Idaho Falls, ID (United States); Hales, Jason [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-09-01

    This report summarizes the low length scale effort during FY 2014 in developing mesoscale capabilities for microstructure evolution in reactor pressure vessels. During operation, reactor pressure vessels are subject to hardening and embrittlement caused by irradiation-induced defect accumulation and irradiation-enhanced solute precipitation. Both defect production and solute precipitation start from the atomic scale, and manifest their eventual effects as degradation in engineering-scale properties. To predict the property degradation, multiscale modeling and simulation are needed to deal with the microstructure evolution, and to link the microstructure feature to material properties. In this report, the development of mesoscale capabilities for defect accumulation and solute precipitation are summarized. Atomic-scale efforts that supply information for the mesoscale capabilities are also included.

  12. Influence of rainfall observation network on model calibration and application

    Directory of Open Access Journals (Sweden)

    A. Bárdossy

    2008-01-01

    Full Text Available The objective in this study is to investigate the influence of the spatial resolution of the rainfall input on the model calibration and application. The analysis is carried out by varying the distribution of the raingauge network. A meso-scale catchment located in southwest Germany has been selected for this study. First, the semi-distributed HBV model is calibrated with the precipitation interpolated from the available observed rainfall of the different raingauge networks. An automatic calibration method based on the combinatorial optimization algorithm simulated annealing is applied. The performance of the hydrological model is analyzed as a function of the raingauge density. Secondly, the calibrated model is validated using interpolated precipitation from the same raingauge density used for the calibration as well as interpolated precipitation based on networks of reduced and increased raingauge density. Lastly, the effect of missing rainfall data is investigated by using a multiple linear regression approach for filling in the missing measurements. The model, calibrated with the complete set of observed data, is then run in the validation period using the above described precipitation field. The simulated hydrographs obtained in the above described three sets of experiments are analyzed through the comparisons of the computed Nash-Sutcliffe coefficient and several goodness-of-fit indexes. The results show that the model using different raingauge networks might need re-calibration of the model parameters, specifically model calibrated on relatively sparse precipitation information might perform well on dense precipitation information while model calibrated on dense precipitation information fails on sparse precipitation information. Also, the model calibrated with the complete set of observed precipitation and run with incomplete observed data associated with the data estimated using multiple linear regressions, at the locations treated as

  13. Precipitates/Salts Model Calculations for Various Drift Temperature Environments

    International Nuclear Information System (INIS)

    Marnier, P.

    2001-01-01

    The objective and scope of this calculation is to assist Performance Assessment Operations and the Engineered Barrier System (EBS) Department in modeling the geochemical effects of evaporation within a repository drift. This work is developed and documented using procedure AP-3.12Q, Calculations, in support of ''Technical Work Plan For Engineered Barrier System Department Modeling and Testing FY 02 Work Activities'' (BSC 2001a). The primary objective of this calculation is to predict the effects of evaporation on the abstracted water compositions established in ''EBS Incoming Water and Gas Composition Abstraction Calculations for Different Drift Temperature Environments'' (BSC 2001c). A secondary objective is to predict evaporation effects on observed Yucca Mountain waters for subsequent cement interaction calculations (BSC 2001d). The Precipitates/Salts model is documented in an Analysis/Model Report (AMR), ''In-Drift Precipitates/Salts Analysis'' (BSC 2001b)

  14. The Alaska Water Isotope Network (AKWIN): Precipitation, lake, river and stream dynamics

    Science.gov (United States)

    Rogers, M.; Welker, J. M.; Toohey, R.

    2011-12-01

    The hydrologic cycle is central to the structure and function of northern landscapes. The movement of water creates interactions between terrestrial, aquatic, marine and atmospheric processes. Understanding the processes and the spatial patterns that govern the isotopic (δ18O & δD) characteristics of the hydrologic cycle is especially important today as: a) modern climate/weather-isotope relations allow for more accurate interpretation of climate proxies and the calibration of atmospheric models, b) water isotopes facilitate understanding the role of storm tracks in regulating precipitation isotopic variability, c) water isotopes allow for estimates of glacial melt water inputs into aquatic systems, d) water isotopes allow for quantification of surface and groundwater interactions, e) water isotopes allow for quantification of permafrost meltwater use by plant communities, f) water isotopes aid in migratory bird forensics, g) water isotopes are critical to estimating field metabolic rates, h) water isotopes allow for crop and diet forensics and i) water isotopes can provide insight into evaporation and transpiration processes. As part of a new NSF MRI project at the Environment and Natural Resources Institute (ENRI) at the University of Alaska Anchorage and as an extension of the US Network for Isotopes in Precipitation (USNIP); we are forming AKWIN. The network will utilize long-term weekly sampling at Denali National Park and Caribou Poker Creek Watershed (USNIP sites-1989 to present), regular sampling across Alaska involving land management agencies (USGS, NPS, USFWS, EPA), educators, volunteers and citizen scientists, UA extended campuses, individual research projects, opportunistic sampling and published data to construct isoscapes and time series databases and information packages. We will be using a suite of spatial and temporal analysis methods to characterize water isotopes across Alaska and will provide web portals for data products. Our network is

  15. Using stochastic space-time models to map extreme precipitation in southern Portugal

    Directory of Open Access Journals (Sweden)

    A. C. Costa

    2008-07-01

    Full Text Available The topographic characteristics and spatial climatic diversity are significant in the South of continental Portugal where the rainfall regime is typically Mediterranean. Direct sequential cosimulation is proposed for mapping an extreme precipitation index in southern Portugal using elevation as auxiliary information. The analysed index (R5D can be considered a flood indicator because it provides a measure of medium-term precipitation total. The methodology accounts for local data variability and incorporates space-time models that allow capturing long-term trends of extreme precipitation, and local changes in the relationship between elevation and extreme precipitation through time. Annual gridded datasets of the flood indicator are produced from 1940 to 1999 on 800 m×800 m grids by using the space-time relationship between elevation and the index. Uncertainty evaluations of the proposed scenarios are also produced for each year. The results indicate that the relationship between elevation and extreme precipitation varies locally and has decreased through time over the study region. In wetter years the flood indicator exhibits the highest values in mountainous regions of the South, while in drier years the spatial pattern of extreme precipitation has much less variability over the study region. The uncertainty of extreme precipitation estimates also varies in time and space, and in earlier decades is strongly dependent on the density of the monitoring stations network. The produced maps will be useful in regional and local studies related to climate change, desertification, land and water resources management, hydrological modelling, and flood mitigation planning.

  16. PbO networks composed of single crystalline nanosheets synthesized by a facile chemical precipitation method

    Energy Technology Data Exchange (ETDEWEB)

    Samberg, Joshua P. [Department of Materials Science and Engineering, North Carolina State University, 911 Partners Way, Engineering Building I, Raleigh, NC 27695-7907 (United States); Kajbafvala, Amir, E-mail: amir.kajbafvala@gmail.com [Department of Materials Science and Engineering, North Carolina State University, 911 Partners Way, Engineering Building I, Raleigh, NC 27695-7907 (United States); Koolivand, Amir [Department of Chemistry, North Carolina State University, 2620 Yarbrough Drive, Raleigh, NC 27695 (United States)

    2014-03-01

    Graphical abstract: - Highlights: • Synthesis of PbO networks through a simple chemical precipitation route. • The synthesis method is rapid and low-cost. • Each network is composed of single crystalline PbO nanosheets. • A possible growth mechanism is proposed for synthesized PbO networks. - Abstract: For the field of energy storage, nanostructured lead oxide (PbO) shows immense potential for increased specific energy and deep discharge for lead acid battery technologies. In this work, PbO networks composed of single crystalline nanosheets were synthesized utilizing a simple, low cost and rapid chemical precipitation method. The PbO networks were prepared in a single reaction vessel from starting reagents of lead acetate dehydrate, ammonium hydroxide and deionized water. Lead acetate dehydrate was chosen as a reagent, as opposed to lead nitrate, to eliminate the possibility of nitrate contamination of the final product. X-ray diffraction (XRD) analysis, high resolution scanning electron microscopy (HRSEM) and high resolution transmission electron microscopy (HRTEM) analysis were used to characterize the synthesized PbO networks. The reproducible method described herein synthesized pure β-PbO (massicot) powders, with no byproducts. A possible formation mechanism for these PbO networks is proposed. The growth is found to proceed predominately in the 〈1 1 1〉 and 〈2 0 0〉 directions while being limited in the 〈0 1 1〉 direction.

  17. PbO networks composed of single crystalline nanosheets synthesized by a facile chemical precipitation method

    International Nuclear Information System (INIS)

    Samberg, Joshua P.; Kajbafvala, Amir; Koolivand, Amir

    2014-01-01

    Graphical abstract: - Highlights: • Synthesis of PbO networks through a simple chemical precipitation route. • The synthesis method is rapid and low-cost. • Each network is composed of single crystalline PbO nanosheets. • A possible growth mechanism is proposed for synthesized PbO networks. - Abstract: For the field of energy storage, nanostructured lead oxide (PbO) shows immense potential for increased specific energy and deep discharge for lead acid battery technologies. In this work, PbO networks composed of single crystalline nanosheets were synthesized utilizing a simple, low cost and rapid chemical precipitation method. The PbO networks were prepared in a single reaction vessel from starting reagents of lead acetate dehydrate, ammonium hydroxide and deionized water. Lead acetate dehydrate was chosen as a reagent, as opposed to lead nitrate, to eliminate the possibility of nitrate contamination of the final product. X-ray diffraction (XRD) analysis, high resolution scanning electron microscopy (HRSEM) and high resolution transmission electron microscopy (HRTEM) analysis were used to characterize the synthesized PbO networks. The reproducible method described herein synthesized pure β-PbO (massicot) powders, with no byproducts. A possible formation mechanism for these PbO networks is proposed. The growth is found to proceed predominately in the 〈1 1 1〉 and 〈2 0 0〉 directions while being limited in the 〈0 1 1〉 direction

  18. A Global Model for Circumgalactic and Cluster-core Precipitation

    Science.gov (United States)

    Voit, G. Mark; Meece, Greg; Li, Yuan; O'Shea, Brian W.; Bryan, Greg L.; Donahue, Megan

    2017-08-01

    We provide an analytic framework for interpreting observations of multiphase circumgalactic gas that is heavily informed by recent numerical simulations of thermal instability and precipitation in cool-core galaxy clusters. We start by considering the local conditions required for the formation of multiphase gas via two different modes: (1) uplift of ambient gas by galactic outflows, and (2) condensation in a stratified stationary medium in which thermal balance is explicitly maintained. Analytic exploration of these two modes provides insights into the relationships between the local ratio of the cooling and freefall timescales (I.e., {t}{cool}/{t}{ff}), the large-scale gradient of specific entropy, and the development of precipitation and multiphase media in circumgalactic gas. We then use these analytic findings to interpret recent simulations of circumgalactic gas in which global thermal balance is maintained. We show that long-lasting configurations of gas with 5≲ \\min ({t}{cool}/{t}{ff})≲ 20 and radial entropy profiles similar to observations of cool cores in galaxy clusters are a natural outcome of precipitation-regulated feedback. We conclude with some observational predictions that follow from these models. This work focuses primarily on precipitation and AGN feedback in galaxy-cluster cores, because that is where the observations of multiphase gas around galaxies are most complete. However, many of the physical principles that govern condensation in those environments apply to circumgalactic gas around galaxies of all masses.

  19. Modeling of hydride precipitation and re-orientation

    Energy Technology Data Exchange (ETDEWEB)

    Tikare, Veena [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Weck, Philippe F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mitchell, John Anthony [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-09-18

    In this report, we present a thermodynamic-­based model of hydride precipitation in Zr-based claddings. The model considers the state of the cladding immediately following drying, after removal from cooling-pools, and presents the evolution of precipitate formation upon cooling as follows: The pilgering process used to form Zr-based cladding imparts strong crystallographic and grain shape texture, with the basal plane of the hexagonal α-Zr grains being strongly aligned in the rolling-­direction and the grains are elongated with grain size being approximately twice as long parallel to the rolling direction, which is also the long axis of the tubular cladding, as it is in the orthogonal directions.

  20. Statistical Models for Social Networks

    NARCIS (Netherlands)

    Snijders, Tom A. B.; Cook, KS; Massey, DS

    2011-01-01

    Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For

  1. Evaluation of the WRF model for precipitation downscaling on orographic complex islands

    Science.gov (United States)

    Díaz, Juan P.; González, Albano; Expósito, Francisco; Pérez, Juan C.

    2010-05-01

    General Circulation Models (GCMs) have proven to be an effective tool to simulate many aspects of large-scale and global climate. However, their applicability to climate impact studies is limited by their capabilities to resolve regional scale situations. In this sense, dynamical downscaling techniques are an appropriate alternative to estimate high resolution regional climatologies. In this work, the Weather Research and Forecasting model (WRF) has been used to simulate precipitations over the Canary Islands region during 2009. The precipitation patterns over Canary Islands, located at North Atlantic region, show large gradients over a relatively small geographical area due to large scale factors such as Trade Winds regime predominant in the area and mesoscale factors mainly due to the complex terrain. Sensitivity study of simulated WRF precipitations to variations in model setup and parameterizations was carried out. Thus, WRF experiments were performed using two way nesting at 3 km horizontal grid spacing and 28 vertical levels in the Canaries inner domain. The initial and lateral and lower boundary conditions for the outer domain were provided at 6 hourly intervals by NCEP FNL (Final) Operational Global Analysis data on 1.0x1.0 degree resolution interpolated onto the WRF model grid. Numerous model options have been tested, including different microphysics schemes, cumulus parameterizations and nudging configuration Positive-definite moisture advection condition was also checked. Two integration approaches were analyzed: a 1-year continuous long-term integration and a consecutive short-term monthly reinitialized integration. To assess the accuracy of our simulations, model results are compared against observational datasets obtained from a network of meteorological stations in the region. In general, we can observe that the regional model is able to reproduce the spatial distribution of precipitation, but overestimates rainfall, mainly during strong

  2. Multisite bias correction of precipitation data from regional climate models

    Czech Academy of Sciences Publication Activity Database

    Hnilica, Jan; Hanel, M.; Puš, V.

    2017-01-01

    Roč. 37, č. 6 (2017), s. 2934-2946 ISSN 0899-8418 R&D Projects: GA ČR GA16-05665S Grant - others:Grantová agentura ČR - GA ČR(CZ) 16-16549S Institutional support: RVO:67985874 Keywords : bias correction * regional climate model * correlation * covariance * multivariate data * multisite correction * principal components * precipitation Subject RIV: DA - Hydrology ; Limnology OBOR OECD: Climatic research Impact factor: 3.760, year: 2016

  3. Effect of the precipitation interpolation method on the performance of a snowmelt runoff model

    Science.gov (United States)

    Jacquin, Alexandra

    2014-05-01

    Uncertainties on the spatial distribution of precipitation seriously affect the reliability of the discharge estimates produced by watershed models. Although there is abundant research evaluating the goodness of fit of precipitation estimates obtained with different gauge interpolation methods, few studies have focused on the influence of the interpolation strategy on the response of watershed models. The relevance of this choice may be even greater in the case of mountain catchments, because of the influence of orography on precipitation. This study evaluates the effect of the precipitation interpolation method on the performance of conceptual type snowmelt runoff models. The HBV Light model version 4.0.0.2, operating at daily time steps, is used as a case study. The model is applied in Aconcagua at Chacabuquito catchment, located in the Andes Mountains of Central Chile. The catchment's area is 2110[Km2] and elevation ranges from 950[m.a.s.l.] to 5930[m.a.s.l.] The local meteorological network is sparse, with all precipitation gauges located below 3000[m.a.s.l.] Precipitation amounts corresponding to different elevation zones are estimated through areal averaging of precipitation fields interpolated from gauge data. Interpolation methods applied include kriging with external drift (KED), optimal interpolation method (OIM), Thiessen polygons (TP), multiquadratic functions fitting (MFF) and inverse distance weighting (IDW). Both KED and OIM are able to account for the existence of a spatial trend in the expectation of precipitation. By contrast, TP, MFF and IDW, traditional methods widely used in engineering hydrology, cannot explicitly incorporate this information. Preliminary analysis confirmed that these methods notably underestimate precipitation in the study catchment, while KED and OIM are able to reduce the bias; this analysis also revealed that OIM provides more reliable estimations than KED in this region. Using input precipitation obtained by each method

  4. Data Visualization and Analysis Tools for the Global Precipitation Measurement (GPM) Validation Network

    Science.gov (United States)

    Morris, Kenneth R.; Schwaller, Mathew

    2010-01-01

    The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) Mission compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) to similar measurements from U.S. and international operational weather radars. This prototype is a major component of the GPM Ground Validation System (GVS). The VN provides a means for the precipitation measurement community to identify and resolve significant discrepancies between the ground radar (GR) observations and similar satellite observations. The VN prototype is based on research results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller (2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for the comparisons. This paper describes software tools that have been developed for visualization and statistical analysis of the original and volume matched PR and GR data.

  5. Dynamic modelling of processes in rivers affected by precipitation runoff

    DEFF Research Database (Denmark)

    Jacobsen, Judith L.

    1997-01-01

    In this thesis, models for the dynamics of oxygen and organic matter in receiving waters (such as rivers and creeks), which are affected by rain, are developed. A time series analysis framework is used, but presented with special emphasis on continuous time state space models. Also, the concept o....... In most models, precipitation in the form of rain have been included to study the impact from this. Finally, the future and industrial perspectives are presented, along with a list of suggestions for future research related to the subjects considered in this thesis....

  6. Wax Precipitation Modeled with Many Mixed Solid Phases

    DEFF Research Database (Denmark)

    Heidemann, Robert A.; Madsen, Jesper; Stenby, Erling Halfdan

    2005-01-01

    The behavior of the Coutinho UNIQUAC model for solid wax phases has been examined. The model can produce as many mixed solid phases as the number of waxy components. In binary mixtures, the solid rich in the lighter component contains little of the heavier component but the second phase shows sub......-temperature and low-temperature forms, are pure. Model calculations compare well with the data of Pauly et al. for C18 to C30 waxes precipitating from n-decane solutions. (C) 2004 American Institute of Chemical Engineers....

  7. Mineral Precipitation in Fractures: Multiscale Imaging and Geochemical Modeling

    Science.gov (United States)

    Hajirezaie, S.; Peters, C. A.; Swift, A.; Sheets, J. M.; Cole, D. R.; Crandall, D.; Cheshire, M.; Stack, A. G.; Anovitz, L. M.

    2017-12-01

    For subsurface energy technologies such as geologic carbon sequestration, fractures are potential pathways for fluid migration from target formations. Highly permeable fractures may become sealed by mineral precipitation. In this study, we examined shale specimens with existing cemented fractures as natural analogues, using an array of imaging methods to characterize mineralogy and porosity at several spatial scales. In addition, we used reactive transport modeling to investigate geochemical conditions that can lead to extensive mineral precipitation and to simulate the impacts on fracture hydraulic properties. The naturally-cemented fractured rock specimens were from the Upper Wolfcamp formation in Texas, at 10,000 ft depth. The specimens were scanned using x-ray computed tomography (xCT) at resolution of 13 microns. The xCT images revealed an original fracture aperture of 1.9 mm filled with several distinct mineral phases and vuggy void regions, and the mineral phase volumes and surface areas were quantified and mapped in 3D. Specimens were thin-sectioned and examined at micron- and submicron-scales using petrographic microscopy (PM), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), and small angle X-ray scattering (SAXS). Collectively these methods revealed crystals of dolomite as large as 900 microns in length overlain with a heterogeneous mixture of carbonate minerals including calcite, dolomite, and Fe-rich dolomite, interspersed at spatial scales as small as 5 microns. In addition, secondary precipitation of SiO2 was found to fill some of the void space. This multiscale imaging was used to inform the reactive transport modeling employed to examine the conditions that can cause the observed mineral precipitation in fractures at a larger scale. Two brines containing solutions that when mixed would lead to precipitation of various carbonate minerals were simulated as injectants into a fracture domain. In particular, the competing

  8. Precipitation data for water years 1992 and 1993 from a network of nonrecording gages at Yucca Mountain, Nevada

    International Nuclear Information System (INIS)

    Ambos, D.S.; Flint, A.L.; Hevesi, J.A.

    1995-01-01

    This report presents precipitation data collected in a storage gage network at Yucca Mountain, Nevada, from October 1, 1991, to September 30, 1993. The measured values indicate total accumulated precipitation for specified time intervals approximately corresponding to separate storm events. Installation of a precipitation monitoring network was initiated in January 1990, and was continually expanded and upgraded throughout the period ending in September 1993. The final network included 3 different gage types for a total of 133 gages at 108 locations within the three drainages overlying the potential repository site. Measured precipitation indicated above average accumulations for water years 1992 and 1993 relative to the most recent estimate of 6.7 inches for long-term average annual precipitation over the area of the network. The total precipitation averaged over the network in 1992 was about 8.2 inches with a maximum of about 11.2 inches measured at borehole USW GA-1. The total precipitation averaged over the network in 1993 was about 10.3 inches with a maximum of about 12.1 inches at neutron-access borehole UE-25 UZN number-sign 4

  9. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim

    2014-12-03

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  10. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim; Chasparis, Georgios; Shamma, Jeff S.

    2014-01-01

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  11. Isotopic composition of precipitations in Brazil: isothermic models and the influence of evapotranspiration in the Amazonic Basin

    International Nuclear Information System (INIS)

    Dall'Olio, Attilio.

    1976-11-01

    The simplest theoretical models of the isotopic fractionation of water during equilibrium isothermical processes are analized in detail. The theoretical results are applied to the interpretation of the stable isotope concentrations in the precipitations of 11 Brazilian cities that belong to the international network of IAEA/WMO. The analysis shows that the experimental data are fairly consistent with such equilibrium models; no non-equilibrium processes need to be assumed. The study of the stable isotope content of precipitations in the Amazonic Basin suggests some modifications to the models in order that the evapotranspiration contribution to the vapour balance be taken into account [pt

  12. Macroscopic diffusion models for precipitation in crystalline gallium arsenide

    Energy Technology Data Exchange (ETDEWEB)

    Kimmerle, Sven-Joachim Wolfgang

    2009-09-21

    Based on a thermodynamically consistent model for precipitation in gallium arsenide crystals including surface tension and bulk stresses by Dreyer and Duderstadt, we propose two different mathematical models to describe the size evolution of liquid droplets in a crystalline solid. The first model treats the diffusion-controlled regime of interface motion, while the second model is concerned with the interface-controlled regime of interface motion. Our models take care of conservation of mass and substance. These models generalise the well-known Mullins- Sekerka model for Ostwald ripening. We concentrate on arsenic-rich liquid spherical droplets in a gallium arsenide crystal. Droplets can shrink or grow with time but the centres of droplets remain fixed. The liquid is assumed to be homogeneous in space. Due to different scales for typical distances between droplets and typical radii of liquid droplets we can derive formally so-called mean field models. For a model in the diffusion-controlled regime we prove this limit by homogenisation techniques under plausible assumptions. These mean field models generalise the Lifshitz-Slyozov-Wagner model, which can be derived from the Mullins-Sekerka model rigorously, and is well understood. Mean field models capture the main properties of our system and are well adapted for numerics and further analysis. We determine possible equilibria and discuss their stability. Numerical evidence suggests in which case which one of the two regimes might be appropriate to the experimental situation. (orig.)

  13. Modelling the Spatial Isotope Variability of Precipitation in Syria

    Energy Technology Data Exchange (ETDEWEB)

    Kattan, Z.; Kattaa, B. [Department of Geology, Atomic Energy Commission of Syria (AECS), Damascus (Syrian Arab Republic)

    2013-07-15

    Attempts were made to model the spatial variability of environmental isotope ({sup 18}O, {sup 2}H and {sup 3}H) compositions of precipitation in syria. Rainfall samples periodically collected on a monthly basis from 16 different stations were used for processing and demonstrating the spatial distributions of these isotopes, together with those of deuterium excess (d) values. Mathematically, the modelling process was based on applying simple polynomial models that take into consideration the effects of major geographic factors (Lon.E., Lat.N., and altitude). The modelling results of spatial distribution of stable isotopes ({sup 18}O and {sup 2}H) were generally good, as shown from the high correlation coefficients (R{sup 2} = 0.7-0.8), calculated between the observed and predicted values. In the case of deuterium excess and tritium distributions, the results were most likely approximates (R{sup 2} = 0.5-0.6). Improving the simulation of spatial isotope variability probably requires the incorporation of other local meteorological factors, such as relative air humidity, precipitation amount and vapour pressure, which are supposed to play an important role in such an arid country. (author)

  14. Precipitates/Salts Model Calculations for Various Drift Temperature Environments

    Energy Technology Data Exchange (ETDEWEB)

    P. Marnier

    2001-12-20

    The objective and scope of this calculation is to assist Performance Assessment Operations and the Engineered Barrier System (EBS) Department in modeling the geochemical effects of evaporation within a repository drift. This work is developed and documented using procedure AP-3.12Q, Calculations, in support of ''Technical Work Plan For Engineered Barrier System Department Modeling and Testing FY 02 Work Activities'' (BSC 2001a). The primary objective of this calculation is to predict the effects of evaporation on the abstracted water compositions established in ''EBS Incoming Water and Gas Composition Abstraction Calculations for Different Drift Temperature Environments'' (BSC 2001c). A secondary objective is to predict evaporation effects on observed Yucca Mountain waters for subsequent cement interaction calculations (BSC 2001d). The Precipitates/Salts model is documented in an Analysis/Model Report (AMR), ''In-Drift Precipitates/Salts Analysis'' (BSC 2001b).

  15. Patterns of precipitation and soil moisture extremes in Texas, US: A complex network analysis

    Science.gov (United States)

    Sun, Alexander Y.; Xia, Youlong; Caldwell, Todd G.; Hao, Zengchao

    2018-02-01

    Understanding of the spatial and temporal dynamics of extreme precipitation not only improves prediction skills, but also helps to prioritize hazard mitigation efforts. This study seeks to enhance the understanding of spatiotemporal covariation patterns embedded in precipitation (P) and soil moisture (SM) by using an event-based, complex-network-theoretic approach. Events concurrences are quantified using a nonparametric event synchronization measure, and spatial patterns of hydroclimate variables are analyzed by using several network measures and a community detection algorithm. SM-P coupling is examined using a directional event coincidence analysis measure that takes the order of event occurrences into account. The complex network approach is demonstrated for Texas, US, a region possessing a rich set of hydroclimate features and is frequented by catastrophic flooding. Gridded daily observed P data and simulated SM data are used to create complex networks of P and SM extremes. The uncovered high degree centrality regions and community structures are qualitatively in agreement with the overall existing knowledge of hydroclimate extremes in the study region. Our analyses provide new visual insights on the propagation, connectivity, and synchronicity of P extremes, as well as the SM-P coupling, in this flood-prone region, and can be readily used as a basis for event-driven predictive analytics for other regions.

  16. Applying an orographic precipitation model to improve mass balance modeling of the Juneau Icefield, AK

    Science.gov (United States)

    Roth, A. C.; Hock, R.; Schuler, T.; Bieniek, P.; Aschwanden, A.

    2017-12-01

    Mass loss from glaciers in Southeast Alaska is expected to alter downstream ecological systems as runoff patterns change. To investigate these potential changes under future climate scenarios, distributed glacier mass balance modeling is required. However, the spatial resolution gap between global or regional climate models and the requirements for glacier mass balance modeling studies must be addressed first. We have used a linear theory of orographic precipitation model to downscale precipitation from both the Weather Research and Forecasting (WRF) model and ERA-Interim to the Juneau Icefield region over the period 1979-2013. This implementation of the LT model is a unique parameterization that relies on the specification of snow fall speed and rain fall speed as tuning parameters to calculate the cloud time delay, τ. We assessed the LT model results by considering winter precipitation so the effect of melt was minimized. The downscaled precipitation pattern produced by the LT model captures the orographic precipitation pattern absent from the coarse resolution WRF and ERA-Interim precipitation fields. Observational data constraints limited our ability to determine a unique parameter combination and calibrate the LT model to glaciological observations. We established a reference run of parameter values based on literature and performed a sensitivity analysis of the LT model parameters, horizontal resolution, and climate input data on the average winter precipitation. The results of the reference run showed reasonable agreement with the available glaciological measurements. The precipitation pattern produced by the LT model was consistent regardless of parameter combination, horizontal resolution, and climate input data, but the precipitation amount varied strongly with these factors. Due to the consistency of the winter precipitation pattern and the uncertainty in precipitation amount, we suggest a precipitation index map approach to be used in combination with

  17. Modeling online social signed networks

    Science.gov (United States)

    Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

    2018-04-01

    People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

  18. Model Fitting for Predicted Precipitation in Darwin: Some Issues with Model Choice

    Science.gov (United States)

    Farmer, Jim

    2010-01-01

    In Volume 23(2) of the "Australian Senior Mathematics Journal," Boncek and Harden present an exercise in fitting a Markov chain model to rainfall data for Darwin Airport (Boncek & Harden, 2009). Days are subdivided into those with precipitation and precipitation-free days. The author abbreviates these labels to wet days and dry days.…

  19. Storms over the METER--ORNL Precipitation Network: the first six months

    International Nuclear Information System (INIS)

    Miller, R.L.; Patrinos, A.A.N.; Saylor, R.E.

    1979-06-01

    This report presents the first set of data collected by the METER--ORNL Precipitation Network. This network of 49 recording raingages and 5 recording windsets was installed in February 1978, around the Bowen Electric Generating Plant in northwest Georgia for the purpose of investigating the potential effect of the plant's cooling towers on rainfall. This study is conducted on behalf of the DOE Program on Meteorological Effects of Thermal Energy Releases (METER). Included in this report are the complete descriptions of 98 rainfall events which occurred over the METER--ORNL network during the period February 22--August 31, 1978. These descriptions are augmented by information and data supplied by the National Weather Service (NWS). Several stratifications of the rainfall events are performed for reference purposes

  20. A neighbourhood evolving network model

    International Nuclear Information System (INIS)

    Cao, Y.J.; Wang, G.Z.; Jiang, Q.Y.; Han, Z.X.

    2006-01-01

    Many social, technological, biological and economical systems are best described by evolved network models. In this short Letter, we propose and study a new evolving network model. The model is based on the new concept of neighbourhood connectivity, which exists in many physical complex networks. The statistical properties and dynamics of the proposed model is analytically studied and compared with those of Barabasi-Albert scale-free model. Numerical simulations indicate that this network model yields a transition between power-law and exponential scaling, while the Barabasi-Albert scale-free model is only one of its special (limiting) cases. Particularly, this model can be used to enhance the evolving mechanism of complex networks in the real world, such as some social networks development

  1. MODELING OF ISOTHERMAL PRECIPITATION KINETICS IN HSLA STEELS AND ITS APPLICATION

    Institute of Scientific and Technical Information of China (English)

    X.M. Zhao; D. Wu; L.Z. Zhang; Z.Y. Liu

    2004-01-01

    Microalloying elements in high-strength low-alloy steels, such as Nb, Ti and V, precipitate during hot-rolling processes. On the basis of classical theory of nucleation and growth, quantitative modeling of isothermal precipitation was developed, which was tested by the stress relaxation method, the calculated precipitation-time-temperature curve is in good agreements with the measured results, then the model was applied to predict the precipitation behavior during continuous cooling.

  2. Fronts and precipitation in CMIP5 models for the austral winter of the Southern Hemisphere

    Science.gov (United States)

    Blázquez, Josefina; Solman, Silvina A.

    2018-04-01

    Wintertime fronts climatology and the relationship between fronts and precipitation as depicted by a group of CMIP5 models are evaluated over the Southern Hemisphere (SH). The frontal activity is represented by an index that takes into account the vorticity, the gradient of temperature and the specific humidity at the 850 hPa level. ERA-Interim reanalysis and GPCP datasets are used to assess the performance of the models in the present climate. Overall, it is found that the models can reproduce adequately the main features of frontal activity and front frequency over the SH. The total precipitation is overestimated in most of the models, especially the maximum values over the mid latitudes. This overestimation could be related to the high values of precipitation frequency that are identified in some of the models evaluated. The relationship between fronts and precipitation has also been evaluated in terms of both frequency of frontal precipitation and percentage of precipitation due to fronts. In general terms, the models overestimate the proportion between frontal and total precipitation. In contrast with frequency of total precipitation, the frequency of frontal precipitation is well reproduced by the models, with the higher values located at the mid latitudes. The results suggest that models represent very well the dynamic forcing (fronts) and the frequency of frontal precipitation, though the amount of precipitation due to fronts is overestimated.

  3. Modeled Watershed Runoff Associated with Variations in Precipitation Data, with Implications for Contaminant Fluxes: Initial Results

    Science.gov (United States)

    Precipitation is one of the primary forcing functions of hydrologic and watershed fate and transport models; however, in light of advances in precipitation estimates across watersheds, data remain highly uncertain. A wide variety of simulated and observed precipitation data are a...

  4. Comparison of precipitation chemistry measurements obtained by the Canadian Air and Precipitation Monitoring Network and National Atmospheric Deposition Program for the period 1995-2004

    Science.gov (United States)

    Wetherbee, Gregory A.; Shaw, Michael J.; Latysh, Natalie E.; Lehmann, Christopher M.B.; Rothert, Jane E.

    2010-01-01

    Precipitation chemistry and depth measurements obtained by the Canadian Air and Precipitation Monitoring Network (CAPMoN) and the US National Atmospheric Deposition Program/National Trends Network (NADP/NTN) were compared for the 10-year period 1995–2004. Colocated sets of CAPMoN and NADP instrumentation, consisting of precipitation collectors and rain gages, were operated simultaneously per standard protocols for each network at Sutton, Ontario and Frelighsburg, Ontario, Canada and at State College, PA, USA. CAPMoN samples were collected daily, and NADP samples were collected weekly, and samples were analyzed exclusively by each network’s laboratory for pH, H + , Ca2+  , Mg2+  , Na + , K + , NH+4 , Cl − , NO−3 , and SO2−4 . Weekly and annual precipitation-weighted mean concentrations for each network were compared. This study is a follow-up to an earlier internetwork comparison for the period 1986–1993, published by Alain Sirois, Robert Vet, and Dennis Lamb in 2000. Median weekly internetwork differences for 1995–2004 data were the same to slightly lower than for data for the previous study period (1986–1993) for all analytes except NO−3 , SO2−4 , and sample depth. A 1994 NADP sampling protocol change and a 1998 change in the types of filters used to process NADP samples reversed the previously identified negative bias in NADP data for hydrogen-ion and sodium concentrations. Statistically significant biases (α = 0.10) for sodium and hydrogen-ion concentrations observed in the 1986–1993 data were not significant for 1995–2004. Weekly CAPMoN measurements generally are higher than weekly NADP measurements due to differences in sample filtration and field instrumentation, not sample evaporation, contamination, or analytical laboratory differences.

  5. Climate network analysis of regional precipitation extremes: The true story told by event synchronization

    Science.gov (United States)

    Odenweller, Adrian; Donner, Reik V.

    2017-04-01

    Over the last decade, complex network methods have been frequently used for characterizing spatio-temporal patterns of climate variability from a complex systems perspective, yielding new insights into time-dependent teleconnectivity patterns and couplings between different components of the Earth climate. Among the foremost results reported, network analyses of the synchronicity of extreme events as captured by the so-called event synchronization have been proposed to be powerful tools for disentangling the spatio-temporal organization of particularly extreme rainfall events and anticipating the timing of monsoon onsets or extreme floodings. Rooted in the analysis of spike train synchrony analysis in the neurosciences, event synchronization has the great advantage of automatically classifying pairs of events arising at two distinct spatial locations as temporally close (and, thus, possibly statistically - or even dynamically - interrelated) or not without the necessity of selecting an additional parameter in terms of a maximally tolerable delay between these events. This consideration is conceptually justified in case of the original application to spike trains in electroencephalogram (EEG) recordings, where the inter-spike intervals show relatively narrow distributions at high temporal sampling rates. However, in case of climate studies, precipitation extremes defined by daily precipitation sums exceeding a certain empirical percentile of their local distribution exhibit a distinctively different type of distribution of waiting times between subsequent events. This raises conceptual concerns if event synchronization is still appropriate for detecting interlinkages between spatially distributed precipitation extremes. In order to study this problem in more detail, we employ event synchronization together with an alternative similarity measure for event sequences, event coincidence rates, which requires a manual setting of the tolerable maximum delay between two

  6. Interpolation of Missing Precipitation Data Using Kernel Estimations for Hydrologic Modeling

    Directory of Open Access Journals (Sweden)

    Hyojin Lee

    2015-01-01

    Full Text Available Precipitation is the main factor that drives hydrologic modeling; therefore, missing precipitation data can cause malfunctions in hydrologic modeling. Although interpolation of missing precipitation data is recognized as an important research topic, only a few methods follow a regression approach. In this study, daily precipitation data were interpolated using five different kernel functions, namely, Epanechnikov, Quartic, Triweight, Tricube, and Cosine, to estimate missing precipitation data. This study also presents an assessment that compares estimation of missing precipitation data through Kth nearest neighborhood (KNN regression to the five different kernel estimations and their performance in simulating streamflow using the Soil Water Assessment Tool (SWAT hydrologic model. The results show that the kernel approaches provide higher quality interpolation of precipitation data compared with the KNN regression approach, in terms of both statistical data assessment and hydrologic modeling performance.

  7. Developing Personal Network Business Models

    DEFF Research Database (Denmark)

    Saugstrup, Dan; Henten, Anders

    2006-01-01

    The aim of the paper is to examine the issue of business modeling in relation to personal networks, PNs. The paper builds on research performed on business models in the EU 1ST MAGNET1 project (My personal Adaptive Global NET). The paper presents the Personal Network concept and briefly reports...

  8. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.; Byrne, H.M.; King, J.R.; Bennett, M.J.

    2013-01-01

    methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more

  9. Complex Networks in Psychological Models

    Science.gov (United States)

    Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.

    We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.

  10. A glacier runoff extension to the Precipitation Runoff Modeling System

    Science.gov (United States)

    Van Beusekom, Ashley E.; Viger, Roland

    2016-01-01

    A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while maintaining model usability. PRMSglacier is validated on two basins in Alaska, Wolverine, and Gulkana Glacier basin, which have been studied since 1966 and have a substantial amount of data with which to test model performance over a long period of time covering a wide range of climatic and hydrologic conditions. When error in field measurements is considered, the Nash-Sutcliffe efficiencies of streamflow are 0.87 and 0.86, the absolute bias fractions of the winter mass balance simulations are 0.10 and 0.08, and the absolute bias fractions of the summer mass balances are 0.01 and 0.03, all computed over 42 years for the Wolverine and Gulkana Glacier basins, respectively. Without taking into account measurement error, the values are still within the range achieved by the more computationally expensive codes tested over shorter time periods.

  11. A model of coauthorship networks

    Science.gov (United States)

    Zhou, Guochang; Li, Jianping; Xie, Zonglin

    2017-10-01

    A natural way of representing the coauthorship of authors is to use a generalization of graphs known as hypergraphs. A random geometric hypergraph model is proposed here to model coauthorship networks, which is generated by placing nodes on a region of Euclidean space randomly and uniformly, and connecting some nodes if the nodes satisfy particular geometric conditions. Two kinds of geometric conditions are designed to model the collaboration patterns of academic authorities and basic researches respectively. The conditions give geometric expressions of two causes of coauthorship: the authority and similarity of authors. By simulation and calculus, we show that the forepart of the degree distribution of the network generated by the model is mixture Poissonian, and the tail is power-law, which are similar to these of some coauthorship networks. Further, we show more similarities between the generated network and real coauthorship networks: the distribution of cardinalities of hyperedges, high clustering coefficient, assortativity, and small-world property

  12. Slovenian Network of Isotopes in Precipitation (SLONIP) - a review of activities in the period 1981-2015

    Science.gov (United States)

    Vreča, Polona; Kanduč, Tjaša; Kocman, David; Lojen, Sonja; Štrok, Marko; Robinson, Johanna Amalia

    2017-04-01

    The importance of collecting data on the water isotope composition of precipitation in the frame of the Global Network of Isotopes in Precipitation (GNIP) has been steadily increasing since it was initiated by the IAEA and the WMO in 1958, particularly in the last decade (Terzer et al., 2013). GNIP provides an important database for water resources management, verifying and improving atmospheric circulation models, studying climates and the interactions between water in the atmosphere and the biosphere, providing baseline information for the authentication of commodities, etc. Geographical diversity of Slovenia influences the climate and also the water cycle considerably, therefore monitoring of isotopes in precipitation is of particular interest. A review on monitoring of isotopes in precipitation was performed and information about sampling, analytical methods, available data and their evaluation was collected for the period 1981-2015. The first regular and systematic monitoring began in 1981 in Ljubljana (Pezdič, 1999). Later, a programme of collecting new data at a higher spatial density and temporal frequency in different parts of the country by different research groups has been initiated and was extended several times. Consequently, the number of sampling locations has grown within Slovenian Network of Isotopes in Precipitation (SLONIP) and altogether isotopes were monitored at more than 30 different locations countrywide (Vreča and Malenšek, 2016). However, the network is still not a part of a national monitoring programme, such as that operating in some European countries, for example, in Switzerland (Schürch et al., 2003). Only part of Slovenian data is available in GNIP database. Based on the collected data, we identified gaps in the research and made recommendations for future monitoring in the frame of the SLONIP. The list of main gaps includes limited information about sampling (e.g. missing coordinates, type of collector, period, frequency

  13. Precipitation in Powder Metallurgy, Nickel Base Superalloys: Review of Modeling Approach and Formulation of Engineering (Postprint)

    Science.gov (United States)

    2016-12-01

    AFRL-RX-WP-JA-2016-0333 PRECIPITATION IN POWDER- METALLURGY , NICKEL-BASE SUPERALLOYS: REVIEW OF MODELING APPROACH AND FORMULATION OF...PRECIPITATION IN POWDER- METALLURGY , NICKEL- BASE SUPERALLOYS: REVIEW OF MODELING APPROACH AND FORMULATION OF ENGINEERING (POSTPRINT) 5a...and kinetic parameters required for the modeling of γ′ precipitation in powder- metallurgy (PM), nickel-base superalloys are summarized. These

  14. Improved Regional Climate Model Simulation of Precipitation by a Dynamical Coupling to a Hydrology Model

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Drews, Martin; Hesselbjerg Christensen, Jens

    convective precipitation systems. As a result climate model simulations let alone future projections of precipitation often exhibit substantial biases. Here we show that the dynamical coupling of a regional climate model to a detailed fully distributed hydrological model - including groundwater-, overland...... of local precipitation dynamics are seen for time scales of app. Seasonal duration and longer. We show that these results can be attributed to a more complete treatment of land surface feedbacks. The local scale effect on the atmosphere suggests that coupled high-resolution climate-hydrology models...... including a detailed 3D redistribution of sub- and land surface water have a significant potential for improving climate projections even diminishing the need for bias correction in climate-hydrology studies....

  15. Evaluation of Model Microphysics Within Precipitation Bands of Extratropical Cyclones

    Science.gov (United States)

    Colle, Brian A.; Molthan, Andrew; Yu, Ruyi; Stark, David; Yuter, Sandra; Nesbitt, Steven

    2013-01-01

    Recent studies evaluating the bulk microphysical schemes (BMPs) within cloud resolving models (CRMs) have indicated large uncertainties and errors in the amount and size distributions of snow and cloud ice aloft. The snow prediction is sensitive to the snow densities, habits, and degree of riming within the BMPs. Improving these BMPs is a crucial step toward improving both weather forecasting and climate predictions. Several microphysical schemes in the Weather Research and Forecasting (WRF) model down to 1.33-km grid spacing are evaluated using aircraft, radar, and ground in situ data from the Global Precipitation Mission Coldseason Precipitation Experiment (GCPEx) experiment, as well as a few years (15 winter storms) of surface measurements of riming, crystal habit, snow density, and radar measurements at Stony Brook, NY (SBNY on north shore of Long Island) during the 2009-2012 winter seasons. Surface microphysical measurements at SBNY were taken every 15 to 30 minutes using a stereo microscope and camera, and snow depth and snow density were also recorded. During these storms, a vertically-pointing Ku-band radar was used to observe the vertical evolution of reflectivity and Doppler vertical velocities. A Particle Size and Velocity (PARSIVEL) disdrometer was also used to measure the surface size distribution and fall speeds of snow at SBNY. For the 15 cases at SBNY, the WSM6, Morrison (MORR), Thompson (THOM2), and Stony Brook (SBU-YLIN) BMPs were validated. A non-spherical snow assumption (THOM2 and SBU-YLIN) simulated a more realistic distribution of reflectivity than spherical snow assumptions in the WSM6 and MORR schemes. The MORR, WSM6, and SBU-YLIN schemes are comparable to the observed velocity distribution in light and moderate riming periods. The THOM2 is 0.25 meters per second too slow with its velocity distribution in these periods. In heavier riming, the vertical Doppler velocities in the WSM6, THOM2, and MORR schemes were 0.25 meters per second too

  16. Quantification of the impact of precipitation spatial distribution uncertainty on predictive uncertainty of a snowmelt runoff model

    Science.gov (United States)

    Jacquin, A. P.

    2012-04-01

    This study is intended to quantify the impact of uncertainty about precipitation spatial distribution on predictive uncertainty of a snowmelt runoff model. This problem is especially relevant in mountain catchments with a sparse precipitation observation network and relative short precipitation records. The model analysed is a conceptual watershed model operating at a monthly time step. The model divides the catchment into five elevation zones, where the fifth zone corresponds to the catchment's glaciers. Precipitation amounts at each elevation zone i are estimated as the product between observed precipitation at a station and a precipitation factor FPi. If other precipitation data are not available, these precipitation factors must be adjusted during the calibration process and are thus seen as parameters of the model. In the case of the fifth zone, glaciers are seen as an inexhaustible source of water that melts when the snow cover is depleted.The catchment case study is Aconcagua River at Chacabuquito, located in the Andean region of Central Chile. The model's predictive uncertainty is measured in terms of the output variance of the mean squared error of the Box-Cox transformed discharge, the relative volumetric error, and the weighted average of snow water equivalent in the elevation zones at the end of the simulation period. Sobol's variance decomposition (SVD) method is used for assessing the impact of precipitation spatial distribution, represented by the precipitation factors FPi, on the models' predictive uncertainty. In the SVD method, the first order effect of a parameter (or group of parameters) indicates the fraction of predictive uncertainty that could be reduced if the true value of this parameter (or group) was known. Similarly, the total effect of a parameter (or group) measures the fraction of predictive uncertainty that would remain if the true value of this parameter (or group) was unknown, but all the remaining model parameters could be fixed

  17. Telecommunications network modelling, planning and design

    CERN Document Server

    Evans, Sharon

    2003-01-01

    Telecommunication Network Modelling, Planning and Design addresses sophisticated modelling techniques from the perspective of the communications industry and covers some of the major issues facing telecommunications network engineers and managers today. Topics covered include network planning for transmission systems, modelling of SDH transport network structures and telecommunications network design and performance modelling, as well as network costs and ROI modelling and QoS in 3G networks.

  18. Merging bottom-up and top-down precipitation products using a stochastic error model

    Science.gov (United States)

    Maggioni, Viviana; Massari, Christian; Brocca, Luca; Ciabatta, Luca

    2017-04-01

    operational hydrology. The study, conducted in Italy for a 5-yr period (2010-2014) using a dense network of raingauges (about 3000) as a benchmark, demonstrates that the integration is able to enhance the correlation and the root mean squared error of SM2RAIN+3B42RT with respect to the parent products. This suggests a potential benefit of merging SM2RAIN derived rainfall with state-of-the-art satellite precipitation estimates for creating a product characterized by higher accuracy and better performance when used in the contest of operational hydrology. REFERENCES 1. Brocca, L.; Ciabatta, L.; Massari, C.; Moramarco, T.; Hahn, S.; Hasenauer, S.; Kidd, R.; Dorigo, W.; Wagner, W.; Levizzani, V. Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data. J. Geophys. Res. Atmos. 2014, 119, 5128-5141. 2. Hossain, F.; Anagnostou, E. N. A two-dimensional satellite rainfall error model. IEEE Trans. Geosci. Remote Sens. 2006, 44, 1511-1522.

  19. Projection of future climate change conditions using IPCC simulations, neural networks and Bayesian statistics. Part 2: Precipitation mean state and seasonal cycle in South America

    Energy Technology Data Exchange (ETDEWEB)

    Boulanger, Jean-Philippe [LODYC, UMR CNRS/IRD/UPMC, Tour 45-55/Etage 4/Case 100, UPMC, Paris Cedex 05 (France); University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Martinez, Fernando; Segura, Enrique C. [University of Buenos Aires, Departamento de Computacion, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina)

    2007-02-15

    Evaluating the response of climate to greenhouse gas forcing is a major objective of the climate community, and the use of large ensemble of simulations is considered as a significant step toward that goal. The present paper thus discusses a new methodology based on neural network to mix ensemble of climate model simulations. Our analysis consists of one simulation of seven Atmosphere-Ocean Global Climate Models, which participated in the IPCC Project and provided at least one simulation for the twentieth century (20c3m) and one simulation for each of three SRES scenarios: A2, A1B and B1. Our statistical method based on neural networks and Bayesian statistics computes a transfer function between models and observations. Such a transfer function was then used to project future conditions and to derive what we would call the optimal ensemble combination for twenty-first century climate change projections. Our approach is therefore based on one statement and one hypothesis. The statement is that an optimal ensemble projection should be built by giving larger weights to models, which have more skill in representing present climate conditions. The hypothesis is that our method based on neural network is actually weighting the models that way. While the statement is actually an open question, which answer may vary according to the region or climate signal under study, our results demonstrate that the neural network approach indeed allows to weighting models according to their skills. As such, our method is an improvement of existing Bayesian methods developed to mix ensembles of simulations. However, the general low skill of climate models in simulating precipitation mean climatology implies that the final projection maps (whatever the method used to compute them) may significantly change in the future as models improve. Therefore, the projection results for late twenty-first century conditions are presented as possible projections based on the &apos

  20. MAP3S Precipitation Chemistry Network: second periodic summary report, July 1977--June 1978

    Energy Technology Data Exchange (ETDEWEB)

    1979-01-01

    The MAP3S Precipitation Chemistry Network consists of eight sites located in the northeastern United States. Precipitation event samples are collected by cooperating site operators, using specially developed sampling equipment. The concentration data collected over the period July 1, 1977 to July 1, 1978, are listed as a summary of the data reported monthly throughout the year. Samples were chemically analyzed at a central laboratory for 13 pollutant species - pH, conductivity, SO/sub 2/, SO/sub 4//sup =/, NH/sub 4//sup +/, NO/sub 2//sup -/, NO/sub 3//sup -/, Cl/sup -/, PO/sub 4//sup 3 -/, Na/sup +/, K/sup +/, Ca/sup + +/, and Mg/sup + +/ - using ion chromatography, automated wet chemistry, atomic absorption spectrophotometry, and electrode techniques. Second-year developments included: the installation of refrigeration equipment in all Battelle collectors; the initiation of an externally administered quality control program; and use of ion chromatography for cation as well as anion species. Supplementary research efforts included a special collector comparison study at the Pennsylvania State site and further analysis of sulfite versus sulfate deposition.

  1. Consultants' meeting on operational aspects of the global network ''isotopes in precipitation''

    International Nuclear Information System (INIS)

    1995-01-01

    The Consultant's meeting on ''Operational Aspects of the Global Network - Isotopes in Precipitation'' was organized by the International Atomic Energy Agency (IAEA) in co-operation with the World Meteorological Organization (WMO), the Past Global Changes Project (PAGES) of the International Geosphere-Biosphere Programme (IGBP), the World Health Organization (WHO) and the International Association of Hydrological Sciences (IAHS). It was agreed to transfer the responsibility of running the GNIP and the collection of isotope data in precipitation to a Steering Committee, which will consist of representatives of the following organizations: IAEA, WMO, IGBP-PAGES, WHO, UNESCO and IAHS. The responsibilities of the International Atomic Energy Agency (IAEA) in the Steering Committee are as follows: Co-ordination of the sample analysis: Arrangements for and participation in the measuring programme. Monitoring analytical aspects of sample collection, storage, etc. Arrangements for interlaboratory comparison exercises; collection of isotope and meteorological data, maintenance of the GNIP database and data distribution to interested users; promotion of full use and wider application of GNIP data in practical hydrological applications. Figs, tabs

  2. Dynamic Modelling and Identification of Precipitation Reactions in Full-Scale WWTP

    DEFF Research Database (Denmark)

    Mbamba, Christian Kazadi; Tait, Stephan; Flores-Alsina, Xavier

    , this paper evaluates plant-wide modelling of precipitation reactions using a generic approach integrated within activated sludge and anaerobic models. Preliminary results of anaerobic digester sludge in batch system suggest that the model is able to simulate the dynamics of precipitation reactions. Kinetic...

  3. Refinement of the daily precipitation simulated by the CMIP5 models over the north of the Northeast of Brazil

    Directory of Open Access Journals (Sweden)

    Gyrlene Aparecida Mendes da Silva

    2015-04-01

    Full Text Available The ability of the Artificial Neural Network (ANN and the Multiple Linear Regression (MLR in reproducing the area-average observed daily precipitation during the rainy season (Feb-Mar-Apr over the north of the Northeast of Brazil (NEB is examined. For the present climate of Dec-Jan-Feb from 1963 to 2003 period these statistical models are developed and validated using the observed daily precipitation and simulated from the historical outputs of 4 models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5. The simulations from all the models during DJF and FMA seasons show an anomalous intensification of the ITCZ and southward displacement in comparison with the climatology. Correlations of 0.54, 0.66 and 0.66 are found between the simulated daily precipitation of the CCSM4, GFDL_ESM2M and MIROC_ESM models during DJF season and the observed values during FMA season. Only the CCSM4 model displays a slightly reasonable agreement with the observations. A comparison between the statistical downscaling using the nonlinear (ANN and linear model (MLR to identify the one most suitable for the analysis of daily precipitation was made. The ANN technique provides more ability to predict the present climate when compared to MLR technique. Based on this result, we examined the accuracy of the ANN model in project the changes for the future climate period from 2055 to 2095 over the same study region. For instance, a comparison between the daily precipitation changes projected indirectly from the ANN during Feb-Mar-Apr with those projected directly from the CMIP5 models forced by RCP 8.5 scenario is made. The results suggest that ANN model weights the CMIP5 projections according to the each model ability in simulating the present climate (and its variability. In others, the ANN model is a potentially promising approach to use as a complementary tool to improvement of the seasonal numerical simulations.

  4. Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

    Science.gov (United States)

    Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan

    2017-10-01

    Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.

  5. Campus network security model study

    Science.gov (United States)

    Zhang, Yong-ku; Song, Li-ren

    2011-12-01

    Campus network security is growing importance, Design a very effective defense hacker attacks, viruses, data theft, and internal defense system, is the focus of the study in this paper. This paper compared the firewall; IDS based on the integrated, then design of a campus network security model, and detail the specific implementation principle.

  6. Improved hydrological modeling for remote regions using a combination of observed and simulated precipitation data

    DEFF Research Database (Denmark)

    van der Linden, Sandra; Christensen, Jens Hesselbjerg

    2003-01-01

    -resolution regional climate model (HIRHAM4) with a mean-field bias correction using observed precipitation. A hydrological model (USAFLOW) was applied to simulate runoff using observed precipitation and a combination of observed and simulated precipitation as input. The method was illustrated for the remote Usa basin......, situated in the European part of Arctic Russia, close to the Ural Mountains. It was shown that runoff simulations agree better with observations when the combined precipitation data set was used than when only observed precipitation was used. This appeared to be because the HIRHAM4 model data compensated...... for the absence of observed data from mountainous areas where precipitation is orographically enhanced. In both cases, the runoff simulated by USAFLOW was superior to the runoff simulated within the HIRHAM4 model itself. This was attributed to the rather simplistic description of the water balance in the HIRHAM4...

  7. Links between meteorological conditions and spatial/temporal variations in long-term isotope records from the Austrian precipitation network

    International Nuclear Information System (INIS)

    Kaiser, A.; Scheifinger, H.; Kralik, M.; Papesch, W.; Rank, D.; Stichler, W.

    2002-01-01

    The isotope records from the Austrian Network for Isotopes in Precipitation (ANIP) show significant but not uniform long-term trends. While the 10-year running means of some mountain stations exhibit a pronounced increase in δ 18 O of about 1 per mille since 1975, the change of δ 18 O at the valley stations is much lower. There are also differences in the time behaviour. The differences in the δ 18 O-values of sampling stations at similar altitudes can be explained by different origins of the air moisture (Atlantic or Mediterranean influence). Furthermore, a significant difference in the behaviour of the deuterium excess at neighbouring mountain and valley stations has been observed. There is a slight increase of the yearly mean of the deuterium excess with increasing altitude of the sampling station. But moreover, the seasonal pattern of the deuterium excess is quite different. While the valley stations exhibit the expected minimum in summer, the mountain stations show a distinct maximum between June and October. As a first step into a comprehensive analysis of the meteorological effects on the isotope patterns, the role of advection of different air masses is studied by trajectory statistics. Back trajectories, based on the three dimensional wind fields of the ECMWF model, are calculated for each hour within each precipitation event. Thus, the frequency of the origin of air masses and their contribution to the isotope patterns of the monthly precipitation samples are studied for two selected mountain stations north and south of the main ridge of the Alps. (author)

  8. Characterizing 3-D flow velocity in evolving pore networks driven by CaCO3 precipitation and dissolution

    Science.gov (United States)

    Chojnicki, K. N.; Yoon, H.; Martinez, M. J.

    2015-12-01

    Understanding reactive flow in geomaterials is important for optimizing geologic carbon storage practices, such as using pore space efficiently. Flow paths can be complex in large degrees of geologic heterogeneities across scales. In addition, local heterogeneity can evolve as reactive transport processes alter the pore-scale morphology. For example, dissolved carbon dioxide may react with minerals in fractured rocks, confined aquifers, or faults, resulting in heterogeneous cementation (and/or dissolution) and evolving flow conditions. Both path and flow complexities are important and poorly characterized, making it difficult to determine their evolution with traditional 2-D transport models. Here we characterize the development of 3-D pore-scale flow with an evolving pore configuration due to calcium carbonate (CaCO3) precipitation and dissolution. A simple pattern of a microfluidic pore network is used initially and pore structures will become more complex due to precipitation and dissolution processes. At several stages of precipitation and dissolution, we directly visualize 3-D velocity vectors using micro particle image velocimetry and a laser scanning confocal microscope. Measured 3-D velocity vectors are then compared to 3-D simulated flow fields which will be used to simulate reactive transport. Our findings will highlight the importance of the 3-D flow dynamics and its impact on estimating reactive surface area over time. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. This material is based upon work supported as part of the Center for Frontiers of Subsurface Energy Security, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Award Number DE-SC0001114.

  9. Evaluation of CMIP5 models for projection of future precipitation change in Bornean tropical rainforests

    Science.gov (United States)

    Hussain, Mubasher; Yusof, Khamaruzaman Wan; Mustafa, Muhammad Raza Ul; Mahmood, Rashid; Jia, Shaofeng

    2017-10-01

    We present the climate change impact on the annual and seasonal precipitation over Rajang River Basin (RRB) in Sarawak by employing a set of models from Coupled Model Intercomparison Project Phase 5 (CMIP5). Based on the capability to simulate the historical precipitation, we selected the three most suitable GCMs (i.e. ACCESS1.0, ACCESS1.3, and GFDL-ESM2M) and their mean ensemble (B3MMM) was used to project the future precipitation over the RRB. Historical (1976-2005) and future (2011-2100) precipitation ensembles of B3MMM were used to perturb the stochastically generated future precipitation over 25 rainfall stations in the river basin. The B3MMM exhibited a significant increase in precipitation during 2080s, up to 12 and 8% increase in annual precipitation over upper and lower RRB, respectively, under RCP8.5, and up to 7% increase in annual precipitation under RCP4.5. On the seasonal scale, Mann-Kendal trend test estimated statistically significant positive trend in the future precipitation during all seasons; except September to November when we only noted significant positive trend for the lower RRB under RCP4.5. Overall, at the end of the twenty-first century, an increase in annual precipitation is noteworthy in the whole RRB, with 7 and 10% increase in annual precipitation under the RCP4.5 and the RCP8.5, respectively.

  10. A spatial approach to the modelling and estimation of areal precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Skaugen, T

    1996-12-31

    In hydroelectric power technology it is important that the mean precipitation that falls in an area can be calculated. This doctoral thesis studies how the morphology of rainfall, described by the spatial statistical parameters, can be used to improve interpolation and estimation procedures. It attempts to formulate a theory which includes the relations between the size of the catchment and the size of the precipitation events in the modelling of areal precipitation. The problem of estimating and modelling areal precipitation can be formulated as the problem of estimating an inhomogeneously distributed flux of a certain spatial extent being measured at points in a randomly placed domain. The information contained in the different morphology of precipitation types is used to improve estimation procedures of areal precipitation, by interpolation (kriging) or by constructing areal reduction factors. A new approach to precipitation modelling is introduced where the analysis of the spatial coverage of precipitation at different intensities plays a key role in the formulation of a stochastic model for extreme areal precipitation and in deriving the probability density function of areal precipitation. 127 refs., 30 figs., 13 tabs.

  11. Generalized Network Psychometrics : Combining Network and Latent Variable Models

    NARCIS (Netherlands)

    Epskamp, S.; Rhemtulla, M.; Borsboom, D.

    2017-01-01

    We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between

  12. Neural network modeling of emotion

    Science.gov (United States)

    Levine, Daniel S.

    2007-03-01

    This article reviews the history and development of computational neural network modeling of cognitive and behavioral processes that involve emotion. The exposition starts with models of classical conditioning dating from the early 1970s. Then it proceeds toward models of interactions between emotion and attention. Then models of emotional influences on decision making are reviewed, including some speculative (not and not yet simulated) models of the evolution of decision rules. Through the late 1980s, the neural networks developed to model emotional processes were mainly embodiments of significant functional principles motivated by psychological data. In the last two decades, network models of these processes have become much more detailed in their incorporation of known physiological properties of specific brain regions, while preserving many of the psychological principles from the earlier models. Most network models of emotional processes so far have dealt with positive and negative emotion in general, rather than specific emotions such as fear, joy, sadness, and anger. But a later section of this article reviews a few models relevant to specific emotions: one family of models of auditory fear conditioning in rats, and one model of induced pleasure enhancing creativity in humans. Then models of emotional disorders are reviewed. The article concludes with philosophical statements about the essential contributions of emotion to intelligent behavior and the importance of quantitative theories and models to the interdisciplinary enterprise of understanding the interactions of emotion, cognition, and behavior.

  13. Modeling of fluctuating reaction networks

    International Nuclear Information System (INIS)

    Lipshtat, A.; Biham, O.

    2004-01-01

    Full Text:Various dynamical systems are organized as reaction networks, where the population size of one component affects the populations of all its neighbors. Such networks can be found in interstellar surface chemistry, cell biology, thin film growth and other systems. I cases where the populations of reactive species are large, the network can be modeled by rate equations which provide all reaction rates within mean field approximation. However, in small systems that are partitioned into sub-micron size, these populations strongly fluctuate. Under these conditions rate equations fail and the master equation is needed for modeling these reactions. However, the number of equations in the master equation grows exponentially with the number of reactive species, severely limiting its feasibility for complex networks. Here we present a method which dramatically reduces the number of equations, thus enabling the incorporation of the master equation in complex reaction networks. The method is examplified in the context of reaction network on dust grains. Its applicability for genetic networks will be discussed. 1. Efficient simulations of gas-grain chemistry in interstellar clouds. Azi Lipshtat and Ofer Biham, Phys. Rev. Lett. 93 (2004), 170601. 2. Modeling of negative autoregulated genetic networks in single cells. Azi Lipshtat, Hagai B. Perets, Nathalie Q. Balaban and Ofer Biham, Gene: evolutionary genomics (2004), In press

  14. Changes in precipitation extremes projected by a 20-km mesh global atmospheric model

    Directory of Open Access Journals (Sweden)

    Akio Kitoh

    2016-03-01

    Full Text Available High-resolution modeling is necessary to project weather and climate extremes and their future changes under global warming. A global high-resolution atmospheric general circulation model with grid size about 20 km is able to reproduce climate fields as well as regional-scale phenomena such as monsoonal rainfall, tropical and extratropical cyclones, and heavy precipitation. This 20-km mesh model is applied to project future changes in weather and climate extremes at the end of the 21st century with four different spatial patterns in sea surface temperature (SST changes: one with the mean SST changes by the 28 models of the Coupled Model Intercomparison Project Phase 5 (CMIP5 under the Representative Concentration Pathways (RCP-8.5 scenario, and the other three obtained from a cluster analysis, in which tropical SST anomalies derived from the 28 CMIP5 models were grouped. Here we focus on future changes in regional precipitation and its extremes. Various precipitation indices averaged over the Twenty-two regional land domains are calculated. Heavy precipitation indices (maximum 5-day precipitation total and maximum 1-day precipitation total increase in all regional domains, even where mean precipitation decrease (Southern Africa, South Europe/Mediterranean, Central America. South Asia is the domain of the largest extreme precipitation increase. In some domains, different SST patterns result in large precipitation changes, possibly related to changes in large-scale circulations in the tropical Pacific.

  15. MODELING OF STRAIN-INDUCED PRECIPITATION KINETICS IN Nb MICROALLOYED STEELS

    Institute of Scientific and Technical Information of China (English)

    X.G. Zhou; Z.Y. Liu; D. Wu; Z.Li; C.M. Li

    2006-01-01

    On the basis of the thermodynamic calculation of precipitation and considering the effect of strain on the precipitation behavior and chemical composition (Si and Mn), the kinetics of precipitation from austenite has been investigated for different temperatures and strains. Nucleation theory and the solubility product of niobium, carbon, and nitrogen in austenite have been used to derive equations for the start time of precipitation as a function of temperature and composition. The value of n in Avrami equation was determined using the available experimental data from the published reports, which indicated that n is a constant independent of temperature and the end time of precipitation is a function of n and the start time of precipitation. The values of the start time and end time of precipitation predicted by the new model are compared with the experimental values and a good agreement was obtained between both.

  16. The global historical climatology network: Long-term monthly temperature, precipitation, and pressure data

    International Nuclear Information System (INIS)

    Vose, R.S.; Schmoyer, R.L.; Peterson, T.C.; Steurer, P.M.; Heim, R.R. Jr.; Karl, T.R.; Eischeid, J.K.

    1992-01-01

    Interest in global climate change has risen dramatically during the past several decades. In a similar fashion, the number of data sets available to study global change has also increased. Unfortunately, many different organizations and researchers have compiled these data sets, making it confusing and time consuming for individuals to acquire the most comprehensive data. In response to this rapid growth in the number of global data sets, DOE's Carbon Dioxide Information Analysis Center (CDIAC) and NOAA's National Climatic Data Center (NCDC) established the Global Historical Climatology Network (GHCN) project. The purpose of this project is to compile an improved data set of long-term monthly mean temperature, precipitation, sea level pressure, and station pressure for as dense a network of global stations as possible. Specifically, the GHCN project seeks to consolidate the numerous preexisting national-, regional-, and global-scale data sets into a single global data base; to subject the data to rigorous quality control; and to update, enhance, and distribute the data set at regular intervals. The purpose of this paper is to describe the compilation and contents of the GHCN data base (i.e., GHCN Version 1.0)

  17. United States Historical Climatology Network (US HCN) monthly temperature and precipitation data

    Energy Technology Data Exchange (ETDEWEB)

    Daniels, R.C. [ed.] [Univ. of Tennessee, Knoxville, TN (United States). Energy, Environment and Resources Center; Boden, T.A. [ed.] [Oak Ridge National Lab., TN (United States); Easterling, D.R.; Karl, T.R.; Mason, E.H.; Hughes, P.Y.; Bowman, D.P. [National Climatic Data Center, Asheville, NC (United States)

    1996-01-11

    This document describes a database containing monthly temperature and precipitation data for 1221 stations in the contiguous United States. This network of stations, known as the United States Historical Climatology Network (US HCN), and the resulting database were compiled by the National Climatic Data Center, Asheville, North Carolina. These data represent the best available data from the United States for analyzing long-term climate trends on a regional scale. The data for most stations extend through December 31, 1994, and a majority of the station records are serially complete for at least 80 years. Unlike many data sets that have been used in past climate studies, these data have been adjusted to remove biases introduced by station moves, instrument changes, time-of-observation differences, and urbanization effects. These monthly data are available free of charge as a numeric data package (NDP) from the Carbon Dioxide Information Analysis Center. The NDP includes this document and 27 machine-readable data files consisting of supporting data files, a descriptive file, and computer access codes. This document describes how the stations in the US HCN were selected and how the data were processed, defines limitations and restrictions of the data, describes the format and contents of the magnetic media, and provides reprints of literature that discuss the editing and adjustment techniques used in the US HCN.

  18. Modelling and on-line estimation of zinc sulphide precipitation in

    NARCIS (Netherlands)

    Grootscholten, T.I.M.; Keesman, K.J.; Lens, P.N.L.

    2008-01-01

    In this paper the ZnS precipitation in a continuously stirred tank reactor (CSTR) is modelled using mass balances. The dynamics analysis of the model reveals that the ZnS precipitation shows a two time-scales behaviour with inherent numerical stability problems, which therefore needs special

  19. Modeling precipitation-runoff relationships to determine water yield from a ponderosa pine forest watershed

    Science.gov (United States)

    Assefa S. Desta

    2006-01-01

    A stochastic precipitation-runoff modeling is used to estimate a cold and warm-seasons water yield from a ponderosa pine forested watershed in the north-central Arizona. The model consists of two parts namely, simulation of the temporal and spatial distribution of precipitation using a stochastic, event-based approach and estimation of water yield from the watershed...

  20. Negative corona discharges modelling. Application to the electrostatic precipitation

    International Nuclear Information System (INIS)

    Gaychet, S.

    2010-01-01

    Electrostatic precipitation presents many advantages from the nuclear wastes treatment's point of view. Indeed, this kind of process can capture submicron particles without producing secondary wastes (no filter media) and without pressure looses in the exhaust circuit. The work presented in this thesis concerns the study of negative corona discharges in air at atmospheric pressure occurring in an electrostatic precipitator (ESP) developed by the CEA (Atomic Energy Committee). The aim of this study is to determine how the electrostatic precipitation dedicated phenomena, especially the specific high voltage generator, the gas temperature and the fact that particles are flowing through the gap then collapsing on the electrodes, modify the discharge to improve the efficiency of ESPs. This work is based on a fundamental experimental study of the negative corona discharge and on numerical simulations of this discharge under conditions close to those of the lab scale ESP developed by the CEA. (author) [fr

  1. Effect of tropospheric models on derived precipitable water vapor over Southeast Asia

    Science.gov (United States)

    Rahimi, Zhoobin; Mohd Shafri, Helmi Zulhaidi; Othman, Faridah; Norman, Masayu

    2017-05-01

    An interesting subject in the field of GPS technology is estimating variation of precipitable water vapor (PWV). This estimation can be used as a data source to assess and monitor rapid changes in meteorological conditions. So far, numerous GPS stations are distributed across the world and the number of GPS networks is increasing. Despite these developments, a challenging aspect of estimating PWV through GPS networks is the need of tropospheric parameters such as temperature, pressure, and relative humidity (Liu et al., 2015). To estimate the tropospheric parameters, global pressure temperature (GPT) model developed by Boehm et al. (2007) is widely used in geodetic analysis for GPS observations. To improve the accuracy, Lagler et al. (2013) introduced GPT2 model by adding annual and semi-annual variation effects to GPT model. Furthermore, Boehm et al. (2015) proposed the GPT2 wet (GPT2w) model which uses water vapor pressure to improve the calculations. The global accuracy of GPT2 and GPT2w models has been evaluated by previous researches (Fund et al., 2011; Munekane and Boehm, 2010); however, investigations to assess the accuracy of global tropospheric models in tropical regions such as Southeast Asia is not sufficient. This study tests and examines the accuracy of GPT2w as one of the most recent versions of tropospheric models (Boehm et al., 2015). We developed a new regional model called Malaysian Pressure Temperature (MPT) model, and compared this model with GPT2w model. The compared results at one international GNSS service (IGS) station located in the south of Peninsula Malaysia shows that MPT model has a better performance than GPT2w model to produce PWV during monsoon season. According to the results, MPT has improved the accuracy of estimated pressure and temperature by 30% and 10%, respectively, in comparison with GPT2w model. These results indicate that MPT model can be a good alternative tool in the absence of meteorological sensors at GPS stations in

  2. Geographic patterns of networks derived from extreme precipitation over the Indian subcontinent

    Science.gov (United States)

    Stolbova, Veronika; Bookhagen, Bodo; Marwan, Norbert; Kurths, Juergen

    2014-05-01

    Complex networks (CN) and event synchronization (ES) methods have been applied to study a number of climate phenomena such as Indian Summer Monsoon (ISM), South-American Monsoon, and African Monsoon. These methods proved to be powerful tools to infer interdependencies in climate dynamics between geographical sites, spatial structures, and key regions of the considered climate phenomenon. Here, we use these methods to study the spatial temporal variability of the extreme rainfall over the Indian subcontinent, in order to filter the data by coarse-graining the network, and to identify geographic patterns that are signature features (spatial signatures) of the ISM. We find four main geographic patterns of networks derived from extreme precipitation over the Indian subcontinent using up-to-date satellite-derived, and high temporal and spatial resolution rain-gauge interpolated daily rainfall datasets. In order to prove that our results are also relevant for other climatic variables like pressure and temperature, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). We find that two of the patterns revealed from the CN extreme rainfall analysis coincide with those obtained for the pressure and temperature fields, and all four above mentioned patterns can be explained by topography, winds, and monsoon circulation. CN and ES enable to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to infer geographic pattern that are spatial signatures of the ISM. These patterns deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

  3. Impact of precipitation spatial resolution on the hydrological response of an integrated distributed water resources model

    DEFF Research Database (Denmark)

    Fu, Suhua; Sonnenborg, Torben; Jensen, Karsten Høgh

    2011-01-01

    Precipitation is a key input variable to hydrological models, and the spatial variability of the input is expected to impact the hydrological response predicted by a distributed model. In this study, the effect of spatial resolution of precipitation on runoff , recharge and groundwater head...... of the total catchment and runoff discharge hydrograph at watershed outlet. On the other hand, groundwater recharge and groundwater head were both aff ected. The impact of the spatial resolution of precipitation input is reduced with increasing catchment size. The effect on stream discharge is relatively low...... was analyzed in the Alergaarde catchment in Denmark. Six different precipitation spatial resolutions were used as inputs to a physically based, distributed hydrological model, the MIKE SHE model. The results showed that the resolution of precipitation input had no apparent effect on annual water balance...

  4. Network model of security system

    Directory of Open Access Journals (Sweden)

    Adamczyk Piotr

    2016-01-01

    Full Text Available The article presents the concept of building a network security model and its application in the process of risk analysis. It indicates the possibility of a new definition of the role of the network models in the safety analysis. Special attention was paid to the development of the use of an algorithm describing the process of identifying the assets, vulnerability and threats in a given context. The aim of the article is to present how this algorithm reduced the complexity of the problem by eliminating from the base model these components that have no links with others component and as a result and it was possible to build a real network model corresponding to reality.

  5. Modeled Watershed Runoff Associated with Variations in Precipitation Data with Implications for Contaminant Fluxes

    Science.gov (United States)

    Watershed-scale fate and transport models are important tools for estimating the sources, transformation, and transport of contaminants to surface water systems. Precipitation is one of the primary inputs to watershed biogeochemical models, influencing changes in the water budge...

  6. Current approaches to gene regulatory network modelling

    Directory of Open Access Journals (Sweden)

    Brazma Alvis

    2007-09-01

    Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

  7. Quantitative precipitation climatology over the Himalayas by using Precipitation Radar on Tropical Rainfall Measuring Mission (TRMM) and a dense network of rain-gauges

    Science.gov (United States)

    Yatagai, A.

    2010-09-01

    Quantified grid observation data at a reasonable resolution are indispensable for environmental monitoring as well as for predicting future change of mountain environment. However quantified datasets have not been available for the Himalayan region. Hence we evaluate climatological precipitation data around the Himalayas by using Precipitation Radar (PR) data acquired by the Tropical Rainfall Measuring Mission (TRMM) over 10 years of observation. To validate and adjust these patterns, we used a dense network of rain gauges collected by the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE Water Resources) project (http://www.chikyu.ac.jp/precip/). We used more than 2600 stations which have more than 10-year monthly precipitation over the Himalayan region (75E-105E, 20-36N) including country data of Nepal, Bangladesh, Bhutan, Pakistan, India, Myanmar, and China. The region we studied is so topographically complicated that horizontal patterns are not uniform. Therefore, every path data of PR2A25 (near-surface rain) was averaged in a 0.05-degree grid and a 10-year monthly average was computed (hereafter we call PR). On the other hand, for rain-gauge, we first computed cell averages if each 0.05-degree grid cell has 10 years observation or more. Here we refer to the 0.05-degree rain-gauge climatology data as RG data. On the basis of comparisons between the RG and PR composite values, we defined the parameters of the regressions to correct the monthly climatology value based on the rain gauge observations. Compared with the RG, the PR systematically underestimated precipitation by 28-38% in summer (July-September). Significant correlation between TRMM/PR and rain-gauge data was found for all months, but the correlation is relatively low in winter. The relationship is investigated for different elevation zones, and the PR was found to underestimate RG data in most zones, except for certain zones in

  8. A model for the formation of lattice defects at silicon oxide precipitates in silicon

    International Nuclear Information System (INIS)

    Vanhellemont, J.; Gryse, O. de; Clauws, P.

    2003-01-01

    The critical size of silicon oxide precipitates and the formation of lattice defects by the precipitates are discussed. An expression is derived allowing estimation of self-interstitial emission by spherical precipitates as well as strain build-up during precipitate growth. The predictions are compared with published experimental data. A model for stacking fault nucleation at oxide precipitates is developed based on strain and self-interstitial accumulation during the thermal history of the wafer. During a low-temperature treatment high levels of strain develop. During subsequent high-temperature treatment, excess strain energy in the precipitate is released by self-interstitial emission leading to favourable conditions for stacking fault nucleation

  9. Evaluation of precipitation extremes over the Asian domain: observation and modelling studies

    Science.gov (United States)

    Kim, In-Won; Oh, Jaiho; Woo, Sumin; Kripalani, R. H.

    2018-04-01

    In this study, a comparison in the precipitation extremes as exhibited by the seven reference datasets is made to ascertain whether the inferences based on these datasets agree or they differ. These seven datasets, roughly grouped in three categories i.e. rain-gauge based (APHRODITE, CPC-UNI), satellite-based (TRMM, GPCP1DD) and reanalysis based (ERA-Interim, MERRA, and JRA55), having a common data period 1998-2007 are considered. Focus is to examine precipitation extremes in the summer monsoon rainfall over South Asia, East Asia and Southeast Asia. Measures of extreme precipitation include the percentile thresholds, frequency of extreme precipitation events and other quantities. Results reveal that the differences in displaying extremes among the datasets are small over South Asia and East Asia but large differences among the datasets are displayed over the Southeast Asian region including the maritime continent. Furthermore, precipitation data appear to be more consistent over East Asia among the seven datasets. Decadal trends in extreme precipitation are consistent with known results over South and East Asia. No trends in extreme precipitation events are exhibited over Southeast Asia. Outputs of the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulation data are categorized as high, medium and low-resolution models. The regions displaying maximum intensity of extreme precipitation appear to be dependent on model resolution. High-resolution models simulate maximum intensity of extreme precipitation over the Indian sub-continent, medium-resolution models over northeast India and South China and the low-resolution models over Bangladesh, Myanmar and Thailand. In summary, there are differences in displaying extreme precipitation statistics among the seven datasets considered here and among the 29 CMIP5 model data outputs.

  10. A new model for prediction of dispersoid precipitation in aluminium alloys containing zirconium and scandium

    International Nuclear Information System (INIS)

    Robson, J.D.

    2004-01-01

    A model has been developed to predict precipitation of ternary Al 3 (Sc, Zr) dispersoids in aluminium alloys containing zirconium and scandium. The model is based on the classical numerical method of Kampmann and Wagner, extended to predict precipitation of a ternary phase. The model has been applied to the precipitation of dispersoids in scandium containing AA7050. The dispersoid precipitation kinetics and number density are predicted to be sensitive to the scandium concentration, whilst the dispersoid radius is not. The dispersoids are predicted to enrich in zirconium during precipitation. Coarsening has been investigated in detail and it has been predicted that a steady-state size distribution is only reached once coarsening is well advanced. The addition of scandium is predicted to eliminate the dispersoid free zones observed in scandium free 7050, greatly increasing recrystallization resistance

  11. Impact of time displaced precipitation estimates for on-line updated models

    DEFF Research Database (Denmark)

    Borup, Morten; Grum, Morten; Mikkelsen, Peter Steen

    2012-01-01

    When an online runoff model is updated from system measurements the requirements to the precipitation estimates change. Using rain gauge data as precipitation input there will be a displacement between the time where the rain intensity hits the gauge and the time where the rain hits the actual...

  12. Comparing the impact of time displaced and biased precipitation estimates for online updated urban runoff models

    DEFF Research Database (Denmark)

    Borup, Morten; Mikkelsen, Peter Steen; Borup, Morten

    2013-01-01

    When an online runoff model is updated from system measurements, the requirements of the precipitation input change. Using rain gauge data as precipitation input there will be a displacement between the time when the rain hits the gauge and the time where the rain hits the actual catchment, due...

  13. Target-Centric Network Modeling

    DEFF Research Database (Denmark)

    Mitchell, Dr. William L.; Clark, Dr. Robert M.

    In Target-Centric Network Modeling: Case Studies in Analyzing Complex Intelligence Issues, authors Robert Clark and William Mitchell take an entirely new approach to teaching intelligence analysis. Unlike any other book on the market, it offers case study scenarios using actual intelligence...... reporting formats, along with a tested process that facilitates the production of a wide range of analytical products for civilian, military, and hybrid intelligence environments. Readers will learn how to perform the specific actions of problem definition modeling, target network modeling......, and collaborative sharing in the process of creating a high-quality, actionable intelligence product. The case studies reflect the complexity of twenty-first century intelligence issues by dealing with multi-layered target networks that cut across political, economic, social, technological, and military issues...

  14. CMIP5 model simulations of Ethiopian Kiremt-season precipitation: current climate and future changes

    Science.gov (United States)

    Li, Laifang; Li, Wenhong; Ballard, Tristan; Sun, Ge; Jeuland, Marc

    2016-05-01

    Kiremt-season (June-September) precipitation provides a significant water supply for Ethiopia, particularly in the central and northern regions. The response of Kiremt-season precipitation to climate change is thus of great concern to water resource managers. However, the complex processes that control Kiremt-season precipitation challenge the capability of general circulation models (GCMs) to accurately simulate precipitation amount and variability. This in turn raises questions about their utility for predicting future changes. This study assesses the impact of climate change on Kiremt-season precipitation using state-of-the-art GCMs participating in the Coupled Model Intercomparison Project Phase 5. Compared to models with a coarse resolution, high-resolution models (horizontal resolution <2°) can more accurately simulate precipitation, most likely due to their ability to capture precipitation induced by topography. Under the Representative Concentration Pathway (RCP) 4.5 scenario, these high-resolution models project an increase in precipitation over central Highlands and northern Great Rift Valley in Ethiopia, but a decrease in precipitation over the southern part of the country. Such a dipole pattern is attributable to the intensification of the North Atlantic subtropical high (NASH) in a warmer climate, which influences Ethiopian Kiremt-season precipitation mainly by modulating atmospheric vertical motion. Diagnosis of the omega equation demonstrates that an intensified NASH increases (decreases) the advection of warm air and positive vorticity into the central Highlands and northern Great Rift Valley (southern part of the country), enhancing upward motion over the northern Rift Valley but decreasing elsewhere. Under the RCP 4.5 scenario, the high-resolution models project an intensification of the NASH by 15 (3 × 105 m2 s-2) geopotential meters (stream function) at the 850-hPa level, contributing to the projected precipitation change over Ethiopia. The

  15. A systematic study of multiple minerals precipitation modelling in wastewater treatment.

    Science.gov (United States)

    Kazadi Mbamba, Christian; Tait, Stephan; Flores-Alsina, Xavier; Batstone, Damien J

    2015-11-15

    Mineral solids precipitation is important in wastewater treatment. However approaches to minerals precipitation modelling are varied, often empirical, and mostly focused on single precipitate classes. A common approach, applicable to multi-species precipitates, is needed to integrate into existing wastewater treatment models. The present study systematically tested a semi-mechanistic modelling approach, using various experimental platforms with multiple minerals precipitation. Experiments included dynamic titration with addition of sodium hydroxide to synthetic wastewater, and aeration to progressively increase pH and induce precipitation in real piggery digestate and sewage sludge digestate. The model approach consisted of an equilibrium part for aqueous phase reactions and a kinetic part for minerals precipitation. The model was fitted to dissolved calcium, magnesium, total inorganic carbon and phosphate. Results indicated that precipitation was dominated by the mineral struvite, forming together with varied and minor amounts of calcium phosphate and calcium carbonate. The model approach was noted to have the advantage of requiring a minimal number of fitted parameters, so the model was readily identifiable. Kinetic rate coefficients, which were statistically fitted, were generally in the range 0.35-11.6 h(-1) with confidence intervals of 10-80% relative. Confidence regions for the kinetic rate coefficients were often asymmetric with model-data residuals increasing more gradually with larger coefficient values. This suggests that a large kinetic coefficient could be used when actual measured data is lacking for a particular precipitate-matrix combination. Correlation between the kinetic rate coefficients of different minerals was low, indicating that parameter values for individual minerals could be independently fitted (keeping all other model parameters constant). Implementation was therefore relatively flexible, and would be readily expandable to include other

  16. The Austrian Network of Isotopes in Precipitation and Surface water: more than 50 years applications and interpretations of basic isotope-hydrological data for Central Europe

    Science.gov (United States)

    Wyhlidal, S.; Rank, D.; Kralik, M.

    2017-12-01

    Austria runs one of the longest-standing and most dense isotope precipitation collection networks worldwide, resulting in a unique isotope time series. Stable isotope variations in precipitation are a consequence of isotope effects accompanying each step of the water cycle. Therefore, stable isotope ratios of oxygen (18O/16O) and hydrogen (2H/1H) in precipitation provide important information about the origin and atmospheric transport of water vapour. The separation of a remote moisture source signals from local influences is thereby challenging. The amount of precipitation in Austria is highly influenced by the Alpine mountain range (400-3.000 mm/a). The amount of annual precipitation increases towards the mountain ranges. However, strong regional differences exist between the north and south of the Austrian Alps because the Alpine range functions as weather divide. The isotope time series of the stations of the Austrian precipitation network show significant but not uniform long-term trends. While the 10-year running mean of some mountain stations exhibit a highly significant increase in δ18O of about 1 ‰ since 1975, the change of δ18O at the valley stations is less pronounced. The increasing δ18O values can be correlated to an increase mean air temperature in the Alpine area and can be used as an additional indicator of climate change in this region. The differences in δ18O-values of sampling stations at similar altitudes can be explained by the origin of the air moisture. An Atlantic influence causes lower δ18O-values than sources from the Mediterranean. This can be explained by the different distances to the sea. Deuterium excess is a second-order isotopic parameter which is often interpreted as a tracer of the evaporation conditions of water vapor at the moisture source in terms of relative humidity, wind speed, and sea surface temperature, but can also be modified by local influences, such as below-cloud evaporation and equilibrium fractionation under

  17. Documentation of a daily mean stream temperature module—An enhancement to the Precipitation-Runoff Modeling System

    Science.gov (United States)

    Sanders, Michael J.; Markstrom, Steven L.; Regan, R. Steven; Atkinson, R. Dwight

    2017-09-15

    A module for simulation of daily mean water temperature in a network of stream segments has been developed as an enhancement to the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS). This new module is based on the U.S. Fish and Wildlife Service Stream Network Temperature model, a mechanistic, one-dimensional heat transport model. The new module is integrated in PRMS. Stream-water temperature simulation is activated by selection of the appropriate input flags in the PRMS Control File and by providing the necessary additional inputs in standard PRMS input files.This report includes a comprehensive discussion of the methods relevant to the stream temperature calculations and detailed instructions for model input preparation.

  18. Precipitation model in microalloyed steels both isothermal and continuous cooling conditions

    International Nuclear Information System (INIS)

    Medina, S. F.; Quispe, A.; Gomez, M.

    2015-01-01

    Niobium and vanadium precipitates (nitrides and carbides) can inhibit the static recrystallization of austenite but this does not happen for Ti, which form nitrides at high temperatures. RPTT diagrams show the interaction between recrystallization and precipitation allowing study the strain induced precipitation kinetics and precipitate coarsening. Based on Dutta and Sellars expression for the start of strain-induced precipitation in microalloyed steels, a new model has been constructed which takes into account the influence of variables such as microalloying element percentages, strain, temperature, strain rate and grain size. Recrystallization- Precipitation-Time-Temperature (RPTT) diagrams have been plotted thanks to a new experimental study carried out by means of hot torsion tests on approximately twenty microalloyed steels with different Nb, V and Ti contents. Mathematical analysis of the results recommends the modification of some parameters such as the supersaturation ratio (ks) and constant B, which is no longer a constant but a function of ks. The expressions are now more consistent and predict the Precipitation-Time-Temperature (PTT) curves with remarkable accuracy. The model for strain-induced precipitation kinetics is completed by means of Avramis equation. Finally, the model constructed in isothermal testing conditions, it has been converted to continuous cooling conditions in order to apply it in hot rolling. (Author)

  19. Projected Changes in the Annual Cycle of Precipitation over Central Asia by CMIP5 Models

    Science.gov (United States)

    Yu, X.; Zhao, Y.

    2017-12-01

    Future changes in the annual cycle of the precipitation in central Asia (CA) were estimated based on the historical and Representative Concentration Pathway 8.5 (RCP8.5) experiments from 25 models of the Coupled Model Intercomparison Project phase 5 (CMIP5). Compared with the Global Precipitation Climatology Project (GPCP) observations, the historical (1979-1999) experiments showed that most models can capture the migration of rainfall centers, but remarkable discrepancies exist in the location and intensity of rainfall centers between simulations and observations. Considering the skill scores of precipitation and pattern correlations of circulations, which are closely related to the precipitation for each month, for the 25 models, the four best models (e.g., CanESM2, CMCC-CMS, MIROC5 and MPI-ESM-LR) with relatively good performance were selected. The four models' ensemble mean indicated that the migration and location of the precipitation centers were better reproduced, except the intensity of the centers was overestimated, compared with the result that only considered precipitation. Based on the four best models' ensemble mean under RCP8.5 scenarios, precipitation was projected to increase dramatically over most of the CA region in the boreal cold seasons (November, December, January, February, March, April and May) with the maximum in December in the end of twenty-first century (2079-2099), and several positive centers were located in the Pamirs Plateau and the Tianshan Mountains. By contrast, the precipitation changes were weak in the boreal warm seasons (June, July, August, September and October), with a wet center located in the northern Himalayas. Furthermore, there remain some uncertainties in the projected precipitation regions and periods obtained by comparing models' ensemble results of this paper and the results of previous studies. These uncertainties should be investigated in future work.

  20. Phase Behavior Modeling of Asphaltene Precipitation for Heavy Crudes: A Promising Tool Along with Experimental Data

    Science.gov (United States)

    Tavakkoli, M.; Kharrat, R.; Masihi, M.; Ghazanfari, M. H.; Fadaei, S.

    2012-12-01

    Thermodynamic modeling is known as a promising tool for phase behavior modeling of asphaltene precipitation under different conditions such as pressure depletion and CO2 injection. In this work, a thermodynamic approach is used for modeling the phase behavior of asphaltene precipitation. The precipitated asphaltene phase is represented by an improved solid model, while the oil and gas phases are modeled with an equation of state. The PR-EOS was used to perform flash calculations. Then, the onset point and the amount of precipitated asphaltene were predicted. A computer code based on an improved solid model has been developed and used for predicting asphaltene precipitation data for one of Iranian heavy crudes, under pressure depletion and CO2 injection conditions. A significant improvement has been observed in predicting the asphaltene precipitation data under gas injection conditions. Especially for the maximum value of asphaltene precipitation and for the trend of the curve after the peak point, good agreement was observed. For gas injection conditions, comparison of the thermodynamic micellization model and the improved solid model showed that the thermodynamic micellization model cannot predict the maximum of precipitation as well as the improved solid model. The non-isothermal improved solid model has been used for predicting asphaltene precipitation data under pressure depletion conditions. The pressure depletion tests were done at different levels of temperature and pressure, and the parameters of a non-isothermal model were tuned using three onset pressures at three different temperatures for the considered crude. The results showed that the model is highly sensitive to the amount of solid molar volume along with the interaction coefficient parameter between the asphaltene component and light hydrocarbon components. Using a non-isothermal improved solid model, the asphaltene phase envelope was developed. It has been revealed that at high temperatures, an

  1. The global precipitation response to volcanic eruptions in the CMIP5 models

    International Nuclear Information System (INIS)

    Iles, Carley E; Hegerl, Gabriele C

    2014-01-01

    We examine the precipitation response to volcanic eruptions in the Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations compared to three observational datasets, including one with ocean coverage. Global precipitation decreases significantly following eruptions in CMIP5 models, with the largest decrease in wet tropical regions. This also occurs in observational land data, and ocean data in the boreal cold season. Monsoon rainfall decreases following eruptions in both models and observations. In response to individual eruptions, the ITCZ shifts away from the hemisphere with the greater concentration of aerosols in CMIP5. Models undergo a longer-lasting ocean precipitation response than over land, but the response in the short satellite record is too noisy to confirm this. We detect the influence of volcanism on precipitation in all three datasets in the cold season, although the models underestimate the size of the response. In the warm season the volcanic influence is only marginally detectable. (letter)

  2. Modelling Particulate Removal in Tubular Wet Electrostatic Precipitators Using a Modified Drift Flux Model

    Directory of Open Access Journals (Sweden)

    S Ramechecandane

    2016-09-01

    Full Text Available Tubular electrostatic precipitators (ESP have been used in a number of chemical processing industries. The tubular ESPs have many advantages over conventional plate-plate and wire-plate ESPs. The present study is concerned with the numerical modeling of particulate removal in a tubular wet single-stage electrostatic precipitator (wESP. The geometric parameters of a model wESP and the corresponding inlet gas velocities for the wESP are chosen from available experimental data. In addition to the RNG k - ε model for the mean turbulent flow field inside the wESP, the Poisson equation for the electric field, the charge continuity equation and the concentration equation are solved sequentially to obtain a full-fledged solution to the problem under investigation. The proposed drift flux model is implemented in the opensource CFD code OpenFOAM®. The paper discusses the influence of the number of charges acquired by the particles and the corresponding inlet gas velocities on particle concentration distribution within the wESP. Two representative cases with monodispersed particles of 1 μm and 10 μm diameter are considered for the numerical analysis. It is seen from the present analysis that the number of units of charge on particles, the particle size and the inlet gas velocities play a vital role in determining the efficiency of electrostatic precipitation.

  3. Orographic precipitation at global and regional scales: Observational uncertainty and evaluation of 25-km global model simulations

    Science.gov (United States)

    Schiemann, Reinhard; Roberts, Charles J.; Bush, Stephanie; Demory, Marie-Estelle; Strachan, Jane; Vidale, Pier Luigi; Mizielinski, Matthew S.; Roberts, Malcolm J.

    2015-04-01

    Precipitation over land exhibits a high degree of variability due to the complex interaction of the precipitation generating atmospheric processes with coastlines, the heterogeneous land surface, and orography. Global general circulation models (GCMs) have traditionally had very limited ability to capture this variability on the mesoscale (here ~50-500 km) due to their low resolution. This has changed with recent investments in resolution and ensembles of multidecadal climate simulations of atmospheric GCMs (AGCMs) with ~25 km grid spacing are becoming increasingly available. Here, we evaluate the mesoscale precipitation distribution in one such set of simulations obtained in the UPSCALE (UK on PrACE - weather-resolving Simulations of Climate for globAL Environmental risk) modelling campaign with the HadGEM-GA3 AGCM. Increased model resolution also poses new challenges to the observational datasets used to evaluate models. Global gridded data products such as those provided by the Global Precipitation Climatology Project (GPCP) are invaluable for assessing large-scale features of the precipitation distribution but may not sufficiently resolve mesoscale structures. In the absence of independent estimates, the intercomparison of different observational datasets may be the only way to get some insight into the uncertainties associated with these observations. Here, we focus on mid-latitude continental regions where observations based on higher-density gauge networks are available in addition to the global data sets: Europe/the Alps, South and East Asia, and the continental US. The ability of GCMs to represent mesoscale variability is of interest in its own right, as climate information on this scale is required by impact studies. An additional motivation for the research proposed here arises from continuing efforts to quantify the components of the global radiation budget and water cycle. Recent estimates based on radiation measurements suggest that the global mean

  4. Environmental isotope data no. 10: World survey of isotope concentration in precipitation (1988-1991). Report from a network

    International Nuclear Information System (INIS)

    1994-01-01

    This is the tenth volume of the publication Environmental Isotope Data: World Survey of Isotope Concentration in Precipitation. This volume is primarily concerned with the concentration of the environmental isotopes (tritium, deuterium and oxygen-18) in monthly samples of precipitation taken by a global network of 169 stations in the period 1988 to 1991. Selected meteorological data, such as the amount of precipitation, mean water vapour pressure and surface air temperature, are also presented. Data before 1988 which were unavailable at the time of the earlier issues have also been included in the latter part of this volume as late reports. The data are being widely used in hydrological, hydrometeorological and climatological studies. 9 refs, 2 figs

  5. A comparison of monthly precipitation point estimates at 6 locations in Iran using integration of soft computing methods and GARCH time series model

    Science.gov (United States)

    Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

    2017-11-01

    Precipitation plays an important role in determining the climate of a region. Precise estimation of precipitation is required to manage and plan water resources, as well as other related applications such as hydrology, climatology, meteorology and agriculture. Time series of hydrologic variables such as precipitation are composed of deterministic and stochastic parts. Despite this fact, the stochastic part of the precipitation data is not usually considered in modeling of precipitation process. As an innovation, the present study introduces three new hybrid models by integrating soft computing methods including multivariate adaptive regression splines (MARS), Bayesian networks (BN) and gene expression programming (GEP) with a time series model, namely generalized autoregressive conditional heteroscedasticity (GARCH) for modeling of the monthly precipitation. For this purpose, the deterministic (obtained by soft computing methods) and stochastic (obtained by GARCH time series model) parts are combined with each other. To carry out this research, monthly precipitation data of Babolsar, Bandar Anzali, Gorgan, Ramsar, Tehran and Urmia stations with different climates in Iran were used during the period of 1965-2014. Root mean square error (RMSE), relative root mean square error (RRMSE), mean absolute error (MAE) and determination coefficient (R2) were employed to evaluate the performance of conventional/single MARS, BN and GEP, as well as the proposed MARS-GARCH, BN-GARCH and GEP-GARCH hybrid models. It was found that the proposed novel models are more precise than single MARS, BN and GEP models. Overall, MARS-GARCH and BN-GARCH models yielded better accuracy than GEP-GARCH. The results of the present study confirmed the suitability of proposed methodology for precise modeling of precipitation.

  6. Effect of precipitation spatial distribution uncertainty on the uncertainty bounds of a snowmelt runoff model output

    Science.gov (United States)

    Jacquin, A. P.

    2012-04-01

    This study analyses the effect of precipitation spatial distribution uncertainty on the uncertainty bounds of a snowmelt runoff model's discharge estimates. Prediction uncertainty bounds are derived using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The model analysed is a conceptual watershed model operating at a monthly time step. The model divides the catchment into five elevation zones, where the fifth zone corresponds to the catchment glaciers. Precipitation amounts at each elevation zone i are estimated as the product between observed precipitation (at a single station within the catchment) and a precipitation factor FPi. Thus, these factors provide a simplified representation of the spatial variation of precipitation, specifically the shape of the functional relationship between precipitation and height. In the absence of information about appropriate values of the precipitation factors FPi, these are estimated through standard calibration procedures. The catchment case study is Aconcagua River at Chacabuquito, located in the Andean region of Central Chile. Monte Carlo samples of the model output are obtained by randomly varying the model parameters within their feasible ranges. In the first experiment, the precipitation factors FPi are considered unknown and thus included in the sampling process. The total number of unknown parameters in this case is 16. In the second experiment, precipitation factors FPi are estimated a priori, by means of a long term water balance between observed discharge at the catchment outlet, evapotranspiration estimates and observed precipitation. In this case, the number of unknown parameters reduces to 11. The feasible ranges assigned to the precipitation factors in the first experiment are slightly wider than the range of fixed precipitation factors used in the second experiment. The mean squared error of the Box-Cox transformed discharge during the calibration period is used for the evaluation of the

  7. Multivariate autoregressive modelling and conditional simulation of precipitation time series for urban water models

    NARCIS (Netherlands)

    Torres-Matallana, J.A.; Leopold, U.; Heuvelink, G.B.M.

    2017-01-01

    Precipitation is the most active flux and major input of hydrological systems. Precipitation controls hydrological states (soil moisture and groundwater level), and fluxes (runoff, evapotranspiration and groundwater recharge).
    Hence, precipitation plays a paramount role in urban water systems.

  8. Future Simulated Intensification of Precipitation Extremes, CMIP5 Model Uncertainties and Dependencies

    Science.gov (United States)

    Bador, M.; Donat, M.; Geoffroy, O.; Alexander, L. V.

    2017-12-01

    Precipitation intensity during extreme events is expected to increase with climate change. Throughout the 21st century, CMIP5 climate models project a general increase in annual extreme precipitation in most regions. We investigate how robust this future increase is across different models, regions and seasons. We find that there is strong similarity in extreme precipitation changes between models that share atmospheric physics, reducing the ensemble of 27 models to 14 independent projections. We find that future simulated extreme precipitation increases in most models in the majority of land grid cells located in the dry, intermediate and wet regions according to each model's precipitation climatology. These increases significantly exceed the range of natural variability estimated from long equilibrium control runs. The intensification of extreme precipitation across the entire spectrum of dry to wet regions is particularly robust in the extra-tropics in both wet and dry season, whereas uncertainties are larger in the tropics. The CMIP5 ensemble therefore indicates robust future intensification of annual extreme rainfall in particular in extra-tropical regions. Generally, the CMIP5 robustness is higher during the dry season compared to the wet season and the annual scale, but inter-model uncertainties in the tropics remain important.

  9. Integrated modeling of second phase precipitation in cold-worked 316 stainless steels under irradiation

    International Nuclear Information System (INIS)

    Mamivand, Mahmood; Yang, Ying; Busby, Jeremy T.; Morgan, Dane

    2017-01-01

    The current work combines the Cluster Dynamics (CD) technique and CALPHAD-based precipitation modeling to address the second phase precipitation in cold-worked (CW) 316 stainless steels (SS) under irradiation at 300–400 °C. CD provides the radiation enhanced diffusion and dislocation evolution as inputs for the precipitation model. The CALPHAD-based precipitation model treats the nucleation, growth and coarsening of precipitation processes based on classical nucleation theory and evolution equations, and simulates the composition, size and size distribution of precipitate phases. We benchmark the model against available experimental data at fast reactor conditions (9.4 × 10"–"7 dpa/s and 390 °C) and then use the model to predict the phase instability of CW 316 SS under light water reactor (LWR) extended life conditions (7 × 10"–"8 dpa/s and 275 °C). The model accurately predicts the γ' (Ni_3Si) precipitation evolution under fast reactor conditions and that the formation of this phase is dominated by radiation enhanced segregation. The model also predicts a carbide volume fraction that agrees well with available experimental data from a PWR reactor but is much higher than the volume fraction observed in fast reactors. We propose that radiation enhanced dissolution and/or carbon depletion at sinks that occurs at high flux could be the main sources of this inconsistency. The integrated model predicts ~1.2% volume fraction for carbide and ~3.0% volume fraction for γ' for typical CW 316 SS (with 0.054 wt% carbon) under LWR extended life conditions. Finally, this work provides valuable insights into the magnitudes and mechanisms of precipitation in irradiated CW 316 SS for nuclear applications.

  10. Linear Friction Welding Process Model for Carpenter Custom 465 Precipitation-Hardened Martensitic Stainless Steel

    Science.gov (United States)

    2014-04-11

    Carpenter Custom 465 precipitation-hardened martensitic stainless steel to develop a linear friction welding (LFW) process model for this material...Model for Carpenter Custom 465 Precipitation-Hardened Martensitic Stainless Steel The views, opinions and/or findings contained in this report are... Martensitic Stainless Steel Report Title An Arbitrary Lagrangian-Eulerian finite-element analysis is combined with thermo-mechanical material

  11. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo

    2015-09-15

    We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation and angiogenesis) and ion transportation networks (e.g., neural networks) is explained in detail and basic analytical features like the gradient flow structure of the fluid transportation network model and the impact of the model parameters on the geometry and topology of network formation are analyzed. We also present a numerical finite-element based discretization scheme and discuss sample cases of network formation simulations.

  12. Network modelling methods for FMRI.

    Science.gov (United States)

    Smith, Stephen M; Miller, Karla L; Salimi-Khorshidi, Gholamreza; Webster, Matthew; Beckmann, Christian F; Nichols, Thomas E; Ramsey, Joseph D; Woolrich, Mark W

    2011-01-15

    There is great interest in estimating brain "networks" from FMRI data. This is often attempted by identifying a set of functional "nodes" (e.g., spatial ROIs or ICA maps) and then conducting a connectivity analysis between the nodes, based on the FMRI timeseries associated with the nodes. Analysis methods range from very simple measures that consider just two nodes at a time (e.g., correlation between two nodes' timeseries) to sophisticated approaches that consider all nodes simultaneously and estimate one global network model (e.g., Bayes net models). Many different methods are being used in the literature, but almost none has been carefully validated or compared for use on FMRI timeseries data. In this work we generate rich, realistic simulated FMRI data for a wide range of underlying networks, experimental protocols and problematic confounds in the data, in order to compare different connectivity estimation approaches. Our results show that in general correlation-based approaches can be quite successful, methods based on higher-order statistics are less sensitive, and lag-based approaches perform very poorly. More specifically: there are several methods that can give high sensitivity to network connection detection on good quality FMRI data, in particular, partial correlation, regularised inverse covariance estimation and several Bayes net methods; however, accurate estimation of connection directionality is more difficult to achieve, though Patel's τ can be reasonably successful. With respect to the various confounds added to the data, the most striking result was that the use of functionally inaccurate ROIs (when defining the network nodes and extracting their associated timeseries) is extremely damaging to network estimation; hence, results derived from inappropriate ROI definition (such as via structural atlases) should be regarded with great caution. Copyright © 2010 Elsevier Inc. All rights reserved.

  13. The effect of a giant wind farm on precipitation in a regional climate model

    International Nuclear Information System (INIS)

    Fiedler, B H; Bukovsky, M S

    2011-01-01

    The Weather Research and Forecasting (WRF) model is employed as a nested regional climate model to study the effect of a giant wind farm on warm-season precipitation in the eastern two-thirds of the USA. The boundary conditions for WRF are supplied by 62 years of NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research) global reanalysis. In the model, the presence of a mid-west wind farm, either giant or small, can have an enormous impact on the weather and the amount of precipitation for one season, which is consistent with the known sensitivity of long-term weather forecasts to initial conditions. The effect on climate is less strong. In the average precipitation of 62 warm seasons, there is a statistically significant 1.0% enhancement of precipitation in a multi-state area surrounding and to the south-east of the wind farm.

  14. Precipitation collector bias and its effects on temporal trends and spatial variability in National Atmospheric Deposition Program/National Trends Network data

    Science.gov (United States)

    Wetherbee, Gregory A.

    2017-01-01

    Precipitation samples have been collected by the National Atmospheric Deposition Program's (NADP) National Trends Network (NTN) using the Aerochem Metrics Model 301 (ACM) collector since 1978. Approximately one-third of the NTN ACM collectors have been replaced with N-CON Systems, Inc. Model ADS 00-120 (NCON) collectors. Concurrent data were collected over 6 years at 12 NTN sites using colocated ACM and NCON collectors in various precipitation regimes. Linear regression models of the colocated data were used to adjust for relative bias between the collectors. Replacement of ACM collectors with NCON collectors resulted in shifts in 10-year seasonal precipitation-weighted mean concentration (PWMC) trend slopes for: cations (−0.001 to −0.007 mgL−1yr−1), anions (−0.009 to −0.028 mgL−1yr−1), and hydrogen ion (+0.689 meqL-1yr−1). Larger shifts in NO3− and SO4−2 seasonal PWMC trend slopes were observed in the Midwest and Northeast US, where concentrations are generally higher than in other regions. Geospatial analysis of interpolated concentration rasters indicated regions of accentuated variability introduced by incorporation of NCON collectors into the NTN.

  15. Descriptive and predictive evaluation of high resolution Markov chain precipitation models

    DEFF Research Database (Denmark)

    Sørup, Hjalte Jomo Danielsen; Madsen, Henrik; Arnbjerg-Nielsen, Karsten

    2012-01-01

    A time series of tipping bucket recordings of very high temporal and volumetric resolution precipitation is modelled using Markov chain models. Both first and second‐order Markov models as well as seasonal and diurnal models are investigated and evaluated using likelihood based techniques. The fi...

  16. An assessment of historical Antarctic precipitation and temperature trend using CMIP5 models and reanalysis datasets

    Science.gov (United States)

    Tang, Malcolm S. Y.; Chenoli, Sheeba Nettukandy; Samah, Azizan Abu; Hai, Ooi See

    2018-03-01

    The study of Antarctic precipitation has attracted a lot of attention recently. The reliability of climate models in simulating Antarctic precipitation, however, is still debatable. This work assess the precipitation and surface air temperature (SAT) of Antarctica (90 oS to 60 oS) using 49 Coupled Model Intercomparison Project phase 5 (CMIP5) global climate models and the European Centre for Medium-range Weather Forecasts "Interim" reanalysis (ERA-Interim); the National Centers for Environmental Prediction Climate Forecast System Reanalysis (CFSR); the Japan Meteorological Agency 55-year Reanalysis (JRA-55); and the Modern Era Retrospective-analysis for Research and Applications (MERRA) datasets for 1979-2005 (27 years). For precipitation, the time series show that the MERRA and JRA-55 have significantly increased from 1979 to 2005, while the ERA-Int and CFSR have insignificant changes. The reanalyses also have low correlation with one another (generally less than +0.69). 37 CMIP5 models show increasing trend, 18 of which are significant. The resulting CMIP5 MMM also has a significant increasing trend of 0.29 ± 0.06 mm year-1. For SAT, the reanalyses show insignificant changes and have high correlation with one another, while the CMIP5 MMM shows a significant increasing trend. Nonetheless, the variability of precipitation and SAT of MMM could affect the significance of its trend. One of the many reasons for the large differences of precipitation is the CMIP5 models' resolution.

  17. Research on the model of home networking

    Science.gov (United States)

    Yun, Xiang; Feng, Xiancheng

    2007-11-01

    It is the research hotspot of current broadband network to combine voice service, data service and broadband audio-video service by IP protocol to transport various real time and mutual services to terminal users (home). Home Networking is a new kind of network and application technology which can provide various services. Home networking is called as Digital Home Network. It means that PC, home entertainment equipment, home appliances, Home wirings, security, illumination system were communicated with each other by some composing network technology, constitute a networking internal home, and connect with WAN by home gateway. It is a new network technology and application technology, and can provide many kinds of services inside home or between homes. Currently, home networking can be divided into three kinds: Information equipment, Home appliances, Communication equipment. Equipment inside home networking can exchange information with outer networking by home gateway, this information communication is bidirectional, user can get information and service which provided by public networking by using home networking internal equipment through home gateway connecting public network, meantime, also can get information and resource to control the internal equipment which provided by home networking internal equipment. Based on the general network model of home networking, there are four functional entities inside home networking: HA, HB, HC, and HD. (1) HA (Home Access) - home networking connects function entity; (2) HB (Home Bridge) Home networking bridge connects function entity; (3) HC (Home Client) - Home networking client function entity; (4) HD (Home Device) - decoder function entity. There are many physical ways to implement four function entities. Based on theses four functional entities, there are reference model of physical layer, reference model of link layer, reference model of IP layer and application reference model of high layer. In the future home network

  18. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.

    2013-01-01

    During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.

  19. Performance of Optimally Merged Multisatellite Precipitation Products Using the Dynamic Bayesian Model Averaging Scheme Over the Tibetan Plateau

    Science.gov (United States)

    Ma, Yingzhao; Hong, Yang; Chen, Yang; Yang, Yuan; Tang, Guoqiang; Yao, Yunjun; Long, Di; Li, Changmin; Han, Zhongying; Liu, Ronghua

    2018-01-01

    Accurate estimation of precipitation from satellites at high spatiotemporal scales over the Tibetan Plateau (TP) remains a challenge. In this study, we proposed a general framework for blending multiple satellite precipitation data using the dynamic Bayesian model averaging (BMA) algorithm. The blended experiment was performed at a daily 0.25° grid scale for 2007-2012 among Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT and 3B42V7, Climate Prediction Center MORPHing technique (CMORPH), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). First, the BMA weights were optimized using the expectation-maximization (EM) method for each member on each day at 200 calibrated sites and then interpolated to the entire plateau using the ordinary kriging (OK) approach. Thus, the merging data were produced by weighted sums of the individuals over the plateau. The dynamic BMA approach showed better performance with a smaller root-mean-square error (RMSE) of 6.77 mm/day, higher correlation coefficient of 0.592, and closer Euclid value of 0.833, compared to the individuals at 15 validated sites. Moreover, BMA has proven to be more robust in terms of seasonality, topography, and other parameters than traditional ensemble methods including simple model averaging (SMA) and one-outlier removed (OOR). Error analysis between BMA and the state-of-the-art IMERG in the summer of 2014 further proved that the performance of BMA was superior with respect to multisatellite precipitation data merging. This study demonstrates that BMA provides a new solution for blending multiple satellite data in regions with limited gauges.

  20. Getting water right: A case study in water yield modelling based on precipitation data.

    Science.gov (United States)

    Pessacg, Natalia; Flaherty, Silvia; Brandizi, Laura; Solman, Silvina; Pascual, Miguel

    2015-12-15

    Water yield is a key ecosystem service in river basins and especially in dry regions around the World. In this study we carry out a modelling analysis of water yields in the Chubut River basin, located in one of the driest districts of Patagonia, Argentina. We focus on the uncertainty around precipitation data, a driver of paramount importance for water yield. The objectives of this study are to: i) explore the spatial and numeric differences among six widely used global precipitation datasets for this region, ii) test them against data from independent ground stations, and iii) explore the effects of precipitation data uncertainty on simulations of water yield. The simulations were performed using the ecosystem services model InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) with each of the six different precipitation datasets as input. Our results show marked differences among datasets for the Chubut watershed region, both in the magnitude of precipitations and their spatial arrangement. Five of the precipitation databases overestimate the precipitation over the basin by 50% or more, particularly over the more humid western range. Meanwhile, the remaining dataset (Tropical Rainfall Measuring Mission - TRMM), based on satellite measurements, adjusts well to the observed rainfall in different stations throughout the watershed and provides a better representation of the precipitation gradient characteristic of the rain shadow of the Andes. The observed differences among datasets in the representation of the rainfall gradient translate into large differences in water yield simulations. Errors in precipitation of +30% (-30%) amplify to water yield errors ranging from 50 to 150% (-45 to -60%) in some sub-basins. These results highlight the importance of assessing uncertainties in main input data when quantifying and mapping ecosystem services with biophysical models and cautions about the undisputed use of global environmental datasets. Copyright

  1. Kinetics modeling of precipitation with characteristic shape during post-implantation annealing

    Directory of Open Access Journals (Sweden)

    Kun-Dar Li

    2015-11-01

    Full Text Available In this study, we investigated the precipitation with characteristic shape in the microstructure during post-implantation annealing via a theoretical modeling approach. The processes of precipitates formation and evolution during phase separation were based on a nucleation and growth mechanism of atomic diffusion. Different stages of the precipitation, including the nucleation, growth and coalescence, were distinctly revealed in the numerical simulations. In addition, the influences of ion dose, temperature and crystallographic symmetry on the processes of faceted precipitation were also demonstrated. To comprehend the kinetic mechanism, the simulation results were further analyzed quantitatively by the Kolmogorov-Johnson-Mehl-Avrami (KJMA equation. The Avrami exponents obtained from the regression curves varied from 1.47 to 0.52 for different conditions. With the increase of ion dose and temperature, the nucleation and growth of precipitations were expedited in accordance with the shortened incubation time and the raised coefficient of growth rate. A miscellaneous shape of precipitates in various crystallographic symmetry systems could be simulated through this anisotropic model. From the analyses of the kinetics, more fundamental information about the nucleation and growth mechanism of faceted precipitation during post-implantation annealing was acquired for future application.

  2. The impact of ambient dose rate measuring network and precipitation radar system for detection of environmental radioactivity released by accident

    International Nuclear Information System (INIS)

    Bleher, M; Stoehlker, U.

    2003-01-01

    For the surveillance of environmental radioactivity, the German measuring network of BfS consists of more than 2000 stations where the ambient gamma dose rate is continuously measured. This network is a helpful tool to detect and localise enhanced environmental contamination from artificial radionuclides. The threshold for early warning is so low, that already an additional dose rate contribution of 0,07 μGy/h is detectable. However, this threshold is frequently exceeded due to precipitation events caused by washout of natural activity in air. Therefore, the precipitation radar system of the German Weather Service provides valuable information on the problem, whether the increase of the ambient dose rate is due to natural or man-made events. In case of an accidental release, the data of this radar system show small area precipitation events and potential local hot spots not detected by the measuring network. For the phase of cloud passage, the ambient dose rate measuring network provides a reliable database for the evaluation of the current situation and its further development. It is possible to compare measured data for dose rate with derived intervention levels for countermeasures like ''sheltering''. Thus, critical regions can be identified and it is possible to verify implemented countermeasures. During and after this phase of cloud passage the measured data of the monitoring network help to adapt the results of the national decision support systems PARK and RODOS. Therefore, it is necessary to derive the actual additional contribution to the ambient dose rate. Map representations of measured dose rate are rapidly available and helpful to optimise measurement strategies of mobile systems and collection strategies for samples of agricultural products. (orig.)

  3. Energy modelling in sensor networks

    Science.gov (United States)

    Schmidt, D.; Krämer, M.; Kuhn, T.; Wehn, N.

    2007-06-01

    Wireless sensor networks are one of the key enabling technologies for the vision of ambient intelligence. Energy resources for sensor nodes are very scarce. A key challenge is the design of energy efficient communication protocols. Models of the energy consumption are needed to accurately simulate the efficiency of a protocol or application design, and can also be used for automatic energy optimizations in a model driven design process. We propose a novel methodology to create models for sensor nodes based on few simple measurements. In a case study the methodology was used to create models for MICAz nodes. The models were integrated in a simulation environment as well as in a SDL runtime framework of a model driven design process. Measurements on a test application that was created automatically from an SDL specification showed an 80% reduction in energy consumption compared to an implementation without power saving strategies.

  4. Mixed precipitation occurrences over southern Québec, Canada, under warmer climate conditions using a regional climate model

    Science.gov (United States)

    Matte, Dominic; Thériault, Julie M.; Laprise, René

    2018-05-01

    Winter weather events with temperatures near 0°C are often associated with freezing rain. They can have major impacts on the society by causing power outages and disruptions to the transportation networks. Despite the catastrophic consequences of freezing rain, very few studies have investigated how their occurrences could evolve under climate change. This study aims to investigate the change of freezing rain and ice pellets over southern Québec using regional climate modeling at high resolution. The fifth-generation Canadian Regional Climate Model with climate scenario RCP 8.5 at 0.11° grid mesh was used. The precipitation types such as freezing rain, ice pellets or their combination are diagnosed using five methods (Cantin and Bachand, Bourgouin, Ramer, Czys and, Baldwin). The occurrences of the diagnosed precipitation types for the recent past (1980-2009) are found to be comparable to observations. The projections for the future scenario (2070-2099) suggested a general decrease in the occurrences of mixed precipitation over southern Québec from October to April. This is mainly due to a decrease in long-duration events (≥6 h ). Overall, this study contributes to better understand how the distribution of freezing rain and ice pellets might change in the future using high-resolution regional climate model.

  5. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo; Artina, Marco; Foransier, Massimo; Markowich, Peter A.

    2015-01-01

    We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation

  6. Predisposing, precipitating and perpetuating factors and the common sense model of illness

    DEFF Research Database (Denmark)

    Carstensen, Tina; Kasch, Helge; Frostholm, Lisbeth

    2017-01-01

    Background: Various predisposing, precipitating and perpetuating factors are found to be associated with development of persistent symptoms and disability after whiplash trauma. According to the commonsense model of illness, people use commonsense knowledge to develop individual illness models when...... facing health threat. Question: Can we use the common-sense model as a unifying model to encompass the impact of predisposing, precipitating, and perpetuating factors in the development of chronic whiplash? Looking into specific factors and their interaction: Do illness perceptions mediate the effect...... of precollision sick leave on chronic whiplash? Methods: This presentation will integrate findings from research on predisposing, precipitating, perpetuating factors that are associated with poor outcome after whiplash trauma and propose the common-sense model as a unifying model. Data from a study including 740...

  7. Modeling of chromium precipitation in Fe-Cr alloys

    International Nuclear Information System (INIS)

    Wallenius, J.; Olsson, P.; Lagerstedt, C.; Sandberg, N.; Chakarova, R.; Pontikis, V.

    2004-01-01

    We have implemented a set of Embedded Atom Method (EAM) potentials for simulation of Fe-Cr alloys. The functions for the pure elements were fitted to the respective elastic constants, vacancy formation energy, and thermal expansion coefficients. For Cr, properties of the paramagnetic state were applied, providing a positive Cauchy pressure and hence applicability of the EAM. By relaxing the requirement of reproducing the pressure-volume relation at short interaction distances, stability of the self-interstitial could be obtained. Our Fe-potential gives E lang110rang f -E lang111rang f =-0.23 eV. Mixed Fe-Cr pair potentials were fitted to the calculated mixing enthalpy of ferromagnetic Fe-Cr, which is negative for Cr concentrations below 6%. Simulation of thermal aging in Fe-Cr alloys using a potential fitted to the mixing enthalpy of Fe-20Cr exhibited pronounced Cr-precipitation for temperatures below 900 K, in agreement with the phase diagram. No such ordering was observed at any temperature using a potential fitted to the mixing enthalpy of Fe-5Cr. Applied to recoil cascade simulations the new potentials predict a smaller number of surviving defects than potentials found in the literature. We obtain a cascade efficiency of 0.135 NRT for damage energies in between 10 and 20 keV. An enhanced probability for Cr atoms to end up in defect structures is observed

  8. A Novel Low-Cost Dual-Wavelength Precipitation Radar Sensor Network, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Remote Sensing Solutions, Inc. (RSS) has developed a novel, practical design that will produce a low-cost precipitation radar / radiometer sensor. Operating in a...

  9. Nowcasting of precipitation – Advective statistical forecast model (SAM) for the Czech Republic

    Czech Academy of Sciences Publication Activity Database

    Sokol, Zbyněk; Pešice, Petr

    2012-01-01

    Roč. 103, - (2012), s. 70-79 ISSN 0169-8095 R&D Projects: GA MŠk ME09033; GA ČR GA205/07/0905 Institutional research plan: CEZ:AV0Z30420517 Keywords : Precipitation forecast * Statistical models * Regression * Quantitative precipitation forecast * Extrapolation forecast Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 2.200, year: 2012 http://dx.doi.org/10.1016/j. atm osres.2011.07.013

  10. Impact of convective activity on precipitation δ18O in isotope-enabled models

    Science.gov (United States)

    Hu, J.; Emile-Geay, J.; Dee, S.

    2017-12-01

    The ^18O signal preserved in paleo-archives (e.g. speleothem, tree ring cellulose, ice cores) is widely used to reconstruct precipitation or temperature. In the tropics, the inverse relationship between precipitation ^18O and rainfall amount, namely "amount effect" [Dansgaard, Tellus, 1964], is often used to interpret precipitation ^18O. However, recent studies have shown that precipitation ^18O is also influenced by precipitation type [Kurita et al, JGR, 2009; Moerman et al, EPSL, 2013], and recent observations indicate that it is negatively correlated with the fraction of precipitation associated with stratiform clouds [Aggarwal et al, Nature Geosci, 2016]. It is thus important to determine to what extent isotope-enabled climate models can reproduce these relationships. Here we do so using output from LMDZ, CAM2, and isoGSM from the Stable Water Isotope Intercomparison Group, Phase 2 (SWING2) project and results of SPEEDY-IER [Dee et al, JGR, 2015] from an AMIP-style experiment. The results show that these models simulate the "amount effect" well in the tropics, and the relationship between precipitation ^18O and precipitation is reversed in many places in mid-latitudes, in accordance with observations [Bowen, JGR, 2008]. Also, these models can all reproduce the negative correlation between monthly precipitation ^18O and stratiform precipitation proportion in mid-latitude (30°N-50°N; 50°S-30°S), but in the tropics (30°S-30°N), models show a positive correlation instead. The reason for this bias will be investigated within idealized experiments with SPEEDY-IER. The correct simulations of the impact of convective activity on precipitation ^18O in isotope-enabled models will improve our interpretation of paleoclimate proxies with respect to hydroclimate variability. P. K. Aggarwal et al. (2016), Nature Geosci., 9, 624-629, doi:10.1038/ngeo2739. G. J. Bowen. (2008), J. Geophys. Res., 113, D05113, doi:10.1029/2007JD009295. W. Dansgaard (1964), Tellus, 16(4), 436

  11. Projected changes in precipitation intensity and frequency over complex topography: a multi-model perspective

    Science.gov (United States)

    Fischer, Andreas; Keller, Denise; Liniger, Mark; Rajczak, Jan; Schär, Christoph; Appenzeller, Christof

    2014-05-01

    Fundamental changes in the hydrological cycle are expected in a future warmer climate. This is of particular relevance for the Alpine region, as a source and reservoir of several major rivers in Europe and being prone to extreme events such as floodings. For this region, climate change assessments based on the ENSEMBLES regional climate models (RCMs) project a significant decrease in summer mean precipitation under the A1B emission scenario by the mid-to-end of this century, while winter mean precipitation is expected to slightly rise. From an impact perspective, projected changes in seasonal means, however, are often insufficient to adequately address the multifaceted challenges of climate change adaptation. In this study, we revisit the full matrix of the ENSEMBLES RCM projections regarding changes in frequency and intensity, precipitation-type (convective versus stratiform) and temporal structure (wet/dry spells and transition probabilities) over Switzerland and surroundings. As proxies for raintype changes, we rely on the model parameterized convective and large-scale precipitation components. Part of the analysis involves a Bayesian multi-model combination algorithm to infer changes from the multi-model ensemble. The analysis suggests a summer drying that evolves altitude-specific: over low-land regions it is associated with wet-day frequency decreases of convective and large-scale precipitation, while over elevated regions it is primarily associated with a decline in large-scale precipitation only. As a consequence, almost all the models project an increase in the convective fraction at elevated Alpine altitudes. The decrease in the number of wet days during summer is accompanied by decreases (increases) in multi-day wet (dry) spells. This shift in multi-day episodes also lowers the likelihood of short dry spell occurrence in all of the models. For spring and autumn the combined multi-model projections indicate higher mean precipitation intensity north of the

  12. An evolving network model with community structure

    International Nuclear Information System (INIS)

    Li Chunguang; Maini, Philip K

    2005-01-01

    Many social and biological networks consist of communities-groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties

  13. Brand Marketing Model on Social Networks

    Directory of Open Access Journals (Sweden)

    Jolita Jezukevičiūtė

    2014-04-01

    Full Text Available The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalysis of a single case study revealed a brand marketingsocial networking tools that affect consumers the most. Basedon information analysis and methodological studies, develop abrand marketing model on social networks.

  14. A precipitation-induced landslide susceptibility model for natural gas transmission pipelines

    Energy Technology Data Exchange (ETDEWEB)

    Finley, Jason P. [Fugro William Lettis and Associates, Inc., Valencia, California (United States); Slayter, David L.; Hitchcock, Chris S. [Fugro William Lettis and Associates, Inc., Walnut Creek, California (United States); Lee, Chih-Hung [Pacific Gas and Electric Company, Gas Systems Integrity Management, Walnut Creek, California (United States)

    2010-07-01

    Landslides related to heavy rainfall can cause extensive damage to natural gas transmission pipelines. Fugro William Lettis and Associates Inc. have developed and implemented a geographic information system (GIS) model that evaluates near real-time precipitation-induced landslide susceptibility. The model incorporates state-wide precipitation data and geologically-based landslide classifications to produce rapid landslide risk evaluation for Pacific Gas and Electric Company's (PGandE) gas transmission system during winter rain storms in California. The precipitation data include pre-storm event quantitative precipitation forecasts (QPF) and post-storm event quantitative precipitation estimate (QPE) from the United States National Oceanic and Atmospheric Administration (NOAA). The geologic classifications are based on slope, susceptible geologic formations, and the locations of historic or known landslide occurrences. Currently the model is calibrated using qualitative measures. This paper describes the development of the model algorithm and input data, model results, calibration efforts, and the on-going research and landslide collection warranted for continued refinement of the model.

  15. A novel Direct Small World network model

    Directory of Open Access Journals (Sweden)

    LIN Tao

    2016-10-01

    Full Text Available There is a certain degree of redundancy and low efficiency of existing computer networks.This paper presents a novel Direct Small World network model in order to optimize networks.In this model,several nodes construct a regular network.Then,randomly choose and replot some nodes to generate Direct Small World network iteratively.There is no change in average distance and clustering coefficient.However,the network performance,such as hops,is improved.The experiments prove that compared to traditional small world network,the degree,average of degree centrality and average of closeness centrality are lower in Direct Small World network.This illustrates that the nodes in Direct Small World networks are closer than Watts-Strogatz small world network model.The Direct Small World can be used not only in the communication of the community information,but also in the research of epidemics.

  16. RMBNToolbox: random models for biochemical networks

    Directory of Open Access Journals (Sweden)

    Niemi Jari

    2007-05-01

    Full Text Available Abstract Background There is an increasing interest to model biochemical and cell biological networks, as well as to the computational analysis of these models. The development of analysis methodologies and related software is rapid in the field. However, the number of available models is still relatively small and the model sizes remain limited. The lack of kinetic information is usually the limiting factor for the construction of detailed simulation models. Results We present a computational toolbox for generating random biochemical network models which mimic real biochemical networks. The toolbox is called Random Models for Biochemical Networks. The toolbox works in the Matlab environment, and it makes it possible to generate various network structures, stoichiometries, kinetic laws for reactions, and parameters therein. The generation can be based on statistical rules and distributions, and more detailed information of real biochemical networks can be used in situations where it is known. The toolbox can be easily extended. The resulting network models can be exported in the format of Systems Biology Markup Language. Conclusion While more information is accumulating on biochemical networks, random networks can be used as an intermediate step towards their better understanding. Random networks make it possible to study the effects of various network characteristics to the overall behavior of the network. Moreover, the construction of artificial network models provides the ground truth data needed in the validation of various computational methods in the fields of parameter estimation and data analysis.

  17. Evaluation of globally available precipitation data products as input for water balance models

    Science.gov (United States)

    Lebrenz, H.; Bárdossy, A.

    2009-04-01

    Subject of this study is the evaluation of globally available precipitation data products, which are intended to be used as input variables for water balance models in ungauged basins. The selected data sources are a) the Global Precipitation Climatology Centre (GPCC), b) the Global Precipitation Climatology Project (GPCP) and c) the Climate Research Unit (CRU), resulting into twelve globally available data products. The data products imply different data bases, different derivation routines and varying resolutions in time and space. For validation purposes, the ground data from South Africa were screened on homogeneity and consistency by various tests and an outlier detection using multi-linear regression was performed. External Drift Kriging was subsequently applied on the ground data and the resulting precipitation arrays were compared to the different products with respect to quantity and variance.

  18. Small angle neutron scattering modeling of copper-rich precipitates in steel

    International Nuclear Information System (INIS)

    Spooner, S.

    1997-11-01

    The magnetic to nuclear scattering intensity ratio observed in the scattering from copper rich precipitates in irradiated pressure vessel steels is much smaller than the value of 11.4 expected for a pure copper precipitate in iron. A model for precipitates in pressure vessel steels which matches the observed scattering typically incorporates manganese, nickel, silicon and other elements and it is assumed that the precipitate is non-magnetic. In the present work consideration is given to the effect of composition gradients and ferromagnetic penetration into the precipitate on the small angle scattering cross section for copper rich clusters as distinguished from conventional precipitates. The calculation is an extension of a scattering model for micelles which consist of shells of varying scattering density. A discrepancy between recent SANS scattering experiments on pressure vessel steels was found to be related to applied magnetic field strength. The assumption of cluster structure and its relation to atom probe FIM findings as well as the effects of insufficient field for magnetic saturation is discussed

  19. Brand Marketing Model on Social Networks

    OpenAIRE

    Jolita Jezukevičiūtė; Vida Davidavičienė

    2014-01-01

    The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalys...

  20. Brand marketing model on social networks

    OpenAIRE

    Jezukevičiūtė, Jolita; Davidavičienė, Vida

    2014-01-01

    Paper analyzes the brand and its marketing solutions on social networks. This analysis led to the creation of improved brand marketing model on social networks, which will contribute to the rapid and cheap organization brand recognition, increase competitive advantage and enhance consumer loyalty. Therefore, the brand and a variety of social networks are becoming a hot research area for brand marketing model on social networks. The world‘s most successful brand marketing models exploratory an...

  1. Participation of the Pennsylvania State University in the MAP3S precipitation chemistry network

    International Nuclear Information System (INIS)

    Lamb, D.; de Pena, R.G.

    1991-04-01

    The Meteorology Department of the Pennsylvania State University collected precipitation in central Pennsylvania for more than 14 years on behalf of the Multistate Atmospheric Power Production Pollution Study (MAP3S). The MAP3S protocol, based on the sampling of precipitation from individual meteorological events over a long period of time, has allowed both for the development of a chemical climatology of precipitation in the eastern region of the United States and for a vastly improved understanding of the atmospheric processes responsible for wet acidic deposition. The precipitation chemistry data from the Penn State MAP3S site provide evidence of links to the anthropogenic emissions of sulfur dioxide and oxidant precursors. There is now little doubt that the free acidity in the precipitation of the region is due to the presence of unneutralized sulfate in the aqueous phase. In the absence of significant sources of this sulfur species and in view of supplemental enrichment studies, it is concluded that the sulfate enters cloud and rain water primarily through the aqueous-phase oxidation of sulfur dioxide emitted into the air within the geographical region of deposition. Within the source region the local abundances of sulfur dioxide often exceed those of the oxidants, so the depositions of sulfate and free acidity tend to be modulated by the availability of the strong oxidants. As a consequence, the deposition of sulfate exhibits a very strong seasonal dependence and little response to changes in the emissions of sulfur dioxide

  2. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  3. Network bandwidth utilization forecast model on high bandwidth networks

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Wuchert (William) [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-03-30

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2%. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  4. A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

    Science.gov (United States)

    Tao, W. K.

    2017-12-01

    In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

  5. Impact of Asian Aerosols on Precipitation Over California: An Observational and Model Based Approach

    Science.gov (United States)

    Naeger, Aaron R.; Molthan, Andrew L.; Zavodsky, Bradley T.; Creamean, Jessie M.

    2015-01-01

    Dust and pollution emissions from Asia are often transported across the Pacific Ocean to over the western United States. Therefore, it is essential to fully understand the impact of these aerosols on clouds and precipitation forming over the eastern Pacific and western United States, especially during atmospheric river events that account for up to half of California's annual precipitation and can lead to widespread flooding. In order for numerical modeling simulations to accurately represent the present and future regional climate of the western United States, we must account for the aerosol-cloud-precipitation interactions associated with Asian dust and pollution aerosols. Therefore, we have constructed a detailed study utilizing multi-sensor satellite observations, NOAA-led field campaign measurements, and targeted numerical modeling studies where Asian aerosols interacted with cloud and precipitation processes over the western United States. In particular, we utilize aerosol optical depth retrievals from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS), NOAA Geostationary Operational Environmental Satellite (GOES-11), and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT) to effectively detect and monitor the trans-Pacific transport of Asian dust and pollution. The aerosol optical depth (AOD) retrievals are used in assimilating the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in order to provide the model with an accurate representation of the aerosol spatial distribution across the Pacific. We conduct WRF-Chem model simulations of several cold-season atmospheric river events that interacted with Asian aerosols and brought significant precipitation over California during February-March 2011 when the NOAA CalWater field campaign was ongoing. The CalWater field campaign consisted of aircraft and surface measurements of aerosol and precipitation processes that help extensively validate our WRF

  6. Forecasting gastrointestinal precipitation and oral pharmacokinetics of dantrolene in dogs using an in vitro precipitation testing coupled with in silico modeling and simulation.

    Science.gov (United States)

    Kambayashi, Atsushi; Dressman, Jennifer B

    2017-10-01

    The aim of the current research was to determine the precipitation kinetics of dantrolene sodium using canine biorelevant in vitro testing and to model the precipitation kinetics by appropriately coupling the data with an in silico tool adapted for dogs. The precipitation profiles of dantrolene sodium solutions were obtained with the in vitro paddle apparatus at a revolution rate of 50rpm. The in silico prediction tool was designed using STELLA software and the predicted plasma concentration profiles of dantrolene using the in vitro precipitation data were compared with the observed in vivo pharmacokinetics in beagle dogs. The plasma profiles of dantrolene, which served as a model weakly acidic drug which precipitates in the upper gastrointestinal tract, was successfully predicted using the in vitro precipitation testing coupled with the in silico modeling and simulation approach. The approach was subsequently used to forecast the effect of pharmaceutical excipients (HPMC/PG) on the ability of the drug to supersaturate in the gut and the resulting pharmacokinetics. The agreement of the simulated pharmacokinetics with the observed values confirms the ability of canine biorelevant media to predict oral performance of enhanced dosage forms in dogs. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Comparison of Extreme Precipitation Return Levels using Spatial Bayesian Hierarchical Modeling versus Regional Frequency Analysis

    Science.gov (United States)

    Love, C. A.; Skahill, B. E.; AghaKouchak, A.; Karlovits, G. S.; England, J. F.; Duren, A. M.

    2017-12-01

    We compare gridded extreme precipitation return levels obtained using spatial Bayesian hierarchical modeling (BHM) with their respective counterparts from a traditional regional frequency analysis (RFA) using the same set of extreme precipitation data. Our study area is the 11,478 square mile Willamette River basin (WRB) located in northwestern Oregon, a major tributary of the Columbia River whose 187 miles long main stem, the Willamette River, flows northward between the Coastal and Cascade Ranges. The WRB contains approximately two ­thirds of Oregon's population and 20 of the 25 most populous cities in the state. The U.S. Army Corps of Engineers (USACE) Portland District operates thirteen dams and extreme precipitation estimates are required to support risk­ informed hydrologic analyses as part of the USACE Dam Safety Program. Our intent is to profile for the USACE an alternate methodology to an RFA that was developed in 2008 due to the lack of an official NOAA Atlas 14 update for the state of Oregon. We analyze 24-hour annual precipitation maxima data for the WRB utilizing the spatial BHM R package "spatial.gev.bma", which has been shown to be efficient in developing coherent maps of extreme precipitation by return level. Our BHM modeling analysis involved application of leave-one-out cross validation (LOO-CV), which not only supported model selection but also a comprehensive assessment of location specific model performance. The LOO-CV results will provide a basis for the BHM RFA comparison.

  8. Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)

    Science.gov (United States)

    Regan, R. Steven; Markstrom, Steven L.; Hay, Lauren E.; Viger, Roland J.; Norton, Parker A.; Driscoll, Jessica M.; LaFontaine, Jacob H.

    2018-01-08

    This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.

  9. A statistical intercomparison between "urban" and "rural" precipitation chemistry data from greater Manchester and two nearby secondary national network sites in the United Kingdom

    Science.gov (United States)

    Lee, David S.; Longhurst, James W. S.

    Precipitation chemistry data from a dense urban monitoring network in Greater Manchester, northwest England, were compared with interpolated values from the U.K. secondary national acid deposition monitoring network for the year 1988. Differences were found to be small. However, when data from individual sites from the Greater Manchester network were compared with data from the two nearest secondary national network sites, significant differences were found using simple and complex statistical analyses. Precipitation chemistry at rural sites could be similar to that at urban sites, but the sources of some ions were thought to be different. The synoptic-scale gradients of precipitation chemistry, as shown by the secondary national network, also accounted for some of the differences.

  10. Summary of Mercury and Trace Element Results in Precipitation from the Culpeper, Virginia, Mercury Deposition Network Site (VA-08), 2002-2006

    Science.gov (United States)

    Engle, Mark A.; Kolker, Allan; Mose, Douglas E.; East, Joseph A.; McCord, Jamey D.

    2008-01-01

    The VA-08 Mercury Deposition Network (MDN) site, southwest of Culpeper, Virginia, was established in autumn of 2002. This site, along with nearby VA-28 (~31 km west) at Big Meadows in Shenandoah National Park, fills a spatial gap in the Mid-Atlantic region of the MDN network and provides Hg deposition data immediately west of the Washington, D.C., metropolitan area. Results for the Culpeper site from autumn of 2002 to the end of 2006 suggest that the highest mercury (Hg) deposition (up to 5.0 ug/m2 per quarter of the 6.5-12.6 ug/m2 annual Hg deposition) is measured during the second and third quarters of the year (April-September). This is a result of both elevated Hg precipitation concentrations (up to 27 ng/L) and greater precipitation during these months. The data also exhibit a general statistically significant (peffect during larger precipitation events, especially during winter and spring. Comparison of results between the Culpeper and Big Meadows sites indicates that although quarterly Hg deposition was not significantly different (panalysis of the Hg and trace metal data identified 3 primary source categories, each with large loadings of characteristic elements: 1) Ca, Al, Mg, Sr, La, and Ce (crustal sources); 2) V, Na, and Ni (local wintertime heating oil); and 3) Zn, Cd, Mn, and Hg (regional anthropogenic emission sources). HYSPLIT air mass trajectory modeling and enrichment factor calculations are consistent with this interpretation. A preliminary source attribution model suggests that ~51% of the Hg in wet deposition is due to regional anthropogenic sources, while crustal sources and local oil combustion account for 9.5% and <1%, respectively. This calculation implies that the global Hg burden accounts for ~40% of the Hg in wet deposition.

  11. On the long-range dependence properties of annual precipitation using a global network of instrumental measurements

    Science.gov (United States)

    Tyralis, Hristos; Dimitriadis, Panayiotis; Koutsoyiannis, Demetris; O'Connell, Patrick Enda; Tzouka, Katerina; Iliopoulou, Theano

    2018-01-01

    The long-range dependence (LRD) is considered an inherent property of geophysical processes, whose presence increases uncertainty. Here we examine the spatial behaviour of LRD in precipitation by regressing the Hurst parameter estimate of mean annual precipitation instrumental data which span from 1916-2015 and cover a big area of the earth's surface on location characteristics of the instrumental data stations. Furthermore, we apply the Mann-Kendall test under the LRD assumption (MKt-LRD) to reassess the significance of observed trends. To summarize the results, the LRD is spatially clustered, it seems to depend mostly on the location of the stations, while the predictive value of the regression model is good. Thus when investigating for LRD properties we recommend that the local characteristics should be considered. The application of the MKt-LRD suggests that no significant monotonic trend appears in global precipitation, excluding the climate type D (snow) regions in which positive significant trends appear.

  12. Conditional Stochastic Models in Reduced Space: Towards Efficient Simulation of Tropical Cyclone Precipitation Patterns

    Science.gov (United States)

    Dodov, B.

    2017-12-01

    Stochastic simulation of realistic and statistically robust patterns of Tropical Cyclone (TC) induced precipitation is a challenging task. It is even more challenging in a catastrophe modeling context, where tens of thousands of typhoon seasons need to be simulated in order to provide a complete view of flood risk. Ultimately, one could run a coupled global climate model and regional Numerical Weather Prediction (NWP) model, but this approach is not feasible in the catastrophe modeling context and, most importantly, may not provide TC track patterns consistent with observations. Rather, we propose to leverage NWP output for the observed TC precipitation patterns (in terms of downscaled reanalysis 1979-2015) collected on a Lagrangian frame along the historical TC tracks and reduced to the leading spatial principal components of the data. The reduced data from all TCs is then grouped according to timing, storm evolution stage (developing, mature, dissipating, ETC transitioning) and central pressure and used to build a dictionary of stationary (within a group) and non-stationary (for transitions between groups) covariance models. Provided that the stochastic storm tracks with all the parameters describing the TC evolution are already simulated, a sequence of conditional samples from the covariance models chosen according to the TC characteristics at a given moment in time are concatenated, producing a continuous non-stationary precipitation pattern in a Lagrangian framework. The simulated precipitation for each event is finally distributed along the stochastic TC track and blended with a non-TC background precipitation using a data assimilation technique. The proposed framework provides means of efficient simulation (10000 seasons simulated in a couple of days) and robust typhoon precipitation patterns consistent with observed regional climate and visually undistinguishable from high resolution NWP output. The framework is used to simulate a catalog of 10000 typhoon

  13. Modeling of Asphaltene Precipitation from Crude Oil with the Cubic Plus Association Equation of State

    DEFF Research Database (Denmark)

    Arya, Alay; Liang, Xiaodong; von Solms, Nicolas

    2017-01-01

    In this study, different modeling approaches using the Cubic Plus Association (CPA) equation of state (EoS) are developed to calculate the asphaltene precipitation onset condition and asphaltene yield from degassed crude oil during the addition of n-paraffin. A single model parameter is fitted...

  14. Evaluation of modeled changes in extreme precipitation in Europe and the Rhine basin

    NARCIS (Netherlands)

    Haren, van R.; Oldenborgh, van G.J.; Lenderink, G.; Hazeleger, W.

    2013-01-01

    In this study, we investigate the change in multi-day precipitation extremes in late winter in Europe using observations and climate models. The objectives of the analysis are to determine whether climate models can accurately reproduce observed trends and, if not, to find the causes of the

  15. A model for estimating understory vegetation response to fertilization and precipitation in loblolly pine plantations

    Science.gov (United States)

    Curtis L. VanderSchaaf; Ryan W. McKnight; Thomas R. Fox; H. Lee Allen

    2010-01-01

    A model form is presented, where the model contains regressors selected for inclusion based on biological rationale, to predict how fertilization, precipitation amounts, and overstory stand density affect understory vegetation biomass. Due to time, economic, and logistic constraints, datasets of large sample sizes generally do not exist for understory vegetation. Thus...

  16. Local control on precipitation in a fully coupled climate-hydrology model

    DEFF Research Database (Denmark)

    Larsen, Morten A. D.; Christensen, Jens H.; Drews, Martin

    2016-01-01

    simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface...

  17. Nonlinear regression and ARIMA models for precipitation chemistry in East Central Florida from 1978 to 1997

    International Nuclear Information System (INIS)

    Nickerson, David M.; Madsen, Brooks C.

    2005-01-01

    Continuous monitoring of precipitation in East Central Florida has occurred since 1978 at a sampling site located on the University of Central Florida (UCF) campus. Monthly volume-weighted average (VWA) concentration for several major analytes that are present in precipitation samples was calculated from samples collected daily. Monthly VWA concentration and wet deposition of H + , NH 4 + , Ca 2+ , Mg 2+ , NO 3 - , Cl - and SO 4 2- were evaluated by a nonlinear regression (NLR) model that considered 10-year data (from 1978 to 1987) and 20-year data (from 1978 to 1997). Little change in the NLR parameter estimates was indicated among the 10-year and 20-year evaluations except for general decreases in the predicted trends from the 10-year to the 20-year fits. Box-Jenkins autoregressive integrated moving average (ARIMA) models with linear trend were considered as an alternative to the NLR models for these data. The NLR and ARIMA model forecasts for 1998 were compared to the actual 1998 data. For monthly VWA concentration values, the two models gave similar results. For the wet deposition values, the ARIMA models performed considerably better. - Autoregressive integrated moving average models of precipitation data are an improvement over nonlinear models for the prediction of precipitation chemistry composition

  18. On the performance of satellite precipitation products in riverine flood modeling: A review

    Science.gov (United States)

    Maggioni, Viviana; Massari, Christian

    2018-03-01

    This work is meant to summarize lessons learned on using satellite precipitation products for riverine flood modeling and to propose future directions in this field of research. Firstly, the most common satellite precipitation products (SPPs) during the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) eras are reviewed. Secondly, we discuss the main errors and uncertainty sources in these datasets that have the potential to affect streamflow and runoff model simulations. Thirdly, past studies that focused on using SPPs for predicting streamflow and runoff are analyzed. As the impact of floods depends not only on the characteristics of the flood itself, but also on the characteristics of the region (population density, land use, geophysical and climatic factors), a regional analysis is required to assess the performance of hydrologic models in monitoring and predicting floods. The performance of SPP-forced hydrological models was shown to largely depend on several factors, including precipitation type, seasonality, hydrological model formulation, topography. Across several basins around the world, the bias in SPPs was recognized as a major issue and bias correction methods of different complexity were shown to significantly reduce streamflow errors. Model re-calibration was also raised as a viable option to improve SPP-forced streamflow simulations, but caution is necessary when recalibrating models with SPP, which may result in unrealistic parameter values. From a general standpoint, there is significant potential for using satellite observations in flood forecasting, but the performance of SPP in hydrological modeling is still inadequate for operational purposes.

  19. An acoustical model based monitoring network

    NARCIS (Netherlands)

    Wessels, P.W.; Basten, T.G.H.; Eerden, F.J.M. van der

    2010-01-01

    In this paper the approach for an acoustical model based monitoring network is demonstrated. This network is capable of reconstructing a noise map, based on the combination of measured sound levels and an acoustic model of the area. By pre-calculating the sound attenuation within the network the

  20. Comparison and evaluation of satellite derived precipitation products for hydrological modeling of the Zambezi River Basin

    Directory of Open Access Journals (Sweden)

    T. Cohen Liechti

    2012-02-01

    Full Text Available In the framework of the African DAms ProjecT (ADAPT, an integrated water resource management study in the Zambezi Basin is currently under development. In view of the sparse gauging network for rainfall monitoring, the observations from spaceborne instrumentation currently produce the only available rainfall data for a large part of the basin.

    Three operational and acknowledged high resolution satellite derived estimates: the Tropical Rainfall Measuring Mission product 3B42 (TRMM 3B42, the Famine Early Warning System product 2.0 (FEWS RFE2.0 and the National Oceanic and Atmospheric Administration/Climate Prediction Centre (NOAA/CPC morphing technique (CMORPH are analyzed in terms of spatial and temporal repartition of the precipitations. They are compared to ground data for the wet seasons of the years 2003 to 2009 on a point to pixel basis at daily, 10-daily and monthly time steps and on a pixel to pixel basis for the wet seasons of the years 2003 to 2007 at monthly time steps.

    The general North-South gradient of precipitation is captured by all the analyzed products. Regarding the spatial heterogeneity, FEWS pixels are much more inter-correlated than TRMM and CMORPH pixels. For a rainfall homogeneity threshold criterion of 0.5 global mean correlation coefficient, the area of each sub-basin should not exceed a circle of 2.5° latitude/longitude radius for FEWS and a circle of 0.75° latitude/longitude radius for TRMM and CMORPH considering rectangular meshes.

    In terms of reliability, the correspondence of all estimates with ground data increases with the time step chosen for the analysis. The volume ratio computation indicates that CMORPH is overestimating the rainfall by nearly 50%. The statistics of TRMM and FEWS estimates show quite similar results.

    Due to its lower inter-correlation and longer data set, the TRMM 3B42 product is chosen as input for the hydraulic-hydrologic model of the basin.

  1. Error Analysis of Satellite Precipitation-Driven Modeling of Flood Events in Complex Alpine Terrain

    Directory of Open Access Journals (Sweden)

    Yiwen Mei

    2016-03-01

    Full Text Available The error in satellite precipitation-driven complex terrain flood simulations is characterized in this study for eight different global satellite products and 128 flood events over the Eastern Italian Alps. The flood events are grouped according to two flood types: rain floods and flash floods. The satellite precipitation products and runoff simulations are evaluated based on systematic and random error metrics applied on the matched event pairs and basin-scale event properties (i.e., rainfall and runoff cumulative depth and time series shape. Overall, error characteristics exhibit dependency on the flood type. Generally, timing of the event precipitation mass center and dispersion of the time series derived from satellite precipitation exhibits good agreement with the reference; the cumulative depth is mostly underestimated. The study shows a dampening effect in both systematic and random error components of the satellite-driven hydrograph relative to the satellite-retrieved hyetograph. The systematic error in shape of the time series shows a significant dampening effect. The random error dampening effect is less pronounced for the flash flood events and the rain flood events with a high runoff coefficient. This event-based analysis of the satellite precipitation error propagation in flood modeling sheds light on the application of satellite precipitation in mountain flood hydrology.

  2. Evaluation of Gridded Precipitation Data for Driving SWAT Model in Area Upstream of Three Gorges Reservoir

    Science.gov (United States)

    Yang, Yan; Wang, Guoqiang; Wang, Lijing; Yu, Jingshan; Xu, Zongxue

    2014-01-01

    Gridded precipitation data are becoming an important source for driving hydrologic models to achieve stable and valid simulation results in different regions. Thus, evaluating different sources of precipitation data is important for improving the applicability of gridded data. In this study, we used three gridded rainfall datasets: 1) National Centers for Environmental Prediction - Climate Forecast System Reanalysis (NCEP-CFSR); 2) Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE); and 3) China trend - surface reanalysis (trend surface) data. These are compared with monitoring precipitation data for driving the Soil and Water Assessment Tool in two basins upstream of Three Gorges Reservoir (TGR) in China. The results of one test basin with significant topographic influence indicates that all the gridded data have poor abilities in reproducing hydrologic processes with the topographic influence on precipitation quantity and distribution. However, in a relatively flat test basin, the APHRODITE and trend surface data can give stable and desirable results. The results of this study suggest that precipitation data for future applications should be considered comprehensively in the TGR area, including the influence of data density and topography. PMID:25409467

  3. Evaluation of gridded precipitation data for driving SWAT model in area upstream of Three Gorges Reservoir.

    Science.gov (United States)

    Yang, Yan; Wang, Guoqiang; Wang, Lijing; Yu, Jingshan; Xu, Zongxue

    2014-01-01

    Gridded precipitation data are becoming an important source for driving hydrologic models to achieve stable and valid simulation results in different regions. Thus, evaluating different sources of precipitation data is important for improving the applicability of gridded data. In this study, we used three gridded rainfall datasets: 1) National Centers for Environmental Prediction-Climate Forecast System Reanalysis (NCEP-CFSR); 2) Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE); and 3) China trend-surface reanalysis (trend surface) data. These are compared with monitoring precipitation data for driving the Soil and Water Assessment Tool in two basins upstream of Three Gorges Reservoir (TGR) in China. The results of one test basin with significant topographic influence indicates that all the gridded data have poor abilities in reproducing hydrologic processes with the topographic influence on precipitation quantity and distribution. However, in a relatively flat test basin, the APHRODITE and trend surface data can give stable and desirable results. The results of this study suggest that precipitation data for future applications should be considered comprehensively in the TGR area, including the influence of data density and topography.

  4. A thermodynamic solution model for calcium carbonate: Towards an understanding of multi-equilibria precipitation pathways.

    Science.gov (United States)

    Donnet, Marcel; Bowen, Paul; Lemaître, Jacques

    2009-12-15

    Thermodynamic solubility calculations are normally only related to thermodynamic equilibria in solution. In this paper, we extend the use of such solubility calculations to help elucidate possible precipitation reaction pathways during the entire reaction. We also estimate the interfacial energy of particles using only solubility data by a modification of Mersmann's approach. We have carried this out by considering precipitation reactions as a succession of small quasi-equilibrium states. Thus possible equilibrium precipitation pathways can be evaluated by calculating the evolution of surface charge, particle size and/or interfacial energy during the ongoing reaction. The approach includes the use of the Kelvin's law to express the influence of particle size on the solubility constant of precipitates, the use of Nernst's law to calculate surface potentials from solubility calculations and relate this to experimentally measured zeta potentials. Calcium carbonate precipitation and zeta potential measurements of well characterised high purity calcite have been used as a model system to validate the calculated values. The clarification of the change in zeta potential on titration illustrates the power of this approach as a tool for reaction pathway prediction and hence knowledge based tailoring of precipitation reactions.

  5. Simulating the convective precipitation diurnal cycle in a North American scale convection-permitting model

    Science.gov (United States)

    Scaff, L.; Li, Y.; Prein, A. F.; Liu, C.; Rasmussen, R.; Ikeda, K.

    2017-12-01

    A better representation of the diurnal cycle of convective precipitation is essential for the analysis of the energy balance and the water budget components such as runoff, evaporation and infiltration. Convection-permitting regional climate modeling (CPM) has been shown to improve the models' performance of summer precipitation, allowing to: (1) simulate the mesoscale processes in more detail and (2) to provide more insights in future changes in convective precipitation under climate change. In this work we investigate the skill of the Weather Research and Forecast model (WRF) in simulating the summer precipitation diurnal cycle over most of North America. We use 4 km horizontal grid spacing in a 13-years long current and future period. The future scenario is assuming no significant changes in large-scale weather patterns and aims to answer how the weather of the current climate would change if it would reoccur at the end of the century under a high-end emission scenario (Pseudo Global Warming). We emphasize on a region centered on the lee side of the Canadian Rocky Mountains, where the summer precipitation amount shows a regional maximum. The historical simulations are capable to correctly represent the diurnal cycle. At the lee-side of the Canadian Rockies the increase in the convective available potential energy as well as pronounced low-level moisture flux from the southeast Prairies explains the local maximum in summer precipitation. The PGW scenario shows an increase in summer precipitation amount and intensity in this region, consistently with a stronger source of moisture and convective energy.

  6. Spinal Cord Injury Model System Information Network

    Science.gov (United States)

    ... the UAB-SCIMS More The UAB-SCIMS Information Network The University of Alabama at Birmingham Spinal Cord Injury Model System (UAB-SCIMS) maintains this Information Network as a resource to promote knowledge in the ...

  7. Eight challenges for network epidemic models

    Directory of Open Access Journals (Sweden)

    Lorenzo Pellis

    2015-03-01

    Full Text Available Networks offer a fertile framework for studying the spread of infection in human and animal populations. However, owing to the inherent high-dimensionality of networks themselves, modelling transmission through networks is mathematically and computationally challenging. Even the simplest network epidemic models present unanswered questions. Attempts to improve the practical usefulness of network models by including realistic features of contact networks and of host–pathogen biology (e.g. waning immunity have made some progress, but robust analytical results remain scarce. A more general theory is needed to understand the impact of network structure on the dynamics and control of infection. Here we identify a set of challenges that provide scope for active research in the field of network epidemic models.

  8. A Precipitation-Runoff Model for the Blackstone River Basin, Massachusetts and Rhode Island

    Science.gov (United States)

    Barbaro, Jeffrey R.; Zarriello, Phillip J.

    2007-01-01

    Survey cooperative streamflow-gaging network, and at seven partial-record stations installed in 2004 for this study. Because the model-calibration period preceded data collection at the partial-record stations, a continuous streamflow record was estimated at these stations by correlation with flows at nearby continuous-record stations to provide additional streamflow data for model calibration. Water-use information was compiled for 1996-2001 and included municipal and commercial/industrial withdrawals, private residential withdrawals, golf-course withdrawals, municipal wastewater-return flows, and on-site septic effluent return flows. Streamflow depletion was computed for all time-varying ground-water withdrawals prior to simulation. Water-use data were included in the model to represent the net effect of water use on simulated hydrographs. Consequently, the calibrated values of the hydrologic parameters better represent the hydrologic response of the basin to precipitation. The model was calibrated for 1997-2001 to coincide with the land-use and water-use data compiled for the study. Four long-term stations (Nipmuc River near Harrisville, Rhode Island; Quinsigamond River at North Grafton, Massachusetts; Branch River at Forestdale, Rhode Island; and Blackstone River at Woonsocket, Rhode Island) that monitor flow at 3.3, 5.4, 19, and 88 percent of the total basin area, respectively, provided the primary model-calibration points. Hydrographs, scatter plots, and flow-duration curves of observed and simulated discharges, along with various model-fit statistics, indicated that the model performed well over a range of hydrologic conditions. For example, the total runoff volume for the calibration period simulated at the Nipmuc River near Harrisville, Rhode Island; Quinsigamond River at North Grafton, Massachusetts; Branch River at Forestdale, Rhode Island; and Blackstone River at Woonsocket, Rhode Island streamflow-gaging stations differed from the observed runoff v

  9. Thermodynamics Prediction of Wax Precipitation in Black Oil Using Regular Solution Model and Plus Fraction Characterization

    Directory of Open Access Journals (Sweden)

    Wei Wang

    2013-01-01

    Full Text Available The precipitation of wax/solid paraffin during production, transportation, and processing of crude oil is a serious problem. It is essential to have a reliable model to predict the wax appearance temperature and the amount of solid precipitated at different conditions. This paper presents a work to predict the solid precipitation based on solid-liquid equilibrium with regular solution-molecular thermodynamic theory and characterization of the crude oil plus fraction. Due to the differences of solubility characteristics between solid and liquid phase, the solubility parameters of liquid and solid phase are calculated by a modified model. The heat capacity change between solid and liquid phase is considered and estimated in the thermodynamic model. An activity coefficient based thermodynamic method combined with two characteristic methods to calculate wax precipitation in crude oil, especially heavy oil, has been tested with experimental data. The results show that the wax appearance temperature and the amount of weight precipitated can be predicted well with the experimental data.

  10. A new approach for assimilation of two-dimensional radar precipitation in a high resolution NWP model

    Science.gov (United States)

    Korsholm, Ulrik; Petersen, Claus; Hansen Sass, Bent; Woetman, Niels; Getreuer Jensen, David; Olsen, Bjarke Tobias; GIll, Rasphal; Vedel, Henrik

    2014-05-01

    The DMI nowcasting system has been running in a pre-operational state for the past year. The system consists of hourly simulations with the High Resolution Limited Area weather model combined with surface and three-dimensional variational assimilation at each restart and nudging of satellite cloud products and radar precipitation. Nudging of a two-dimensional radar reflectivity CAPPI product is achieved using a new method where low level horizontal divergence is nudged towards pseudo observations. Pseudo observations are calculated based on an assumed relation between divergence and precipitation rate and the strength of the nudging is proportional to the offset between observed and modelled precipitation leading to increased moisture convergence below cloud base if there is an under-production of precipitation relative to the CAPPI product. If the model over-predicts precipitation, the low level moisture source is reduced, and in-cloud moisture is nudged towards environmental values. In this talk results will be discussed based on calculation of the fractions skill score in cases with heavy precipitation over Denmark. Furthermore, results from simulations combining reflectivity nudging and extrapolation of reflectivity will be shown. Results indicate that the new method leads to fast adjustment of the dynamical state of the model to facilitate precipitation release when the model precipitation intensity is too low. Removal of precipitation is also shown to be of importance and strong improvements were found in the position of the precipitation systems. Bias is reduced for low and extreme precipitation rates.

  11. A generalised chemical precipitation modelling approach in wastewater treatment applied to calcite

    DEFF Research Database (Denmark)

    Mbamba, Christian Kazadi; Batstone, Damien J.; Flores Alsina, Xavier

    2015-01-01

    , the present study aims to identify a broadly applicable precipitation modelling approach. The study uses two experimental platforms applied to calcite precipitating from synthetic aqueous solutions to identify and validate the model approach. Firstly, dynamic pH titration tests are performed to define...... an Arrhenius-style correction of kcryst. The influence of magnesium (a common and representative added impurity) on kcryst was found to be significant but was considered an optional correction because of a lesser influence as compared to that of temperature. Other variables such as ionic strength and pH were...

  12. Entropy Characterization of Random Network Models

    Directory of Open Access Journals (Sweden)

    Pedro J. Zufiria

    2017-06-01

    Full Text Available This paper elaborates on the Random Network Model (RNM as a mathematical framework for modelling and analyzing the generation of complex networks. Such framework allows the analysis of the relationship between several network characterizing features (link density, clustering coefficient, degree distribution, connectivity, etc. and entropy-based complexity measures, providing new insight on the generation and characterization of random networks. Some theoretical and computational results illustrate the utility of the proposed framework.

  13. The model of social crypto-network

    Directory of Open Access Journals (Sweden)

    Марк Миколайович Орел

    2015-06-01

    Full Text Available The article presents the theoretical model of social network with the enhanced mechanism of privacy policy. It covers the problems arising in the process of implementing the mentioned type of network. There are presented the methods of solving problems arising in the process of building the social network with privacy policy. It was built a theoretical model of social networks with enhanced information protection methods based on information and communication blocks

  14. Introducing Synchronisation in Deterministic Network Models

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Jessen, Jan Jakob; Nielsen, Jens Frederik D.

    2006-01-01

    The paper addresses performance analysis for distributed real time systems through deterministic network modelling. Its main contribution is the introduction and analysis of models for synchronisation between tasks and/or network elements. Typical patterns of synchronisation are presented leading...... to the suggestion of suitable network models. An existing model for flow control is presented and an inherent weakness is revealed and remedied. Examples are given and numerically analysed through deterministic network modelling. Results are presented to highlight the properties of the suggested models...

  15. Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

    Science.gov (United States)

    Beranová, Romana; Kyselý, Jan; Hanel, Martin

    2018-04-01

    The study compares characteristics of observed sub-daily precipitation extremes in the Czech Republic with those simulated by Hadley Centre Regional Model version 3 (HadRM3) and Rossby Centre Regional Atmospheric Model version 4 (RCA4) regional climate models (RCMs) driven by reanalyses and examines diurnal cycles of hourly precipitation and their dependence on intensity and surface temperature. The observed warm-season (May-September) maxima of short-duration (1, 2 and 3 h) amounts show one diurnal peak in the afternoon, which is simulated reasonably well by RCA4, although the peak occurs too early in the model. HadRM3 provides an unrealistic diurnal cycle with a nighttime peak and an afternoon minimum coinciding with the observed maximum for all three ensemble members, which suggests that convection is not captured realistically. Distorted relationships of the diurnal cycles of hourly precipitation to daily maximum temperature in HadRM3 further evidence that underlying physical mechanisms are misrepresented in this RCM. Goodness-of-fit tests indicate that generalised extreme value distribution is an applicable model for both observed and RCM-simulated precipitation maxima. However, the RCMs are not able to capture the range of the shape parameter estimates of distributions of short-duration precipitation maxima realistically, leading to either too many (nearly all for HadRM3) or too few (RCA4) grid boxes in which the shape parameter corresponds to a heavy tail. This means that the distributions of maxima of sub-daily amounts are distorted in the RCM-simulated data and do not match reality well. Therefore, projected changes of sub-daily precipitation extremes in climate change scenarios based on RCMs not resolving convection need to be interpreted with caution.

  16. Bivariate spatial analysis of temperature and precipitation from general circulation models and observation proxies

    KAUST Repository

    Philbin, R.

    2015-05-22

    This study validates the near-surface temperature and precipitation output from decadal runs of eight atmospheric ocean general circulation models (AOGCMs) against observational proxy data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis temperatures and Global Precipitation Climatology Project (GPCP) precipitation data. We model the joint distribution of these two fields with a parsimonious bivariate Matérn spatial covariance model, accounting for the two fields\\' spatial cross-correlation as well as their own smoothnesses. We fit output from each AOGCM (30-year seasonal averages from 1981 to 2010) to a statistical model on each of 21 land regions. Both variance and smoothness values agree for both fields over all latitude bands except southern mid-latitudes. Our results imply that temperature fields have smaller smoothness coefficients than precipitation fields, while both have decreasing smoothness coefficients with increasing latitude. Models predict fields with smaller smoothness coefficients than observational proxy data for the tropics. The estimated spatial cross-correlations of these two fields, however, are quite different for most GCMs in mid-latitudes. Model correlation estimates agree well with those for observational proxy data for Australia, at high northern latitudes across North America, Europe and Asia, as well as across the Sahara, India, and Southeast Asia, but elsewhere, little consistent agreement exists.

  17. Bivariate spatial analysis of temperature and precipitation from general circulation models and observation proxies

    KAUST Repository

    Philbin, R.; Jun, M.

    2015-01-01

    This study validates the near-surface temperature and precipitation output from decadal runs of eight atmospheric ocean general circulation models (AOGCMs) against observational proxy data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis temperatures and Global Precipitation Climatology Project (GPCP) precipitation data. We model the joint distribution of these two fields with a parsimonious bivariate Matérn spatial covariance model, accounting for the two fields' spatial cross-correlation as well as their own smoothnesses. We fit output from each AOGCM (30-year seasonal averages from 1981 to 2010) to a statistical model on each of 21 land regions. Both variance and smoothness values agree for both fields over all latitude bands except southern mid-latitudes. Our results imply that temperature fields have smaller smoothness coefficients than precipitation fields, while both have decreasing smoothness coefficients with increasing latitude. Models predict fields with smaller smoothness coefficients than observational proxy data for the tropics. The estimated spatial cross-correlations of these two fields, however, are quite different for most GCMs in mid-latitudes. Model correlation estimates agree well with those for observational proxy data for Australia, at high northern latitudes across North America, Europe and Asia, as well as across the Sahara, India, and Southeast Asia, but elsewhere, little consistent agreement exists.

  18. Schottky effect model of electrical activity of metallic precipitates in silicon

    International Nuclear Information System (INIS)

    Plekhanov, P. S.; Tan, T. Y.

    2000-01-01

    A quantitative model of the electrical activity of metallic precipitates in Si is formulated with an emphasis on the Schottky junction effects of the precipitate-Si system. Carrier diffusion and carrier drift in the Si space charge region are accounted for. Carrier recombination is attributed to the thermionic emission mechanism of charge transport across the Schottky junction rather than the surface recombination. It is shown that the precipitates can have a very large minority carrier capture cross-section. Under weak carrier generation conditions, the supply of minority carriers is found to be the limiting factor of the recombination process. The plausibility of the model is demonstrated by a comparison of calculated and available experimental results. (c) 2000 American Institute of Physics

  19. Assessment of the Effects of Various Precipitation Forcings on Flood Forecasting Potential Using WRF-Hydro Modeling

    Science.gov (United States)

    Zhang, J.; Fang, N. Z.

    2017-12-01

    A potential flood forecast system is under development for the Upper Trinity River Basin (UTRB) in North Central of Texas using the WRF-Hydro model. The Routing Application for the Parallel Computation of Discharge (RAPID) is utilized as channel routing module to simulate streamflow. Model performance analysis was conducted based on three quantitative precipitation estimates (QPE): the North Land Data Assimilation System (NLDAS) rainfall, the Multi-Radar Multi-Sensor (MRMS) QPE and the National Centers for Environmental Prediction (NCEP) quality-controlled stage IV estimates. Prior to hydrologic simulation, QPE performance is assessed on two time scales (daily and hourly) using the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) and Hydrometeorological Automated Data System (HADS) hourly products. The calibrated WRF-Hydro model was then evaluated by comparing the simulated against the USGS observed using various QPE products. The results imply that the NCEP stage IV estimates have the best accuracy among the three QPEs on both time scales, while the NLDAS rainfall performs poorly because of its coarse spatial resolution. Furthermore, precipitation bias demonstrates pronounced impact on flood forecasting skills, as the root mean squared errors are significantly reduced by replacing NLDAS rainfall with NCEP stage IV estimates. This study also demonstrates that accurate simulated results can be achieved when initial soil moisture values are well understood in the WRF-Hydro model. Future research effort will therefore be invested on incorporating data assimilation with focus on initial states of the soil properties for UTRB.

  20. Quantitative estimation of orographic precipitation over the Himalayas by using TRMM/PR and a dense network of rain gauges

    Science.gov (United States)

    Yatagai, A.

    2009-04-01

    Precipitation Radar (PR) data acquired by the Tropical Rainfall Measuring Mission (TRMM) over 10 years of observation were used to show the monthly rainfall patterns over the Himalayas. To validate and adjust these patterns, we used a dense network of rain gauges to measure daily precipitation over Nepal, Bangladesh, Bhutan, Pakistan, India, Myanmar, and China. We then compared TRMM/PR and rain gauge data in 0.05-degree grid cells (an approximately 5.5-km mesh). Compared with the rain gauge observations, the PR systematically underestimated precipitation by 28-38% in summer (July-September).Significant correlation between TRMM/PR and RG data was found for all months, but the correlation is relatively low in winter. The relationship is investigated for different elevation zones, and the PR was found to underestimate RG data in most zones, except for certain zones in February (250-1000m), March (0-1000m), and April (0-1500m). Monthly PR climatology was adjusted on the basis of monthly regressions between the two sets of data and depicted.

  1. Bayesian Network Webserver: a comprehensive tool for biological network modeling.

    Science.gov (United States)

    Ziebarth, Jesse D; Bhattacharya, Anindya; Cui, Yan

    2013-11-01

    The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships. BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW). ycui2@uthsc.edu. Supplementary data are available at Bioinformatics online.

  2. Multiscale modeling of θ' precipitation in Al-Cu binary alloys

    International Nuclear Information System (INIS)

    Vaithyanathan, V.; Wolverton, C.; Chen, L.Q.

    2004-01-01

    We present a multiscale model for studying the growth and coarsening of θ' precipitates in Al-Cu alloys. Our approach utilizes a novel combination of the mesoscale phase-field method with atomistic approaches such as first-principles total energy and linear response calculations, as well as a mixed-space cluster expansion coupled with Monte Carlo simulations. We give quantitative first-principles predictions of: (i) bulk energetics of the Al-Cu solid solution and θ ' precipitate phases, (ii) interfacial energies of the coherent and semi-coherent θ ' /Al interfaces, and (iii) stress-free misfit strains and coherency strain energies of the θ ' /Al system. These first-principles data comprise all the necessary energetic information to construct our phase-field model of microstructural evolution. Using our multiscale approach, we elucidate the effects of various energetic contributions on the equilibrium shape of θ ' precipitates, finding that both the elastic energy and interfacial energy anisotropy contributions play critical roles in determining the aspect ratio of θ ' precipitates. Additionally, we have performed a quantitative study of the morphology of two-dimensional multi-precipitate microstructures during growth and coarsening, and compared the calculated results with experimentally observed morphologies. Our multiscale first-principles/phase-field method is completely general and should therefore be applicable to a wide variety of problems in microstructural evolution

  3. In Silico Modeling Approach for the Evaluation of Gastrointestinal Dissolution, Supersaturation, and Precipitation of Posaconazole.

    Science.gov (United States)

    Hens, Bart; Pathak, Shriram M; Mitra, Amitava; Patel, Nikunjkumar; Liu, Bo; Patel, Sanjaykumar; Jamei, Masoud; Brouwers, Joachim; Augustijns, Patrick; Turner, David B

    2017-12-04

    The aim of this study was to evaluate gastrointestinal (GI) dissolution, supersaturation, and precipitation of posaconazole, formulated as an acidified (pH 1.6) and neutral (pH 7.1) suspension. A physiologically based pharmacokinetic (PBPK) modeling and simulation tool was applied to simulate GI and systemic concentration-time profiles of posaconazole, which were directly compared with intraluminal and systemic data measured in humans. The Advanced Dissolution Absorption and Metabolism (ADAM) model of the Simcyp Simulator correctly simulated incomplete gastric dissolution and saturated duodenal concentrations of posaconazole in the duodenal fluids following administration of the neutral suspension. In contrast, gastric dissolution was approximately 2-fold higher after administration of the acidified suspension, which resulted in supersaturated concentrations of posaconazole upon transfer to the upper small intestine. The precipitation kinetics of posaconazole were described by two precipitation rate constants, extracted by semimechanistic modeling of a two-stage medium change in vitro dissolution test. The 2-fold difference in exposure in the duodenal compartment for the two formulations corresponded with a 2-fold difference in systemic exposure. This study demonstrated for the first time predictive in silico simulations of GI dissolution, supersaturation, and precipitation for a weakly basic compound in part informed by modeling of in vitro dissolution experiments and validated via clinical measurements in both GI fluids and plasma. Sensitivity analysis with the PBPK model indicated that the critical supersaturation ratio (CSR) and second precipitation rate constant (sPRC) are important parameters of the model. Due to the limitations of the two-stage medium change experiment the CSR was extracted directly from the clinical data. However, in vitro experiments with the BioGIT transfer system performed after completion of the in silico modeling provided an almost

  4. Modelling the potential impacts of afforestation on extreme precipitation over West Africa

    Science.gov (United States)

    Odoulami, Romaric C.; Abiodun, Babatunde J.; Ajayi, Ayodele E.

    2018-05-01

    This study examines how afforestation in West Africa could influence extreme precipitation over the region, with a focus on widespread extreme rainfall events (WEREs) over the afforestation area. Two regional climate models (RegCM and WRF) were applied to simulate the present-day climate (1971-2000) and future climate (2031-2060, under IPCC RCP 4.5 emission scenario) with and without afforestation of the Savannah zone in West Africa. The models give a realistic simulation of precipitation indices and WEREs over the subcontinent. On average, the regional models projected future decreases in total annual wet day precipitation (PRCPTOT) and total annual daily precipitation greater than or equal to the 95th percentile of daily precipitation threshold (R95pTOT) and increases in maximum number of consecutive dry days (CDD) over Sahel. Over Savannah, the models projected decreases in PRCPTOT but increases in R95pTOT and CDD. Also, an increase in WEREs frequency is projected over west, central and east Savannah, except that RegCM simulated a decrease in WEREs over east Savannah. In general, afforestation increases PRCPTOT and R95pTOT but decreases CDD over the afforestation area. The forest-induced increases in PRCPTOT and decreases in CDD affect all ecological zones in West Africa. However, the simulations show that afforestation of Savannah also decreases R95pTOT over the Guinea Coast. It further increases WEREs over west and central Savannah and decreases them over east Savannah because of the local decrease in R95pTOT. Results of this study suggest that the future changes in characteristics of extreme precipitation events over West Africa are sensitive to the ongoing land modification.

  5. Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

    Science.gov (United States)

    Zhou, C.; Zhang, X.; Gong, S.; Wang, Y.; Xue, M.

    2016-01-01

    A comprehensive aerosol-cloud-precipitation interaction (ACI) scheme has been developed under a China Meteorological Administration (CMA) chemical weather modeling system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified Atmospheric Chemistry Environment). Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN) are interactively fed online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme - WDM6) and a convective parameterization to drive cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred.The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.

  6. Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

    Directory of Open Access Journals (Sweden)

    C. Zhou

    2016-01-01

    Full Text Available A comprehensive aerosol–cloud–precipitation interaction (ACI scheme has been developed under a China Meteorological Administration (CMA chemical weather modeling system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified Atmospheric Chemistry Environment. Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN are interactively fed online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme – WDM6 and a convective parameterization to drive cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred.The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.

  7. Changes and Attribution of Extreme Precipitation in Climate Models: Subdaily and Daily Scales

    Science.gov (United States)

    Zhang, W.; Villarini, G.; Scoccimarro, E.; Vecchi, G. A.

    2017-12-01

    Extreme precipitation events are responsible for numerous hazards, including flooding, soil erosion, and landslides. Because of their significant socio-economic impacts, the attribution and projection of these events is of crucial importance to improve our response, mitigation and adaptation strategies. Here we present results from our ongoing work.In terms of attribution, we use idealized experiments [pre-industrial control experiment (PI) and 1% per year increase (1%CO2) in atmospheric CO2] from ten general circulation models produced under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and the fraction of attributable risk to examine the CO2 effects on extreme precipitation at the sub-daily and daily scales. We find that the increased CO2 concentration substantially increases the odds of the occurrence of sub-daily precipitation extremes compared to the daily scale in most areas of the world, with the exception of some regions in the sub-tropics, likely in relation to the subsidence of the Hadley Cell. These results point to the large role that atmospheric CO2 plays in extreme precipitation under an idealized framework. Furthermore, we investigate the changes in extreme precipitation events with the Community Earth System Model (CESM) climate experiments using the scenarios consistent with the 1.5°C and 2°C temperature targets. We find that the frequency of annual extreme precipitation at a global scale increases in both 1.5°C and 2°C scenarios until around 2070, after which the magnitudes of the trend become much weaker or even negative. Overall, the frequency of global annual extreme precipitation is similar between 1.5°C and 2°C for the period 2006-2035, and the changes in extreme precipitation in individual seasons are consistent with those for the entire year. The frequency of extreme precipitation in the 2°C experiments is higher than for the 1.5°C experiment after the late 2030s, particularly for the period 2071-2100.

  8. Insights into mountain precipitation and snowpack from a basin-scale wireless-sensor network

    Science.gov (United States)

    A spatially distributed wireless-sensor network, installed across the 2154 km2 portion of the 5311 km2 American River basin above 1500 m elevation, provided spatial measurements of temperature, relative humidity and snow depth. The network consisted of 10 sensor clusters, each with 10 measurement no...

  9. Geochemical models of the precipitation of halite (NaCl) in gas fields

    International Nuclear Information System (INIS)

    Lombana O, Jose L; Jaramillo, Elizabeth A; Alzate E, Guillermo A

    2005-01-01

    The reservoir modeling is a tool that every day takes more importance in the petroleum industry due to multiple problems presented an also that can be afforded by it during the production of reservoir fluids from the porous media in petroleum reservoir. One of these is the formation damage which is reflected as a petrophysic properties change, caused among other factors by the scale precipitation of halite (NaCl) as a consequence of the original state alteration and thermodynamic balance disruption between the porous media and the fluids inside by the gas flow. By the gas flow over the connate water, the porous media reduce its water saturation due to water transferring from liquid to gas state. In this study, a numeric model is developed to model the formation damage for halite precipitation. The model covers one-dimensional monophasic and iso thermic gas flow and evaluates the porosity and permeability changes of porous media due to halite precipitation. The model application for different conditions of temperature, connate water salinity, water saturation,and porosity indicates the following: the biggest damage is caused to the beginning of the porous media,temperature influences considerably the water vaporization rate and therefore the amount of halite precipitation, the lower the porosity of the porous media the bigger the formation damage degree, and finally, higher salinity and water saturation for the connate water in the porous media higher the formation damage degree is reached by the gas flow.

  10. Multisite stochastic simulation of daily precipitation from copula modeling with a gamma marginal distribution

    Science.gov (United States)

    Lee, Taesam

    2018-05-01

    Multisite stochastic simulations of daily precipitation have been widely employed in hydrologic analyses for climate change assessment and agricultural model inputs. Recently, a copula model with a gamma marginal distribution has become one of the common approaches for simulating precipitation at multiple sites. Here, we tested the correlation structure of the copula modeling. The results indicate that there is a significant underestimation of the correlation in the simulated data compared to the observed data. Therefore, we proposed an indirect method for estimating the cross-correlations when simulating precipitation at multiple stations. We used the full relationship between the correlation of the observed data and the normally transformed data. Although this indirect method offers certain improvements in preserving the cross-correlations between sites in the original domain, the method was not reliable in application. Therefore, we further improved a simulation-based method (SBM) that was developed to model the multisite precipitation occurrence. The SBM preserved well the cross-correlations of the original domain. The SBM method provides around 0.2 better cross-correlation than the direct method and around 0.1 degree better than the indirect method. The three models were applied to the stations in the Nakdong River basin, and the SBM was the best alternative for reproducing the historical cross-correlation. The direct method significantly underestimates the correlations among the observed data, and the indirect method appeared to be unreliable.

  11. A meteo-hydrological prediction system based on a multi-model approach for precipitation forecasting

    Directory of Open Access Journals (Sweden)

    S. Davolio

    2008-02-01

    Full Text Available The precipitation forecasted by a numerical weather prediction model, even at high resolution, suffers from errors which can be considerable at the scales of interest for hydrological purposes. In the present study, a fraction of the uncertainty related to meteorological prediction is taken into account by implementing a multi-model forecasting approach, aimed at providing multiple precipitation scenarios driving the same hydrological model. Therefore, the estimation of that uncertainty associated with the quantitative precipitation forecast (QPF, conveyed by the multi-model ensemble, can be exploited by the hydrological model, propagating the error into the hydrological forecast.

    The proposed meteo-hydrological forecasting system is implemented and tested in a real-time configuration for several episodes of intense precipitation affecting the Reno river basin, a medium-sized basin located in northern Italy (Apennines. These episodes are associated with flood events of different intensity and are representative of different meteorological configurations responsible for severe weather affecting northern Apennines.

    The simulation results show that the coupled system is promising in the prediction of discharge peaks (both in terms of amount and timing for warning purposes. The ensemble hydrological forecasts provide a range of possible flood scenarios that proved to be useful for the support of civil protection authorities in their decision.

  12. Tropical intercontinental optical measurement network of aerosol, precipitable water and total column ozone

    Science.gov (United States)

    Holben, B. N.; Tanre, D.; Reagan, J. A.; Eck, T. F.; Setzer, A.; Kaufman, Y. A.; Vermote, E.; Vassiliou, G. D.; Lavenu, F.

    1992-01-01

    A new generation of automatic sunphotometers is used to systematically monitor clear sky total column aerosol concentration and optical properties, precipitable water and total column ozone diurnally and annually in West Africa and South America. The instruments are designed to measure direct beam sun, solar aureole and sky radiances in nine narrow spectral bands from the UV to the near infrared on an hourly basis. The instrumentation and the algorithms required to reduce the data for subsequent analysis are described.

  13. Modelling and Mapping Oxygen-18 Isotope Composition of Precipitation in Spain for Hydrologic and Climatic Applications

    Energy Technology Data Exchange (ETDEWEB)

    Rodriguez-Arevalo, J.; Diaz-Teijeiro, M. F. [Centro de Estudios y Experimentacion de Obras Publicas (CEDEX), Madrid (Spain); Castano, S. [Geological Survey of Spain (IGME), Madrid (Spain)

    2013-07-15

    A simple multiple regression model based on two geographic factors (latitude and elevation) has been developed that reproduces reasonably well the spatial distribution of the current mean oxygen-18 isotope composition in precipitation over spain. In a preliminary analysis, additional geographic and climatic factors do not improve the performance of the model. A continuous digital map of oxygen-18 isotope composition in precipitation has been produced by combining the polynomial model with a digital elevation model using GIS tools. Application of the resulting map to several groundwater case studies in spain has shown it to be useful as a reference of the input function to recharge. Further validation of the model, and further testing of its usefulness in surface hydrology and climatic studies, is ongoing through comparison of model results with isotope data from the GNIP database and from isotope studies in hydrogeology and climate change taking place in spain. (author)

  14. Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

    Science.gov (United States)

    Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

    2011-01-01

    In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to

  15. Modeling the effects of ion dose and crystallographic symmetry on the morphological evolution of embedded precipitates under thermal annealing

    International Nuclear Information System (INIS)

    Li, Kun-Dar

    2014-01-01

    Highlights: •We model the faceted precipitates formation by post-implantation annealing. •The anisotropic interfacial energy and diffusion kinetics play crucial roles. •The evolutions of faceted precipitates, including Ostwald ripening, are revealed. •The mechanism of the nucleation and growth is based on the atomic diffusion. •The effects of ion dose and crystallographic symmetry are also investigated. -- Abstract: Thermal annealing is one of the most common techniques to synthesize embedded precipitates by ion implantation process. In this study, an anisotropic phase field model is presented to investigate the effects of ion dose and crystallographic symmetry on the morphological formation and evolution of embedded precipitates during post-implantation thermal annealing process. This theoretical model provides an efficient numerical approach to understand the phenomenon of faceted precipitates formation by ion implantation. As a theoretical analysis, the interfacial energy and diffusion kinetics play prominent roles in the mechanism of atomic diffusion for the precipitates formation. With a low ion dose, faceted precipitates are developed by virtue of the anisotropic interfacial energy. As an increase of ion dose, connected precipitates with crystallographic characters on the edge are appeared. For a high ion dose, labyrinth-like nanostructures of precipitates are produced and the characteristic morphology of crystallographic symmetry becomes faint. These simulation results for the morphological evolutions of embedded precipitates by ion implantation are corresponded with many experimental observations in the literatures. The quantitative analyses of the simulations are also well described the consequence of precipitates formation under different conditions

  16. Climate change scenarios of precipitation extremes in Central Europe from ENSEMBLES regional climate models

    Czech Academy of Sciences Publication Activity Database

    Gaál, Ľ.; Beranová, R.; Hlavčová, K.; Kyselý, Jan

    2014-01-01

    Roč. 2014, č. 943487 (2014), s. 1-14 ISSN 1687-9309 Institutional support: RVO:67179843 ; RVO:68378289 Keywords : precipitation extremes * regional climate models * climate change Subject RIV: EH - Ecology, Behaviour Impact factor: 0.946, year: 2014

  17. Use of remotely sensed precipitation and leaf area index in a distributed hydrological model

    DEFF Research Database (Denmark)

    Andersen, J.; Dybkjær, G.; Jensen, Karsten Høgh

    2002-01-01

    Remotely sensed precipitation from METEOSAT data and leaf area index (LAI) from NOAA AVHRR data is used as input data to the distributed hydrological modelling of three sub catchments (82.000 km(2)) in the Senegal River Basin. Further, root depths of annual vegetation are related to the temporal...

  18. GLUE Based Uncertainty Estimation of Urban Drainage Modeling Using Weather Radar Precipitation Estimates

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2011-01-01

    Distributed weather radar precipitation measurements are used as rainfall input for an urban drainage model, to simulate the runoff from a small catchment of Denmark. It is demonstrated how the Generalized Likelihood Uncertainty Estimation (GLUE) methodology can be implemented and used to estimate...

  19. Multivariate Regression Analysis and Statistical Modeling for Summer Extreme Precipitation over the Yangtze River Basin, China

    Directory of Open Access Journals (Sweden)

    Tao Gao

    2014-01-01

    Full Text Available Extreme precipitation is likely to be one of the most severe meteorological disasters in China; however, studies on the physical factors affecting precipitation extremes and corresponding prediction models are not accurately available. From a new point of view, the sensible heat flux (SHF and latent heat flux (LHF, which have significant impacts on summer extreme rainfall in Yangtze River basin (YRB, have been quantified and then selections of the impact factors are conducted. Firstly, a regional extreme precipitation index was applied to determine Regions of Significant Correlation (RSC by analyzing spatial distribution of correlation coefficients between this index and SHF, LHF, and sea surface temperature (SST on global ocean scale; then the time series of SHF, LHF, and SST in RSCs during 1967–2010 were selected. Furthermore, other factors that significantly affect variations in precipitation extremes over YRB were also selected. The methods of multiple stepwise regression and leave-one-out cross-validation (LOOCV were utilized to analyze and test influencing factors and statistical prediction model. The correlation coefficient between observed regional extreme index and model simulation result is 0.85, with significant level at 99%. This suggested that the forecast skill was acceptable although many aspects of the prediction model should be improved.

  20. Local control on precipitation in a fully coupled climate-hydrology model.

    Science.gov (United States)

    Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C

    2016-03-10

    The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

  1. How to model wireless mesh networks topology

    International Nuclear Information System (INIS)

    Sanni, M L; Hashim, A A; Anwar, F; Ali, S; Ahmed, G S M

    2013-01-01

    The specification of network connectivity model or topology is the beginning of design and analysis in Computer Network researches. Wireless Mesh Networks is an autonomic network that is dynamically self-organised, self-configured while the mesh nodes establish automatic connectivity with the adjacent nodes in the relay network of wireless backbone routers. Researches in Wireless Mesh Networks range from node deployment to internetworking issues with sensor, Internet and cellular networks. These researches require modelling of relationships and interactions among nodes including technical characteristics of the links while satisfying the architectural requirements of the physical network. However, the existing topology generators model geographic topologies which constitute different architectures, thus may not be suitable in Wireless Mesh Networks scenarios. The existing methods of topology generation are explored, analysed and parameters for their characterisation are identified. Furthermore, an algorithm for the design of Wireless Mesh Networks topology based on square grid model is proposed in this paper. The performance of the topology generated is also evaluated. This research is particularly important in the generation of a close-to-real topology for ensuring relevance of design to the intended network and validity of results obtained in Wireless Mesh Networks researches

  2. Model checking mobile ad hoc networks

    NARCIS (Netherlands)

    Ghassemi, Fatemeh; Fokkink, Wan

    2016-01-01

    Modeling arbitrary connectivity changes within mobile ad hoc networks (MANETs) makes application of automated formal verification challenging. We use constrained labeled transition systems as a semantic model to represent mobility. To model check MANET protocols with respect to the underlying

  3. Structural changes in precipitates and cell model for the conversion of amorphous calcium phosphate to hydroxyapatite during the initial stage of precipitation

    Science.gov (United States)

    Zyman, Z.; Rokhmistrov, D.; Glushko, V.

    2012-08-01

    A new insight on the conversion of an amorphous calcium phosphate, ACP, to hydroxyapatite, HA, has been proposed. The ACP has been precipitated under appropriate conditions of the nitrous method (low concentrations of reactants, pH>10, 25 °С, fast mixing). The ACP to HA conversion has been found to commence immediately after the ACP precipitation. The conversion reveals itself in the first detected shift of the diffuse maximum from 29.5° 2θ (ACP) to about 32° 2θ (the position of principal peaks of HA) in the XRD patterns for the precipitates of 2 min-6 h lifetimes. The precipitates are biphasic mixtures of ACP and nanocrystalline HA, nHA, with increasing nHA/ACP ratio for longer lifetimes. Characteristics of the simulated XRD profiles calculated proceeding on such a picture are excellently confirmed by experimental results. At the end of the conversion, HA nanocrystals start growing. This follows from the appearance of broadened diffraction maxima, which gradually sharpen, along with the appearance and gradual increase of splitting of the initially featureless υ3 and υ4PO43- bands in the IR spectra of precipitates with their aging (after 6 h of the precipitation). Based on the detected structural and compositional peculiarities of ACP in the early stage of precipitation, a cell model for the HA crystallization has been proposed. Proceeding on the model, the principal data in this and earlier studies, considering the ACP to HA conversion as an internal rearrangement process in the ACP particles, has been reasonably explained.

  4. Agent-based modeling and network dynamics

    CERN Document Server

    Namatame, Akira

    2016-01-01

    The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...

  5. Model Consistent Pseudo-Observations of Precipitation and Their Use for Bias Correcting Regional Climate Models

    Directory of Open Access Journals (Sweden)

    Peter Berg

    2015-01-01

    Full Text Available Lack of suitable observational data makes bias correction of high space and time resolution regional climate models (RCM problematic. We present a method to construct pseudo-observational precipitation data bymerging a large scale constrained RCMreanalysis downscaling simulation with coarse time and space resolution observations. The large scale constraint synchronizes the inner domain solution to the driving reanalysis model, such that the simulated weather is similar to observations on a monthly time scale. Monthly biases for each single month are corrected to the corresponding month of the observational data, and applied to the finer temporal resolution of the RCM. A low-pass filter is applied to the correction factors to retain the small spatial scale information of the RCM. The method is applied to a 12.5 km RCM simulation and proven successful in producing a reliable pseudo-observational data set. Furthermore, the constructed data set is applied as reference in a quantile mapping bias correction, and is proven skillful in retaining small scale information of the RCM, while still correcting the large scale spatial bias. The proposed method allows bias correction of high resolution model simulations without changing the fine scale spatial features, i.e., retaining the very information required by many impact models.

  6. Evaluation of modeled changes in extreme precipitation in Europe and the Rhine basin

    International Nuclear Information System (INIS)

    Haren, Ronald van; Oldenborgh, Geert Jan van; Lenderink, Geert; Hazeleger, Wilco

    2013-01-01

    In this study, we investigate the change in multi-day precipitation extremes in late winter in Europe using observations and climate models. The objectives of the analysis are to determine whether climate models can accurately reproduce observed trends and, if not, to find the causes of the difference in trends. Similarly to an earlier finding for mean precipitation trends, and despite a lower signal to noise ratio, climate models fail to reproduce the increase in extremes in much of northern Europe: the model simulations do not cover the observed trend in large parts of this area. A dipole in the sea-level pressure trend over continental Europe causes positive trends in extremes in northern Europe and negative trends in the Iberian Peninsula. Climate models have a much weaker pressure trend dipole and as a result a much weaker (extreme) precipitation response. The inability of climate models to correctly simulate observed changes in atmospheric circulation is also primarily responsible for the underestimation of trends in the Rhine basin. When it has been adjusted for the circulation trend mismatch, the observed trend is well within the spread of the climate model simulations. Therefore, it is important that we improve our understanding of circulation changes, in particular related to the cause of the apparent mismatch between observed and modeled circulation trends over the past century. (letter)

  7. A Semiempirical Model for Sigma-Phase Precipitation in Duplex and Superduplex Stainless Steels

    Science.gov (United States)

    Ferro, P.; Bonollo, F.

    2012-04-01

    Sigma phase is known to reduce the mechanical properties and corrosion resistance of duplex and superduplex stainless steels. Therefore, heat treatments and welding must be carefully performed so as to avoid the appearance of such a detrimental phase, and clearly, models suitable to faithfully predict σ-phase precipitation are very useful tools. Most fully analytical models are based on thermodynamic calculations whose agreement with experimental results is not always good, so that such models should be used for qualitative purposes only. Alternatively, it is possible to exploit semiempirical models, where time-temperature-transformation (TTT) diagrams are empirically determined for a given alloy and the continuous-cooling-transformation (CCT) diagram is calculated from the TTT diagram. In this work, a semiempirical model for σ-phase precipitation in duplex and superduplex stainless steels, under both isothermal and unisothermal conditions, is proposed. Model parameters are calculated from empirical data and CCT diagrams are obtained by means of the additivity rule, whereas experimental measurements for model validation are taken from the literature. This model gives a satisfactory estimation of σ-phase precipitates during both isothermal aging and the continuous cooling process.

  8. Detection of non-stationarity in precipitation extremes using a max-stable process model

    Science.gov (United States)

    Westra, S.; Sisson, S.

    2011-12-01

    The question of how extreme precipitation will change under a future climate represents an urgent research problem, not least because of the significant societal impacts that would result from an increase in precipitation-induced flooding. To better constrain future projections, an important line of evidence comes from statistical assessments of change to extreme precipitation in the observational record, as a significant amount of warming since pre-industrial times has already taken place. In this study we address this problem by applying a max-stable process model to evaluate whether extreme precipitation at sub-daily and daily timescales has changed at various locations around Australia. This max-stable process approach, which was developed to simulate spatial fields comprising observations from multiple point locations, significantly increases the precision of a statistical inference compared to standard univariate methods. Applying the technique to a field of annual maxima derived from 30 sub-daily gauges in east Australia from 1965 to 2005, we find a statistically significant increase of 18% for 6-minute rainfall over this period, with smaller increases for longer duration events. We also find an increase of 5.6% and 22.5% per degree of Australian land surface temperature and global sea surface temperature at 6-minute durations, respectively, again with smaller scaling relationships for longer durations. In contrast, limited change could be observed in daily rainfall at most locations, with the exception of a statistically significant decline of 7.4% per degree land surface temperature in southwest Western Australia. These results suggest both the importance of better understanding changes to precipitation at the sub-daily timescale, as well as the need to more precisely simulate temporal variability by accounting for the spatial nature of precipitation in any statistical model.

  9. How will precipitation change in extratropical cyclones as the planet warms? Insights from a large initial condition climate model ensemble

    Science.gov (United States)

    Yettella, Vineel; Kay, Jennifer E.

    2017-09-01

    The extratropical precipitation response to global warming is investigated within a 30-member initial condition climate model ensemble. As in observations, modeled cyclonic precipitation contributes a large fraction of extratropical precipitation, especially over the ocean and in the winter hemisphere. When compared to present day, the ensemble projects increased cyclone-associated precipitation under twenty-first century business-as-usual greenhouse gas forcing. While the cyclone-associated precipitation response is weaker in the near-future (2016-2035) than in the far-future (2081-2100), both future periods have similar patterns of response. Though cyclone frequency changes are important regionally, most of the increased cyclone-associated precipitation results from increased within-cyclone precipitation. Consistent with this result, cyclone-centric composites show statistically significant precipitation increases in all cyclone sectors. Decomposition into thermodynamic (mean cyclone water vapor path) and dynamic (mean cyclone wind speed) contributions shows that thermodynamics explains 92 and 95% of the near-future and far-future within-cyclone precipitation increases respectively. Surprisingly, the influence of dynamics on future cyclonic precipitation changes is negligible. In addition, the forced response exceeds internal variability in both future time periods. Overall, this work suggests that future cyclonic precipitation changes will result primarily from increased moisture availability in a warmer world, with secondary contributions from changes in cyclone frequency and cyclone dynamics.

  10. Doubly stochastic Poisson process models for precipitation at fine time-scales

    Science.gov (United States)

    Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao

    2012-09-01

    This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.

  11. Validation of mechanistic models for gas precipitation in solids during postirradiation annealing experiments

    Science.gov (United States)

    Rest, J.

    1989-12-01

    A number of different phenomenological models for gas precipitation in solids during postirradiation annealing experiments have been proposed. Validation of such mechanistic models for gas release and swelling is complicated by the use of data containing large systematic errors, and phenomena characterized by synergistic effects as well as uncertainties in materials properties. Statistical regression analysis is recommended for the selection of a reasonably well characterized data base for gas release from irradiated fuel under transient heating conditions. It is demonstrated that an appropriate data selection method is required in order to realistically examine the impact of differing descriptions of the phenomena, and uncertainties in selected materials properties, on the validation results. The results of the analysis show that the kinetics of gas precipitation in solids depend on bubble overpressurization effects and need to be accounted for during the heatup phase of isothermal heating experiments. It is shown that if only the total gas release values (as opposed to time-dependent data) were available, differentiation between different gas precipitation models would be ambiguous. The observed sustained increase in the fractional release curve at relatively high temperatures after the total precipitation of intragranular gas in fission gas bubbles is ascribed to the effects of a grain-growth/grain-boundary sweeping mechanism.

  12. Validation of mechanistic models for gas precipitation in solids during postirradiation annealing experiments

    International Nuclear Information System (INIS)

    Rest, J.

    1989-01-01

    A number of different phenomenological models for gas precipitation in solids during postirradiation annealing experiments have been proposed. Validation of such mechanistic models for gas release and swelling is complicated by the use of data containing large systematic errors, and phenomena characterized by synergistic effects as well as uncertainties in materials properties. Statistical regression analysis is recommended for the selection of a reasonably well characterized data base for gas release from irradiated fuel under transient heating conditions. It is demonstrated that an appropriate data selection method is required in order to realistically examine the impact of differing descriptions of the phenomena, and uncertainties in selected materials properties, on the validation results. The results of the analysis show that the kinetics of gas precipitation in solid depend on bubble overpressurization effects and need to be accounted for during the heatup phase of isothermal heating experiments. It is shown that if only the total gas release values (as opposed to time-dependent data) were available, differentiation between different gas precipitation models would be ambiguous. The observed sustained increase in the fractional release curve at relatively high temperatures after the total precipitation of intragranular gas in fission gas bubbles is ascribed to the effects of a grain-growth/grain-boundary sweeping mechanism. (orig.)

  13. Nonparametric Bayesian Modeling of Complex Networks

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard; Mørup, Morten

    2013-01-01

    an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...

  14. Mathematical modelling of brittle phase precipitation in complex ruthenium containing nickel-based superalloys

    International Nuclear Information System (INIS)

    Rettig, Ralf

    2010-01-01

    A new model has been developed in this work which is capable of simulating the precipitation kinetics of brittle phases, especially TCP-phases (topologically close packed phases) in ruthenium containing superalloys. The model simultaneously simulates the nucleation and the growth stage of precipitation for any number of precipitating phases. The CALPHAD method (Calculation of Phase Diagrams) is employed to calculate thermodynamic properties, such as the driving force or phase compositions in equilibrium. For calculation of diffusion coefficients, kinetic mobility databases which are also based on the CALPHAD-method are used. The model is fully capable of handling multicomponent effects, which are common in complex superalloys. Metastable phases can be treated and will automatically be dissolved if they get unstable. As the model is based on the general CALPHAD method, it can be applied to a broad range of precipitation processes in different alloys as long as the relevant thermodynamic and kinetic databases are available. The developed model proves that the TCP-phases precipitate in a sequence of phases. The first phase that is often formed is the metastable σ-phase because it has the lowest interface energy due to low-energy planes at the interface between matrix and precipitate. After several hundred hours the stable μ- and P-phases start to precipitate by nucleating at the σ-phase which is energetically favourable. During the growth of these stable phases the sigma-phase is continuously dissolved. It can be shown by thermodynamic CALPHAD calculations that the sigma-phase has a lower Gibbs free enthalpy than the μ- and P-phase. All required parameters of the model, such as interface energy and nucleate densities, have been estimated. The mechanisms of suppression of TCP-phase precipitation in the presence of ruthenium in superalloys were investigated with the newly developed model. It is shown by the simulations that ruthenium mostly affects the nucleation

  15. Network structure exploration via Bayesian nonparametric models

    International Nuclear Information System (INIS)

    Chen, Y; Wang, X L; Xiang, X; Tang, B Z; Bu, J Z

    2015-01-01

    Complex networks provide a powerful mathematical representation of complex systems in nature and society. To understand complex networks, it is crucial to explore their internal structures, also called structural regularities. The task of network structure exploration is to determine how many groups there are in a complex network and how to group the nodes of the network. Most existing structure exploration methods need to specify either a group number or a certain type of structure when they are applied to a network. In the real world, however, the group number and also the certain type of structure that a network has are usually unknown in advance. To explore structural regularities in complex networks automatically, without any prior knowledge of the group number or the certain type of structure, we extend a probabilistic mixture model that can handle networks with any type of structure but needs to specify a group number using Bayesian nonparametric theory. We also propose a novel Bayesian nonparametric model, called the Bayesian nonparametric mixture (BNPM) model. Experiments conducted on a large number of networks with different structures show that the BNPM model is able to explore structural regularities in networks automatically with a stable, state-of-the-art performance. (paper)

  16. A phase field model for segregation and precipitation induced by irradiation in alloys

    Science.gov (United States)

    Badillo, A.; Bellon, P.; Averback, R. S.

    2015-04-01

    A phase field model is introduced to model the evolution of multicomponent alloys under irradiation, including radiation-induced segregation and precipitation. The thermodynamic and kinetic components of this model are derived using a mean-field model. The mobility coefficient and the contribution of chemical heterogeneity to free energy are rescaled by the cell size used in the phase field model, yielding microstructural evolutions that are independent of the cell size. A new treatment is proposed for point defect clusters, using a mixed discrete-continuous approach to capture the stochastic character of defect cluster production in displacement cascades, while retaining the efficient modeling of the fate of these clusters using diffusion equations. The model is tested on unary and binary alloy systems using two-dimensional simulations. In a unary system, the evolution of point defects under irradiation is studied in the presence of defect clusters, either pre-existing ones or those created by irradiation, and compared with rate theory calculations. Binary alloys with zero and positive heats of mixing are then studied to investigate the effect of point defect clustering on radiation-induced segregation and precipitation in undersaturated solid solutions. Lastly, irradiation conditions and alloy parameters leading to irradiation-induced homogeneous precipitation are investigated. The results are discussed in the context of experimental results reported for Ni-Si and Al-Zn undersaturated solid solutions subjected to irradiation.

  17. A phase field model for segregation and precipitation induced by irradiation in alloys

    International Nuclear Information System (INIS)

    Badillo, A; Bellon, P; Averback, R S

    2015-01-01

    A phase field model is introduced to model the evolution of multicomponent alloys under irradiation, including radiation-induced segregation and precipitation. The thermodynamic and kinetic components of this model are derived using a mean-field model. The mobility coefficient and the contribution of chemical heterogeneity to free energy are rescaled by the cell size used in the phase field model, yielding microstructural evolutions that are independent of the cell size. A new treatment is proposed for point defect clusters, using a mixed discrete-continuous approach to capture the stochastic character of defect cluster production in displacement cascades, while retaining the efficient modeling of the fate of these clusters using diffusion equations. The model is tested on unary and binary alloy systems using two-dimensional simulations. In a unary system, the evolution of point defects under irradiation is studied in the presence of defect clusters, either pre-existing ones or those created by irradiation, and compared with rate theory calculations. Binary alloys with zero and positive heats of mixing are then studied to investigate the effect of point defect clustering on radiation-induced segregation and precipitation in undersaturated solid solutions. Lastly, irradiation conditions and alloy parameters leading to irradiation-induced homogeneous precipitation are investigated. The results are discussed in the context of experimental results reported for Ni–Si and Al–Zn undersaturated solid solutions subjected to irradiation. (paper)

  18. Spanish Network for Isotopes in Precipitation: Isotope Spatial distribution and contribution to the knowledge of the hydrological cycle; La Red Espanola de Vigilancia de Isotopos en la Precipitacion (REVIP): distribucion isotopica espacial y aportacion al conocimiento del ciclo hidrologico

    Energy Technology Data Exchange (ETDEWEB)

    Diaz-Teijeiro, M. F.; Rodriguez-Arevalo, J.; Castano, S.

    2009-07-01

    The results of seven years of operation of the Spanish Network for Isotopes ({sup 2}H, {sup 1}8O y {sup 3}H) in Precipitation (REVIP) are shown. this Network is managed since 2000 by the Centro de Estudios de Tecnicas Aplicadas of the Centro de Estudios y Experimentacion de Obras Publicas (CEDEX) in collaboration with the Agencia Estatal de Meteorologia (AEMET). The results of REVIP are sent to the International Atomic Energy Agency (IAEA) in order to be integrated in the Global Network for Isotopes in Precipitation (GNIP). The spatial distribution of stable isotopes ({sup 1}8O h {sup 2}H) in precipitation in Spain follows a multiple regression model, based on two geographic factors: latitude and elevation, which is strongly correlated with temperature, an important factor controlling isotope fractionation. This information on {sup 1}8O and {sup 2}H is useful to trace surface and ground waters and, combined with the information, about the spatial and temporal distribution of the Tritium ({sup 3}H) concentration in precipitation, allows to date these waters in order to estimate flow directions and velocities, and to evaluate the residence time of water resources and aquifer vulnerability. (Author)

  19. Turbulent precipitation of uranium oxalate in a vortex reactor - experimental study and modelling

    International Nuclear Information System (INIS)

    Sommer de Gelicourt, Y.

    2004-03-01

    Industrial oxalic precipitation processed in an un-baffled magnetically stirred tank, the Vortex Reactor, has been studied with uranium simulating plutonium. Modelling precipitation requires a mixing model for the continuous liquid phase and the solution of population balance for the dispersed solid phase. Being chemical reaction influenced by the degree of mixing at molecular scale, that commercial CFD code does not resolve, a sub-grid scale model has been introduced: the finite mode probability density functions, and coupled with a model for the liquid energy spectrum. Evolution of the dispersed phase has been resolved by the quadrature method of moments, first used here with experimental nucleation and growth kinetics, and an aggregation kernel based on local shear rate. The promising abilities of this local approach, without any fitting constant, are strengthened by the similarity between experimental results and simulations. (author)

  20. Scaling precipitation input to spatially distributed hydrological models by measured snow distribution

    Directory of Open Access Journals (Sweden)

    Christian Vögeli

    2016-12-01

    Full Text Available Accurate knowledge on snow distribution in alpine terrain is crucial for various applicationssuch as flood risk assessment, avalanche warning or managing water supply and hydro-power.To simulate the seasonal snow cover development in alpine terrain, the spatially distributed,physics-based model Alpine3D is suitable. The model is typically driven by spatial interpolationsof observations from automatic weather stations (AWS, leading to errors in the spatial distributionof atmospheric forcing. With recent advances in remote sensing techniques, maps of snowdepth can be acquired with high spatial resolution and accuracy. In this work, maps of the snowdepth distribution, calculated from summer and winter digital surface models based on AirborneDigital Sensors (ADS, are used to scale precipitation input data, with the aim to improve theaccuracy of simulation of the spatial distribution of snow with Alpine3D. A simple method toscale and redistribute precipitation is presented and the performance is analysed. The scalingmethod is only applied if it is snowing. For rainfall the precipitation is distributed by interpolation,with a simple air temperature threshold used for the determination of the precipitation phase.It was found that the accuracy of spatial snow distribution could be improved significantly forthe simulated domain. The standard deviation of absolute snow depth error is reduced up toa factor 3.4 to less than 20 cm. The mean absolute error in snow distribution was reducedwhen using representative input sources for the simulation domain. For inter-annual scaling, themodel performance could also be improved, even when using a remote sensing dataset from adifferent winter. In conclusion, using remote sensing data to process precipitation input, complexprocesses such as preferential snow deposition and snow relocation due to wind or avalanches,can be substituted and modelling performance of spatial snow distribution is improved.

  1. Understanding SMAP-L4 soil moisture estimation skill and their dependence with topography, precipitation and vegetation type using Mesonet and Micronet networks.

    Science.gov (United States)

    Moreno, H. A.; Basara, J. B.; Thompson, E.; Bertrand, D.; Johnston, C. S.

    2017-12-01

    Soil moisture measurements using satellite information can benefit from a land data assimilation model Goddard Earth Observing System (GEOS-5) and land data assimilation system (LDAS) to improve the representation of fine-scale dynamics and variability. This work presents some advances to understand the predictive skill of L4-SM product across different land-cover types, topography and precipitation totals, by using a dense network of multi-level soil moisture sensors (i.e. Mesonet and Micronet) in Oklahoma. 130 soil moisture stations are used across different precipitation gradients (i.e. arid vs wet), land cover (e.g. forest, shrubland, grasses, crops), elevation (low, mid and high) and slope to assess the improvements by the L4_SM product relative to the raw SMAP L-band brightness temperatures. The comparisons are conducted between July 2015 and July 2016 at the daily time scale. Results show the highest L4-SM overestimations occur in pastures and cultivated crops, during the rainy season and at higher elevation lands (over 800 meters asl). The smallest errors occur in low elevation lands, low rainfall and developed lands. Forested area's soil moisture biases lie in between pastures (max biases) and low intensity/developed lands (min biases). Fine scale assessment of L4-SM should help GEOS-5 and LDAS teams refine model parameters in light of observed differences and improve assimilation techniques in light of land-cover, topography and precipitation regime. Additionally, regional decision makers could have a framework to weight the utility of this product for water resources applications.

  2. Fracture network modeling and GoldSim simulation support

    International Nuclear Information System (INIS)

    Sugita, Kenichiro; Dershowitz, William

    2004-01-01

    During Heisei-15, Golder Associates provided support for JNC Tokai through discrete fracture network data analysis and simulation of the MIU Underground Rock Laboratory, participation in Task 6 of the Aespoe Task Force on Modelling of Groundwater Flow and Transport, and development of methodologies for analysis of repository site characterization strategies and safety assessment. MIU Underground Rock Laboratory support during H-15 involved development of new discrete fracture network (DFN) models for the MIU Shoba-sama Site, in the region of shaft development. Golder developed three DFN models for the site using discrete fracture network, equivalent porous medium (EPM), and nested DFN/EPM approaches. Each of these models were compared based upon criteria established for the multiple modeling project (MMP). Golder supported JNC participation in Task 6AB, 6D and 6E of the Aespoe Task Force on Modelling of Groundwater Flow and Transport during H-15. For Task 6AB, Golder implemented an updated microstructural model in GoldSim, and used this updated model to simulate the propagation of uncertainty from experimental to safety assessment time scales, for 5 m scale transport path lengths. Task 6D and 6E compared safety assessment (PA) and experimental time scale simulations in a 200 m scale discrete fracture network. For Task 6D, Golder implemented a DFN model using FracMan/PA Works, and determined the sensitivity of solute transport to a range of material property and geometric assumptions. For Task 6E, Golder carried out demonstration FracMan/PA Works transport calculations at a 1 million year time scale, to ensure that task specifications are realistic. The majority of work for Task 6E will be carried out during H-16. During H-15, Golder supported JNC's Total System Performance Assessment (TSPO) strategy by developing technologies for the analysis of precipitant concentration. These approaches were based on the GoldSim precipitant data management features, and were

  3. A new approach for assimilation of 2D radar precipitation in a high-resolution NWP model

    DEFF Research Database (Denmark)

    Korsholm, Ulrik Smith; Petersen, Claus; Sass, Bent Hansen

    2015-01-01

    of precipitation, the strength of the nudging is proportional to the offset between observed and modelled precipitation, leading to increased moisture convergence. If the model over-predicts precipitation, the low level moisture source is reduced, and in-cloud moisture is nudged towards environmental values......A new approach for assimilation of 2D precipitation in numerical weather prediction models is presented and tested in a case with convective, heavy precipitation. In the scheme a nudging term is added to the horizontal velocity divergence tendency equation. In case of underproduction....... The method was implemented in the Danish Meteorological Institute numerical weather prediction (DMI NWP) nowcasting system, running with hourly cycles, performing a surface analysis and 3D variational analysis for upper air assimilation at each cycle restart, followed by nudging assimilation of precipitation...

  4. Gamma prime precipitation modeling and strength responses in powder metallurgy superalloys

    Science.gov (United States)

    Mao, Jian

    Precipitation-hardened nickel-based superalloys have been widely used as high temperature structural materials in gas turbine engine applications for more than 50 years. Powder metallurgy (P/M) technology was introduced as an innovative manufacturing process to overcome severe segregation and poor workability of alloys with high alloying contents. The excellent mechanical properties of P/M superalloys also depend upon the characteristic microstructures, including grain size and size distribution of gamma' precipitates. Heat treatment is the most critical processing step that has ultimate influences on the microstructure, and hence, on the mechanical properties of the materials. The main objective of this research was to study the gamma ' precipitation kinetics in various cooling circumstances and also study the strength response to the cooling history in two model alloys, Rne88DT and U720LI. The research is summarized below: (1) An experimental method was developed to allow accurate simulation and control of any desired cooling profile. Two novel cooling methods were introduced: continuous cooling and interrupt cooling. Isothermal aging was also carried out. (2) The growth and coarsening kinetics of the cooling gamma' precipitates were experimentally studied under different cooling and aging conditions, and the empirical equations were established. It was found that the cooling gamma' precipitate versus the cooling rate follows a power law. The gamma' precipitate size versus aging time obeys the LSW cube law for coarsening. (3) The strengthening of the material responses to the cooling rate and the decreasing temperature during cooling was investigated in both alloys. The tensile strength increases with the cooling rate. In addition, the non-monotonic response of strength versus interrupt temperature is of great interest. (4) An energy-driven model integrated with the classic growth and coarsen theories was successfully embedded in a computer program developed to

  5. Towards validation of the Canadian precipitation analysis (CaPA) for hydrologic modeling applications in the Canadian Prairies

    Science.gov (United States)

    Boluwade, Alaba; Zhao, K.-Y.; Stadnyk, T. A.; Rasmussen, P.

    2018-01-01

    This study presents a three-step validation technique to compare the performance of the Canadian Precipitation Analysis (CaPA) product relative to actual observation as a hydrologic forcing in regional watershed simulation. CaPA is an interpolated (6 h or 24 h accumulation) reanalysis precipitation product in near real time covering all of North America. The analysis procedure involves point-to-point (P2P) and map-to-map (M2M) comparisons, followed by proxy validation using an operational version of the WATFLOOD™ hydrologic model from 2002 to 2005 in the Lake Winnipeg Basin (LWB), Canada. The P2P technique using a Bayesian change point analysis shows that CaPA corresponds with actual observations (Canadian daily climate data, CDCD), on both an annual and seasonal basis. CaPA has the same spatial pattern, dependency and autocorrelation properties as CDCD pixel by pixel (M2M). When used as hydrologic forcing in WATFLOOD™, results indicate that CaPA is a reliable product for water resource modeling and predictions, but that the quality of CaPA data varies annually and seasonally, as does the quality of observations. CaPA proved most beneficial as a hydrologic forcing during winter seasons where observation quality is the lowest. Reanalysis products, such as CaPA, can be a reliable option in sparse network areas, and is beneficial for regional governments when the cost of new weather stations is prohibitive.

  6. A hierarchical Bayesian spatio-temporal model for extreme precipitation events

    KAUST Repository

    Ghosh, Souparno; Mallick, Bani K.

    2011-01-01

    We propose a new approach to model a sequence of spatially distributed time series of extreme values. Unlike common practice, we incorporate spatial dependence directly in the likelihood and allow the temporal component to be captured at the second level of hierarchy. Inferences about the parameters and spatio-temporal predictions are obtained via MCMC technique. The model is fitted to a gridded precipitation data set collected over 99 years across the continental U.S. © 2010 John Wiley & Sons, Ltd..

  7. A hierarchical Bayesian spatio-temporal model for extreme precipitation events

    KAUST Repository

    Ghosh, Souparno

    2011-03-01

    We propose a new approach to model a sequence of spatially distributed time series of extreme values. Unlike common practice, we incorporate spatial dependence directly in the likelihood and allow the temporal component to be captured at the second level of hierarchy. Inferences about the parameters and spatio-temporal predictions are obtained via MCMC technique. The model is fitted to a gridded precipitation data set collected over 99 years across the continental U.S. © 2010 John Wiley & Sons, Ltd..

  8. Modelling the structure of complex networks

    DEFF Research Database (Denmark)

    Herlau, Tue

    networks has been independently studied as mathematical objects in their own right. As such, there has been both an increased demand for statistical methods for complex networks as well as a quickly growing mathematical literature on the subject. In this dissertation we explore aspects of modelling complex....... The next chapters will treat some of the various symmetries, representer theorems and probabilistic structures often deployed in the modelling complex networks, the construction of sampling methods and various network models. The introductory chapters will serve to provide context for the included written...

  9. Building functional networks of spiking model neurons.

    Science.gov (United States)

    Abbott, L F; DePasquale, Brian; Memmesheimer, Raoul-Martin

    2016-03-01

    Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more realistic spiking network models. These methods raise a number of issues that warrant further theoretical and experimental study.

  10. Thermodynamic modeling and kinetics simulation of precipitate phases in AISI 316 stainless steels

    International Nuclear Information System (INIS)

    Yang, Y.; Busby, J.T.

    2014-01-01

    This work aims at utilizing modern computational microstructural modeling tools to accelerate the understanding of phase stability in austenitic steels under extended thermal aging. Using the CALPHAD approach, a thermodynamic database OCTANT (ORNL Computational Thermodynamics for Applied Nuclear Technology), including elements of Fe, C, Cr, Ni, Mn, Mo, Si, and Ti, has been developed with a focus on reliable thermodynamic modeling of precipitate phases in AISI 316 austenitic stainless steels. The thermodynamic database was validated by comparing the calculated results with experimental data from commercial 316 austenitic steels. The developed computational thermodynamics was then coupled with precipitation kinetics simulation to understand the temporal evolution of precipitates in austenitic steels under long-term thermal aging (up to 600,000 h) at a temperature regime from 300 to 900 °C. This study discusses the effect of dislocation density and difusion coefficients on the precipitation kinetics at low temperatures, which shed a light on investigating the phase stability and transformation in austenitic steels used in light water reactors

  11. Using Historical Precipitation, Temperature, and Runoff Observations to Evaluate Evaporation Formulations in Land Surface Models

    Science.gov (United States)

    Koster, Randal D.; Mahanama, P. P.

    2012-01-01

    Key to translating soil moisture memory into subseasonal precipitation and air temperature forecast skill is a realistic treatment of evaporation in the forecast system used - in particular, a realistic treatment of how evaporation responds to variations in soil moisture. The inherent soil moisture-evaporation relationships used in today's land surface models (LSMs), however, arguably reflect little more than guesswork given the lack of evaporation and soil moisture data at the spatial scales represented by regional and global models. Here we present a new approach for evaluating this critical aspect of LSMs. Seasonally averaged precipitation is used as a proxy for seasonally-averaged soil moisture, and seasonally-averaged air temperature is used as a proxy for seasonally-averaged evaporation (e.g., more evaporative cooling leads to cooler temperatures) the relationship between historical precipitation and temperature measurements accordingly mimics in certain important ways nature's relationship between soil moisture and evaporation. Additional information on the relationship is gleaned from joint analysis of precipitation and streamflow measurements. An experimental framework that utilizes these ideas to guide the development of an improved soil moisture-evaporation relationship is described and demonstrated.

  12. Partitioning into hazard subregions for regional peaks-over-threshold modeling of heavy precipitation

    Science.gov (United States)

    Carreau, J.; Naveau, P.; Neppel, L.

    2017-05-01

    The French Mediterranean is subject to intense precipitation events occurring mostly in autumn. These can potentially cause flash floods, the main natural danger in the area. The distribution of these events follows specific spatial patterns, i.e., some sites are more likely to be affected than others. The peaks-over-threshold approach consists in modeling extremes, such as heavy precipitation, by the generalized Pareto (GP) distribution. The shape parameter of the GP controls the probability of extreme events and can be related to the hazard level of a given site. When interpolating across a region, the shape parameter should reproduce the observed spatial patterns of the probability of heavy precipitation. However, the shape parameter estimators have high uncertainty which might hide the underlying spatial variability. As a compromise, we choose to let the shape parameter vary in a moderate fashion. More precisely, we assume that the region of interest can be partitioned into subregions with constant hazard level. We formalize the model as a conditional mixture of GP distributions. We develop a two-step inference strategy based on probability weighted moments and put forward a cross-validation procedure to select the number of subregions. A synthetic data study reveals that the inference strategy is consistent and not very sensitive to the selected number of subregions. An application on daily precipitation data from the French Mediterranean shows that the conditional mixture of GPs outperforms two interpolation approaches (with constant or smoothly varying shape parameter).

  13. Modeling, Optimization & Control of Hydraulic Networks

    DEFF Research Database (Denmark)

    Tahavori, Maryamsadat

    2014-01-01

    . The nonlinear network model is derived based on the circuit theory. A suitable projection is used to reduce the state vector and to express the model in standard state-space form. Then, the controllability of nonlinear nonaffine hydraulic networks is studied. The Lie algebra-based controllability matrix is used......Water supply systems consist of a number of pumping stations, which deliver water to the customers via pipeline networks and elevated reservoirs. A huge amount of drinking water is lost before it reaches to end-users due to the leakage in pipe networks. A cost effective solution to reduce leakage...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...

  14. Geophysical monitoring and reactive transport modeling of ureolytically-driven calcium carbonate precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Y.; Ajo-Franklin, J.B.; Spycher, N.; Hubbard, S.S.; Zhang, G.; Williams, K.H.; Taylor, J.; Fujita, Y.; Smith, R.

    2011-07-15

    Ureolytically-driven calcium carbonate precipitation is the basis for a promising in-situ remediation method for sequestration of divalent radionuclide and trace metal ions. It has also been proposed for use in geotechnical engineering for soil strengthening applications. Monitoring the occurrence, spatial distribution, and temporal evolution of calcium carbonate precipitation in the subsurface is critical for evaluating the performance of this technology and for developing the predictive models needed for engineering application. In this study, we conducted laboratory column experiments using natural sediment and groundwater to evaluate the utility of geophysical (complex resistivity and seismic) sensing methods, dynamic synchrotron x-ray computed tomography (micro-CT), and reactive transport modeling for tracking ureolytically-driven calcium carbonate precipitation processes under site relevant conditions. Reactive transport modeling with TOUGHREACT successfully simulated the changes of the major chemical components during urea hydrolysis. Even at the relatively low level of urea hydrolysis observed in the experiments, the simulations predicted an enhanced calcium carbonate precipitation rate that was 3-4 times greater than the baseline level. Reactive transport modeling results, geophysical monitoring data and micro-CT imaging correlated well with reaction processes validated by geochemical data. In particular, increases in ionic strength of the pore fluid during urea hydrolysis predicted by geochemical modeling were successfully captured by electrical conductivity measurements and confirmed by geochemical data. The low level of urea hydrolysis and calcium carbonate precipitation suggested by the model and geochemical data was corroborated by minor changes in seismic P-wave velocity measurements and micro-CT imaging; the latter provided direct evidence of sparsely distributed calcium carbonate precipitation. Ion exchange processes promoted through NH{sub 4}{sup

  15. Precipitation projections under GCMs perspective and Turkish Water Foundation (TWF) statistical downscaling model procedures

    Science.gov (United States)

    Dabanlı, İsmail; Şen, Zekai

    2018-04-01

    The statistical climate downscaling model by the Turkish Water Foundation (TWF) is further developed and applied to a set of monthly precipitation records. The model is structured by two phases as spatial (regional) and temporal downscaling of global circulation model (GCM) scenarios. The TWF model takes into consideration the regional dependence function (RDF) for spatial structure and Markov whitening process (MWP) for temporal characteristics of the records to set projections. The impact of climate change on monthly precipitations is studied by downscaling Intergovernmental Panel on Climate Change-Special Report on Emission Scenarios (IPCC-SRES) A2 and B2 emission scenarios from Max Plank Institute (EH40PYC) and Hadley Center (HadCM3). The main purposes are to explain the TWF statistical climate downscaling model procedures and to expose the validation tests, which are rewarded in same specifications as "very good" for all stations except one (Suhut) station in the Akarcay basin that is in the west central part of Turkey. Eventhough, the validation score is just a bit lower at the Suhut station, the results are "satisfactory." It is, therefore, possible to say that the TWF model has reasonably acceptable skill for highly accurate estimation regarding standard deviation ratio (SDR), Nash-Sutcliffe efficiency (NSE), and percent bias (PBIAS) criteria. Based on the validated model, precipitation predictions are generated from 2011 to 2100 by using 30-year reference observation period (1981-2010). Precipitation arithmetic average and standard deviation have less than 5% error for EH40PYC and HadCM3 SRES (A2 and B2) scenarios.

  16. Future changes in extreme precipitation in the Rhine basin based on global and regional climate model simulations

    NARCIS (Netherlands)

    Pelt, van S.C.; Beersma, J.J.; Buishand, T.A.; Hurk, van den B.J.J.M.; Kabat, P.

    2012-01-01

    Probability estimates of the future change of extreme precipitation events are usually based on a limited number of available global climate model (GCM) or regional climate model (RCM) simulations. Since floods are related to heavy precipitation events, this restricts the assessment of flood risks.

  17. Port Hamiltonian modeling of Power Networks

    NARCIS (Netherlands)

    van Schaik, F.; van der Schaft, Abraham; Scherpen, Jacquelien M.A.; Zonetti, Daniele; Ortega, R

    2012-01-01

    In this talk a full nonlinear model for the power network in port–Hamiltonian framework is derived to study its stability properties. For this we use the modularity approach i.e., we first derive the models of individual components in power network as port-Hamiltonian systems and then we combine all

  18. Modelling traffic congestion using queuing networks

    Indian Academy of Sciences (India)

    Flow-density curves; uninterrupted traffic; Jackson networks. ... ness - also suffer from a big handicap vis-a-vis the Indian scenario: most of these models do .... more well-known queuing network models and onsite data, a more exact Road Cell ...

  19. Settings in Social Networks : a Measurement Model

    NARCIS (Netherlands)

    Schweinberger, Michael; Snijders, Tom A.B.

    2003-01-01

    A class of statistical models is proposed that aims to recover latent settings structures in social networks. Settings may be regarded as clusters of vertices. The measurement model is based on two assumptions. (1) The observed network is generated by hierarchically nested latent transitive

  20. Network interconnections: an architectural reference model

    NARCIS (Netherlands)

    Butscher, B.; Lenzini, L.; Morling, R.; Vissers, C.A.; Popescu-Zeletin, R.; van Sinderen, Marten J.; Heger, D.; Krueger, G.; Spaniol, O.; Zorn, W.

    1985-01-01

    One of the major problems in understanding the different approaches in interconnecting networks of different technologies is the lack of reference to a general model. The paper develops the rationales for a reference model of network interconnection and focuses on the architectural implications for

  1. Spatio-temporal precipitation climatology over complex terrain using a censored additive regression model.

    Science.gov (United States)

    Stauffer, Reto; Mayr, Georg J; Messner, Jakob W; Umlauf, Nikolaus; Zeileis, Achim

    2017-06-15

    Flexible spatio-temporal models are widely used to create reliable and accurate estimates for precipitation climatologies. Most models are based on square root transformed monthly or annual means, where a normal distribution seems to be appropriate. This assumption becomes invalid on a daily time scale as the observations involve large fractions of zero observations and are limited to non-negative values. We develop a novel spatio-temporal model to estimate the full climatological distribution of precipitation on a daily time scale over complex terrain using a left-censored normal distribution. The results demonstrate that the new method is able to account for the non-normal distribution and the large fraction of zero observations. The new climatology provides the full climatological distribution on a very high spatial and temporal resolution, and is competitive with, or even outperforms existing methods, even for arbitrary locations.

  2. Detecting vegetation-precipitation feedbacks in mid-Holocene North Africa from two climate models

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yi; Notaro, Michael; Liu, Zhengyu; Gallimore, Robert; Levis, Samuel; Kutzbach, John E.

    2008-03-31

    Using two climate-vegetation model simulations from the Fast Ocean Atmosphere Model (FOAM) and the Community Climate System Model (CCSM, version 2), we investigate vegetation-precipitation feedbacks across North Africa during the mid-Holocene. From mid-Holocene snapshot runs of FOAM and CCSM2, we detect a negative feedback at the annual timescale with our statistical analysis. Using the Monte- Carlo bootstrap method, the annual negative feedback is further confirmed to be significant in both simulations. Additional analysis shows that this negative interaction is partially caused by the competition between evaporation and transpiration in North African grasslands. Furthermore, we find the feedbacks decrease with increasing timescales, and change signs from positive to negative at increasing timescales in FOAM. The proposed mechanism for this sign switch is associated with the different persistent timescales of upper and lower soil water contents, and their interactions with vegetation and atmospheric precipitation.

  3. Do climate model predictions agree with long-term precipitation trends in the arid southwestern United States?

    Science.gov (United States)

    Elias, E.; Rango, A.; James, D.; Maxwell, C.; Anderson, J.; Abatzoglou, J. T.

    2016-12-01

    Researchers evaluating climate projections across southwestern North America observed a decreasing precipitation trend. Aridification was most pronounced in the cold (non-monsoonal) season, whereas downward trends in precipitation were smaller in the warm (monsoonal) season. In this region, based upon a multimodel mean of 20 Coupled Model Intercomparison Project 5 models using a business-as-usual (Representative Concentration Pathway 8.5) trajectory, midcentury precipitation is projected to increase slightly during the monsoonal time period (July-September; 6%) and decrease slightly during the remainder of the year (October-June; -4%). We use observed long-term (1915-2015) monthly precipitation records from 16 weather stations to investigate how well measured trends corroborate climate model predictions during the monsoonal and non-monsoonal timeframe. Running trend analysis using the Mann-Kendall test for 15 to 101 year moving windows reveals that half the stations showed significant (p≤0.1), albeit small, increasing trends based on the longest term record. Trends based on shorter-term records reveal a period of significant precipitation decline at all stations representing the 1950s drought. Trends from 1930 to 2015 reveal significant annual, monsoonal and non-monsoonal increases in precipitation (Fig 1). The 1960 to 2015 time window shows no significant precipitation trends. The more recent time window (1980 to 2015) shows a slight, but not significant, increase in monsoonal precipitation and a larger, significant decline in non-monsoonal precipitation. GCM precipitation projections are consistent with more recent trends for the region. Running trends from the most recent time window (mid-1990s to 2015) at all stations show increasing monsoonal precipitation and decreasing Oct-Jun precipitation, with significant trends at 6 of 16 stations. Running trend analysis revealed that the long-term trends were not persistent throughout the series length, but depended

  4. Performance modeling of network data services

    Energy Technology Data Exchange (ETDEWEB)

    Haynes, R.A.; Pierson, L.G.

    1997-01-01

    Networks at major computational organizations are becoming increasingly complex. The introduction of large massively parallel computers and supercomputers with gigabyte memories are requiring greater and greater bandwidth for network data transfers to widely dispersed clients. For networks to provide adequate data transfer services to high performance computers and remote users connected to them, the networking components must be optimized from a combination of internal and external performance criteria. This paper describes research done at Sandia National Laboratories to model network data services and to visualize the flow of data from source to sink when using the data services.

  5. Precipitation recycling in West Africa - regional modeling, evaporation tagging and atmospheric water budget analysis

    Science.gov (United States)

    Arnault, Joel; Kunstmann, Harald; Knoche, Hans-Richard

    2015-04-01

    Many numerical studies have shown that the West African monsoon is highly sensitive to the state of the land surface. It is however questionable to which extend a local change of land surface properties would affect the local climate, especially with respect to precipitation. This issue is traditionally addressed with the concept of precipitation recycling, defined as the contribution of local surface evaporation to local precipitation. For this study the West African monsoon has been simulated with the Weather Research and Forecasting (WRF) model using explicit convection, for the domain (1°S-21°N, 18°W-14°E) at a spatial resolution of 10 km, for the period January-October 2013, and using ERA-Interim reanalyses as driving data. This WRF configuration has been selected for its ability to simulate monthly precipitation amounts and daily histograms close to TRMM (Tropical Rainfall Measuring Mission) data. In order to investigate precipitation recycling in this WRF simulation, surface evaporation tagging has been implemented in the WRF source code as well as the budget of total and tagged atmospheric water. Surface evaporation tagging consists in duplicating all water species and the respective prognostic equations in the source code. Then, tagged water species are set to zero at the lateral boundaries of the simulated domain (no inflow of tagged water vapor), and tagged surface evaporation is considered only in a specified region. All the source terms of the prognostic equations of total and tagged water species are finally saved in the outputs for the budget analysis. This allows quantifying the respective contribution of total and tagged atmospheric water to atmospheric precipitation processes. The WRF simulation with surface evaporation tagging and budgets has been conducted two times, first with a 100 km2 tagged region (11-12°N, 1-2°W), and second with a 1000 km2 tagged region (7-16°N, 6°W -3°E). In this presentation we will investigate hydro

  6. Comparison of precipitating electron energy flux on March 22, 1979 with an empirical model: CDAW-6

    International Nuclear Information System (INIS)

    Simons, S.L. Jr.; Reiff, P.H.; Spiro, R.W.; Hardy, D.A.; Kroehl, H.W.

    1985-01-01

    Data recorded by Defense Meterological Satellite Program, TIROS and P-78-1 satellites for the CDAW 6 event on March 22, 1979, have been compared with a statistical model of precipitating electron fluxes. Comparisons have been made on both an orbit-by-orbit basis and on a global basis by sorting and binning the data by AE index, invariant latitude and magnetic local time in a manner similar to which the model was generated. We conclude that the model flux agrees with the data to within a factor of two, although small features and the exact locations of features are not consistently reproduced. In addition, the latitude of highest electron precipitation usually occurs about 3 0 more pole-ward in the model than in the data. We attribute this discrepancy to ring current inflation of the storm time magnetosphere (as evidenced by negative Dst's). We suggest that a similar empirical model based on AL instead of AE and including some indicator of the history of the event would provide an even better comparison. Alternatively, in situ data such as electrojet location should be used routinely to normalize the latitude of the auroral precipitation

  7. Continuum Modeling of Biological Network Formation

    KAUST Repository

    Albi, Giacomo; Burger, Martin; Haskovec, Jan; Markowich, Peter A.; Schlottbom, Matthias

    2017-01-01

    We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes

  8. Network models in economics and finance

    CERN Document Server

    Pardalos, Panos; Rassias, Themistocles

    2014-01-01

    Using network models to investigate the interconnectivity in modern economic systems allows researchers to better understand and explain some economic phenomena. This volume presents contributions by known experts and active researchers in economic and financial network modeling. Readers are provided with an understanding of the latest advances in network analysis as applied to economics, finance, corporate governance, and investments. Moreover, recent advances in market network analysis  that focus on influential techniques for market graph analysis are also examined. Young researchers will find this volume particularly useful in facilitating their introduction to this new and fascinating field. Professionals in economics, financial management, various technologies, and network analysis, will find the network models presented in this book beneficial in analyzing the interconnectivity in modern economic systems.

  9. Synergistic effects in threshold models on networks

    Science.gov (United States)

    Juul, Jonas S.; Porter, Mason A.

    2018-01-01

    Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can—depending on a parameter—either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.

  10. Gossip spread in social network Models

    Science.gov (United States)

    Johansson, Tobias

    2017-04-01

    Gossip almost inevitably arises in real social networks. In this article we investigate the relationship between the number of friends of a person and limits on how far gossip about that person can spread in the network. How far gossip travels in a network depends on two sets of factors: (a) factors determining gossip transmission from one person to the next and (b) factors determining network topology. For a simple model where gossip is spread among people who know the victim it is known that a standard scale-free network model produces a non-monotonic relationship between number of friends and expected relative spread of gossip, a pattern that is also observed in real networks (Lind et al., 2007). Here, we study gossip spread in two social network models (Toivonen et al., 2006; Vázquez, 2003) by exploring the parameter space of both models and fitting them to a real Facebook data set. Both models can produce the non-monotonic relationship of real networks more accurately than a standard scale-free model while also exhibiting more realistic variability in gossip spread. Of the two models, the one given in Vázquez (2003) best captures both the expected values and variability of gossip spread.

  11. Evaluation of EOR Processes Using Network Models

    DEFF Research Database (Denmark)

    Winter, Anatol; Larsen, Jens Kjell; Krogsbøll, Anette

    1998-01-01

    The report consists of the following parts: 1) Studies of wetting properties of model fluids and fluid mixtures aimed at an optimal selection of candidates for micromodel experiments. 2) Experimental studies of multiphase transport properties using physical models of porous networks (micromodels......) including estimation of their "petrophysical" properties (e.g. absolute permeability). 3) Mathematical modelling and computer studies of multiphase transport through pore space using mathematical network models. 4) Investigation of link between pore-scale and macroscopic recovery mechanisms....

  12. Turbulent precipitation of uranium oxalate in a vortex reactor - experimental study and modelling; Precipitation turbulente d'oxalate d'uranium en reacteur vortex - etude experimentale et modelisation

    Energy Technology Data Exchange (ETDEWEB)

    Sommer de Gelicourt, Y

    2004-03-15

    Industrial oxalic precipitation processed in an un-baffled magnetically stirred tank, the Vortex Reactor, has been studied with uranium simulating plutonium. Modelling precipitation requires a mixing model for the continuous liquid phase and the solution of population balance for the dispersed solid phase. Being chemical reaction influenced by the degree of mixing at molecular scale, that commercial CFD code does not resolve, a sub-grid scale model has been introduced: the finite mode probability density functions, and coupled with a model for the liquid energy spectrum. Evolution of the dispersed phase has been resolved by the quadrature method of moments, first used here with experimental nucleation and growth kinetics, and an aggregation kernel based on local shear rate. The promising abilities of this local approach, without any fitting constant, are strengthened by the similarity between experimental results and simulations. (author)

  13. Bayesian inference of uncertainties in precipitation-streamflow modeling in a snow affected catchment

    Science.gov (United States)

    Koskela, J. J.; Croke, B. W. F.; Koivusalo, H.; Jakeman, A. J.; Kokkonen, T.

    2012-11-01

    Bayesian inference is used to study the effect of precipitation and model structural uncertainty on estimates of model parameters and confidence limits of predictive variables in a conceptual rainfall-runoff model in the snow-fed Rudbäck catchment (142 ha) in southern Finland. The IHACRES model is coupled with a simple degree day model to account for snow accumulation and melt. The posterior probability distribution of the model parameters is sampled by using the Differential Evolution Adaptive Metropolis (DREAM(ZS)) algorithm and the generalized likelihood function. Precipitation uncertainty is taken into account by introducing additional latent variables that were used as multipliers for individual storm events. Results suggest that occasional snow water equivalent (SWE) observations together with daily streamflow observations do not contain enough information to simultaneously identify model parameters, precipitation uncertainty and model structural uncertainty in the Rudbäck catchment. The addition of an autoregressive component to account for model structure error and latent variables having uniform priors to account for input uncertainty lead to dubious posterior distributions of model parameters. Thus our hypothesis that informative priors for latent variables could be replaced by additional SWE data could not be confirmed. The model was found to work adequately in 1-day-ahead simulation mode, but the results were poor in the simulation batch mode. This was caused by the interaction of parameters that were used to describe different sources of uncertainty. The findings may have lessons for other cases where parameterizations are similarly high in relation to available prior information.

  14. Proactive modeling of water quality impacts of extreme precipitation events in a drinking water reservoir.

    Science.gov (United States)

    Jeznach, Lillian C; Hagemann, Mark; Park, Mi-Hyun; Tobiason, John E

    2017-10-01

    Extreme precipitation events are of concern to managers of drinking water sources because these occurrences can affect both water supply quantity and quality. However, little is known about how these low probability events impact organic matter and nutrient loads to surface water sources and how these loads may impact raw water quality. This study describes a method for evaluating the sensitivity of a water body of interest from watershed input simulations under extreme precipitation events. An example application of the method is illustrated using the Wachusett Reservoir, an oligo-mesotrophic surface water reservoir in central Massachusetts and a major drinking water supply to metropolitan Boston. Extreme precipitation event simulations during the spring and summer resulted in total organic carbon, UV-254 (a surrogate measurement for reactive organic matter), and total algae concentrations at the drinking water intake that exceeded recorded maximums. Nutrient concentrations after storm events were less likely to exceed recorded historical maximums. For this particular reservoir, increasing inter-reservoir transfers of water with lower organic matter content after a large precipitation event has been shown in practice and in model simulations to decrease organic matter levels at the drinking water intake, therefore decreasing treatment associated oxidant demand, energy for UV disinfection, and the potential for formation of disinfection byproducts. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. An Approach for Generating Precipitation Input for Worst-Case Flood Modelling

    Science.gov (United States)

    Felder, Guido; Weingartner, Rolf

    2015-04-01

    There is a lack of suitable methods for creating precipitation scenarios that can be used to realistically estimate peak discharges with very low probabilities. On the one hand, existing methods are methodically questionable when it comes to physical system boundaries. On the other hand, the spatio-temporal representativeness of precipitation patterns as system input is limited. In response, this study proposes a method of deriving representative spatio-temporal precipitation patterns and presents a step towards making methodically correct estimations of infrequent floods by using a worst-case approach. A Monte-Carlo rainfall-runoff model allows for the testing of a wide range of different spatio-temporal distributions of an extreme precipitation event and therefore for the generation of a hydrograph for each of these distributions. Out of these numerous hydrographs and their corresponding peak discharges, the worst-case catchment reactions on the system input can be derived. The spatio-temporal distributions leading to the highest peak discharges are identified and can eventually be used for further investigations.

  16. Improving the Statistical Modeling of the TRMM Extreme Precipitation Monitoring System

    Science.gov (United States)

    Demirdjian, L.; Zhou, Y.; Huffman, G. J.

    2016-12-01

    This project improves upon an existing extreme precipitation monitoring system based on the Tropical Rainfall Measuring Mission (TRMM) daily product (3B42) using new statistical models. The proposed system utilizes a regional modeling approach, where data from similar grid locations are pooled to increase the quality and stability of the resulting model parameter estimates to compensate for the short data record. The regional frequency analysis is divided into two stages. In the first stage, the region defined by the TRMM measurements is partitioned into approximately 27,000 non-overlapping clusters using a recursive k-means clustering scheme. In the second stage, a statistical model is used to characterize the extreme precipitation events occurring in each cluster. Instead of utilizing the block-maxima approach used in the existing system, where annual maxima are fit to the Generalized Extreme Value (GEV) probability distribution at each cluster separately, the present work adopts the peak-over-threshold (POT) method of classifying points as extreme if they exceed a pre-specified threshold. Theoretical considerations motivate the use of the Generalized-Pareto (GP) distribution for fitting threshold exceedances. The fitted parameters can be used to construct simple and intuitive average recurrence interval (ARI) maps which reveal how rare a particular precipitation event is given its spatial location. The new methodology eliminates much of the random noise that was produced by the existing models due to a short data record, producing more reasonable ARI maps when compared with NOAA's long-term Climate Prediction Center (CPC) ground based observations. The resulting ARI maps can be useful for disaster preparation, warning, and management, as well as increased public awareness of the severity of precipitation events. Furthermore, the proposed methodology can be applied to various other extreme climate records.

  17. Evaluating Cloud and Precipitation Processes in Numerical Models using Current and Potential Future Satellite Missions

    Science.gov (United States)

    van den Heever, S. C.; Tao, W. K.; Skofronick Jackson, G.; Tanelli, S.; L'Ecuyer, T. S.; Petersen, W. A.; Kummerow, C. D.

    2015-12-01

    Cloud, aerosol and precipitation processes play a fundamental role in the water and energy cycle. It is critical to accurately represent these microphysical processes in numerical models if we are to better predict cloud and precipitation properties on weather through climate timescales. Much has been learned about cloud properties and precipitation characteristics from NASA satellite missions such as TRMM, CloudSat, and more recently GPM. Furthermore, data from these missions have been successfully utilized in evaluating the microphysical schemes in cloud-resolving models (CRMs) and global models. However, there are still many uncertainties associated with these microphysics schemes. These uncertainties can be attributed, at least in part, to the fact that microphysical processes cannot be directly observed or measured, but instead have to be inferred from those cloud properties that can be measured. Evaluation of microphysical parameterizations are becoming increasingly important as enhanced computational capabilities are facilitating the use of more sophisticated schemes in CRMs, and as future global models are being run on what has traditionally been regarded as cloud-resolving scales using CRM microphysical schemes. In this talk we will demonstrate how TRMM, CloudSat and GPM data have been used to evaluate different aspects of current CRM microphysical schemes, providing examples of where these approaches have been successful. We will also highlight CRM microphysical processes that have not been well evaluated and suggest approaches for addressing such issues. Finally, we will introduce a potential NASA satellite mission, the Cloud and Precipitation Processes Mission (CAPPM), which would facilitate the development and evaluation of different microphysical-dynamical feedbacks in numerical models.

  18. Towards reproducible descriptions of neuronal network models.

    Directory of Open Access Journals (Sweden)

    Eilen Nordlie

    2009-08-01

    Full Text Available Progress in science depends on the effective exchange of ideas among scientists. New ideas can be assessed and criticized in a meaningful manner only if they are formulated precisely. This applies to simulation studies as well as to experiments and theories. But after more than 50 years of neuronal network simulations, we still lack a clear and common understanding of the role of computational models in neuroscience as well as established practices for describing network models in publications. This hinders the critical evaluation of network models as well as their re-use. We analyze here 14 research papers proposing neuronal network models of different complexity and find widely varying approaches to model descriptions, with regard to both the means of description and the ordering and placement of material. We further observe great variation in the graphical representation of networks and the notation used in equations. Based on our observations, we propose a good model description practice, composed of guidelines for the organization of publications, a checklist for model descriptions, templates for tables presenting model structure, and guidelines for diagrams of networks. The main purpose of this good practice is to trigger a debate about the communication of neuronal network models in a manner comprehensible to humans, as opposed to machine-readable model description languages. We believe that the good model description practice proposed here, together with a number of other recent initiatives on data-, model-, and software-sharing, may lead to a deeper and more fruitful exchange of ideas among computational neuroscientists in years to come. We further hope that work on standardized ways of describing--and thinking about--complex neuronal networks will lead the scientific community to a clearer understanding of high-level concepts in network dynamics, and will thus lead to deeper insights into the function of the brain.

  19. Improved Maximum Parsimony Models for Phylogenetic Networks.

    Science.gov (United States)

    Van Iersel, Leo; Jones, Mark; Scornavacca, Celine

    2018-05-01

    Phylogenetic networks are well suited to represent evolutionary histories comprising reticulate evolution. Several methods aiming at reconstructing explicit phylogenetic networks have been developed in the last two decades. In this article, we propose a new definition of maximum parsimony for phylogenetic networks that permits to model biological scenarios that cannot be modeled by the definitions currently present in the literature (namely, the "hardwired" and "softwired" parsimony). Building on this new definition, we provide several algorithmic results that lay the foundations for new parsimony-based methods for phylogenetic network reconstruction.

  20. Modeling, robust and distributed model predictive control for freeway networks

    NARCIS (Netherlands)

    Liu, S.

    2016-01-01

    In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of

  1. Stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural streamflow

    Science.gov (United States)

    Kolars, Kelsey A.; Vecchia, Aldo V.; Ryberg, Karen R.

    2016-02-24

    The Souris River Basin is a 61,000-square-kilometer basin in the Provinces of Saskatchewan and Manitoba and the State of North Dakota. In May and June of 2011, record-setting rains were seen in the headwater areas of the basin. Emergency spillways of major reservoirs were discharging at full or nearly full capacity, and extensive flooding was seen in numerous downstream communities. To determine the probability of future extreme floods and droughts, the U.S. Geological Survey, in cooperation with the North Dakota State Water Commission, developed a stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural (unregulated) streamflow. Simulations from the model can be used in future studies to simulate regulated streamflow, design levees, and other structures; and to complete economic cost/benefit analyses.Long-term climatic variability was analyzed using tree-ring chronologies to hindcast precipitation to the early 1700s and compare recent wet and dry conditions to earlier extreme conditions. The extended precipitation record was consistent with findings from the Devils Lake and Red River of the North Basins (southeast of the Souris River Basin), supporting the idea that regional climatic patterns for many centuries have consisted of alternating wet and dry climate states.A stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration for the Souris River Basin was developed using recorded meteorological data and extended precipitation records provided through tree-ring analysis. A significant climate transition was seen around1970, with 1912–69 representing a dry climate state and 1970–2011 representing a wet climate state. Although there were some distinct subpatterns within the basin, the predominant differences between the two states were higher spring through early fall precipitation and higher spring potential evapotranspiration for the wet compared to the dry state.A water

  2. Atomistic modeling of zirconium hydride precipitation: methodology for deriving a tight-binding potential

    International Nuclear Information System (INIS)

    Dufresne, Alice

    2014-01-01

    The zirconium-hydrogen system is of nuclear safety interest, as the hydride precipitation leads to the cladding embrittlement, which is made of zirconium-based alloys. The cladding is the first safety barrier confining the radioactive products: its integrity shall be kept during the entire fuel-assemblies life, in reactor, including accidental situation, and post-operation (transport and storage). Many uncertainties remain regarding the hydrides precipitation kinetics and the local stress impact on their precipitation. The atomic scale modeling of this system would bring clarifications on the relevant mechanisms. The usual atomistic modeling methods are based on thermo-statistic approaches, whose precision and reliability depend on the interatomic potential used. However, there was no potential allowing a rigorous study of the Zr-H system. The present work has indeed addressed this issue: a new tight-binding potential for zirconium hydrides modeling is now available. Moreover, this thesis provides a detailed manual for deriving such potentials accounting for spd hybridization, and fitted here on DFT results. This guidebook has be written in light of modeling a pure transition metal followed by a metal-covalent coupling (metallic carbides, nitrides and silicides). (author)

  3. Role of atmospheric aerosol concentration on deep convective precipitation: Cloud-resolving model simulations

    Science.gov (United States)

    Tao, Wei-Kuo; Li, Xiaowen; Khain, Alexander; Matsui, Toshihisa; Lang, Stephen; Simpson, Joanne

    2007-12-01

    A two-dimensional cloud-resolving model with detailed spectral bin microphysics is used to examine the effect of aerosols on three different deep convective cloud systems that developed in different geographic locations: south Florida, Oklahoma, and the central Pacific. A pair of model simulations, one with an idealized low cloud condensation nuclei (CCN) (clean) and one with an idealized high CCN (dirty environment), is conducted for each case. In all three cases, rain reaches the ground earlier for the low-CCN case. Rain suppression is also evident in all three cases with high CCN. However, this suppression only occurs during the early stages of the simulations. During the mature stages of the simulations the effects of increasing aerosol concentration range from rain suppression in the Oklahoma case to almost no effect in the Florida case to rain enhancement in the Pacific case. The model results suggest that evaporative cooling in the lower troposphere is a key process in determining whether high CCN reduces or enhances precipitation. Stronger evaporative cooling can produce a stronger cold pool and thus stronger low-level convergence through interactions with the low-level wind shear. Consequently, precipitation processes can be more vigorous. For example, the evaporative cooling is more than two times stronger in the lower troposphere with high CCN for the Pacific case. Sensitivity tests also suggest that ice processes are crucial for suppressing precipitation in the Oklahoma case with high CCN. A comparison and review of other modeling studies are also presented.

  4. Hydrometeorological network for flood monitoring and modeling

    Science.gov (United States)

    Efstratiadis, Andreas; Koussis, Antonis D.; Lykoudis, Spyros; Koukouvinos, Antonis; Christofides, Antonis; Karavokiros, George; Kappos, Nikos; Mamassis, Nikos; Koutsoyiannis, Demetris

    2013-08-01

    Due to its highly fragmented geomorphology, Greece comprises hundreds of small- to medium-size hydrological basins, in which often the terrain is fairly steep and the streamflow regime ephemeral. These are typically affected by flash floods, occasionally causing severe damages. Yet, the vast majority of them lack flow-gauging infrastructure providing systematic hydrometric data at fine time scales. This has obvious impacts on the quality and reliability of flood studies, which typically use simplistic approaches for ungauged basins that do not consider local peculiarities in sufficient detail. In order to provide a consistent framework for flood design and to ensure realistic predictions of the flood risk -a key issue of the 2007/60/EC Directive- it is essential to improve the monitoring infrastructures by taking advantage of modern technologies for remote control and data management. In this context and in the research project DEUCALION, we have recently installed and are operating, in four pilot river basins, a telemetry-based hydro-meteorological network that comprises automatic stations and is linked to and supported by relevant software. The hydrometric stations measure stage, using 50-kHz ultrasonic pulses or piezometric sensors, or both stage (piezometric) and velocity via acoustic Doppler radar; all measurements are being temperature-corrected. The meteorological stations record air temperature, pressure, relative humidity, wind speed and direction, and precipitation. Data transfer is made via GPRS or mobile telephony modems. The monitoring network is supported by a web-based application for storage, visualization and management of geographical and hydro-meteorological data (ENHYDRIS), a software tool for data analysis and processing (HYDROGNOMON), as well as an advanced model for flood simulation (HYDROGEIOS). The recorded hydro-meteorological observations are accessible over the Internet through the www-application. The system is operational and its

  5. Tool wear modeling using abductive networks

    Science.gov (United States)

    Masory, Oren

    1992-09-01

    A tool wear model based on Abductive Networks, which consists of a network of `polynomial' nodes, is described. The model relates the cutting parameters, components of the cutting force, and machining time to flank wear. Thus real time measurements of the cutting force can be used to monitor the machining process. The model is obtained by a training process in which the connectivity between the network's nodes and the polynomial coefficients of each node are determined by optimizing a performance criteria. Actual wear measurements of coated and uncoated carbide inserts were used for training and evaluating the established model.

  6. Classifying Multi-Model Wheat Yield Impact Response Surfaces Showing Sensitivity to Temperature and Precipitation Change

    Science.gov (United States)

    Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R.; Bindi, Marco; Hoffmann, Holger; Palosuo, Taru; Ruiz-Ramos, Margarita; Tao, Fulu; Trnka, Miroslav; Acutis, Marco; hide

    2017-01-01

    Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (minus 2 to plus 9 degrees Centigrade) and precipitation (minus 50 to plus 50 percent). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the

  7. [Impacts of forest and precipitation on runoff and sediment in Tianshui watershed and GM models].

    Science.gov (United States)

    Ouyang, H

    2000-12-01

    This paper analyzed the impacts of foret stand volume and precipitation on annual erosion modulus, mean sediment, maximum sediment, mean runoff, maximum runoff, minimum runoff, mean water level, maximum water level and minimum water level in Tianshui watershed, and also analyzed the effect of the variation of forest stand volume on monthly mean runoff, minimum runoff and mean water level. The dynamic models of grey system GM(1, N) were constructed to simulate the changes of these hydrological elements. The dynamic GM models on the impact of stand volumes of different forest types(Chinese fir, masson pine and broad-leaved forests) with different age classes(young, middle-aged, mature and over-mature) and that of precipitation on the hydrological elements were also constructed, and their changes with time were analyzed.

  8. Independent effects of temperature and precipitation on modeled runoff in the conterminous United States

    Science.gov (United States)

    McCabe, G.J.; Wolock, D.M.

    2011-01-01

    A water-balance model is used to simulate time series of water-year runoff for 4 km ?? 4 km grid cells for the conterminous United States during the 1900-2008 period. Model outputs are used to examine the separate effects of precipitation and temperature on runoff variability. Overall, water-year runoff has increased in the conterminous United States and precipitation has accounted for almost all of the variability in water-year runoff during the past century. In contrast, temperature effects on runoff have been small for most locations in the United States even during periods when temperatures for most of the United States increased significantly. Copyright 2011 by the American Geophysical Union.

  9. Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

    Czech Academy of Sciences Publication Activity Database

    Beranová, Romana; Kyselý, Jan; Hanel, M.

    2018-01-01

    Roč. 132, 1-2 (2018), s. 515-527 ISSN 0177-798X R&D Projects: GA ČR(CZ) GA14-18675S Institutional support: RVO:68378289 Keywords : sub-daily precipitation * regional climate models * extremes * Czech Republic Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 2.640, year: 2016 https://link.springer.com/article/10.1007/s00704-017-2102-0

  10. An Assessment of Mean Areal Precipitation Methods on Simulated Stream Flow: A SWAT Model Performance Assessment

    Directory of Open Access Journals (Sweden)

    Sean Zeiger

    2017-06-01

    Full Text Available Accurate mean areal precipitation (MAP estimates are essential input forcings for hydrologic models. However, the selection of the most accurate method to estimate MAP can be daunting because there are numerous methods to choose from (e.g., proximate gauge, direct weighted average, surface-fitting, and remotely sensed methods. Multiple methods (n = 19 were used to estimate MAP with precipitation data from 11 distributed monitoring sites, and 4 remotely sensed data sets. Each method was validated against the hydrologic model simulated stream flow using the Soil and Water Assessment Tool (SWAT. SWAT was validated using a split-site method and the observed stream flow data from five nested-scale gauging sites in a mixed-land-use watershed of the central USA. Cross-validation results showed the error associated with surface-fitting and remotely sensed methods ranging from −4.5 to −5.1%, and −9.8 to −14.7%, respectively. Split-site validation results showed the percent bias (PBIAS values that ranged from −4.5 to −160%. Second order polynomial functions especially overestimated precipitation and subsequent stream flow simulations (PBIAS = −160 in the headwaters. The results indicated that using an inverse-distance weighted, linear polynomial interpolation or multiquadric function method to estimate MAP may improve SWAT model simulations. Collectively, the results highlight the importance of spatially distributed observed hydroclimate data for precipitation and subsequent steam flow estimations. The MAP methods demonstrated in the current work can be used to reduce hydrologic model uncertainty caused by watershed physiographic differences.

  11. Radar adjusted data versus modelled precipitation: a case study over Cyprus

    Directory of Open Access Journals (Sweden)

    M. Casaioli

    2006-01-01

    Full Text Available In the framework of the European VOLTAIRE project (Fifth Framework Programme, simulations of relatively heavy precipitation events, which occurred over the island of Cyprus, by means of numerical atmospheric models were performed. One of the aims of the project was indeed the comparison of modelled rainfall fields with multi-sensor observations. Thus, for the 5 March 2003 event, the 24-h accumulated precipitation BOlogna Limited Area Model (BOLAM forecast was compared with the available observations reconstructed from ground-based radar data and estimated by rain gauge data. Since radar data may be affected by errors depending on the distance from the radar, these data could be range-adjusted by using other sensors. In this case, the Precipitation Radar aboard the Tropical Rainfall Measuring Mission (TRMM satellite was used to adjust the ground-based radar data with a two-parameter scheme. Thus, in this work, two observational fields were employed: the rain gauge gridded analysis and the observational analysis obtained by merging the range-adjusted radar and rain gauge fields. In order to verify the modelled precipitation, both non-parametric skill scores and the contiguous rain area (CRA analysis were applied. Skill score results show some differences when using the two observational fields. CRA results are instead quite in agreement, showing that in general a 0.27° eastward shift optimizes the forecast with respect to the two observational analyses. This result is also supported by a subjective inspection of the shifted forecast field, whose gross features agree with the analysis pattern more than the non-shifted forecast one. However, some open questions, especially regarding the effect of other range adjustment techniques, remain open and need to be addressed in future works.

  12. Winter precipitation characteristics in western US related to atmospheric river landfalls: observations and model evaluations

    Science.gov (United States)

    Kim, J.; Guan, B.; Waliser, D. E.; Ferraro, R. D.; Case, J. L.; Iguchi, T.; Kemp, E.; Putman, W.; Wang, W.; Wu, D.; Tian, B.

    2018-01-01

    Winter precipitation (PR) characteristics in western United States (WUS) related to atmospheric river (AR) landfalls are examined using the observation-based PRISM data. The observed AR-related precipitation characteristics are in turn used to evaluate model precipitation data from the NASA MERRA2 reanalysis and from seven dynamical downscaling simulations driven by the MERRA2. Multiple metrics including mean bias, Taylor diagram, and two skill scores are used to measure model performance for three climatological sub-regions in WUS, Pacific Northwest (PNW), Pacific Southwest (PSW) and Great Basin (GB). All model data well represent the winter-mean PR with spatial pattern correlations of 0.8 or higher with PRISM for the three sub-regions. Higher spatial resolutions and/or the use of spectral nudging generally yield higher skill scores in simulating the geographical distribution of PR for the entire winter. The PRISM data shows that the AR-related fraction of winter PR and associated daily PR PDFs in each region vary strongly for landfall locations; AR landfalls in the northern WUS coast (NC) affect mostly PNW while those in the southern WUS coast (SC) affect both PSW and GB. NC (SC) landfalls increase the frequency of heavy PR in PNW (PSW and GB) but reduce it in PSW (PNW). All model data reasonably represent these observed variations in the AR-related winter PR fractions and the daily PR PDFs according to AR landfall locations. However, unlike for the entire winter period, no systematic effects of resolution and/or spectral nudging are identified in these AR-related PR characteristics. Dynamical downscaling in this study generally yield positive added values to the MERRA2 PR in the AR-related PR fraction for most sub-regions and landfall locations, most noticeably for PSW by NU-WRF. The downscaling also generate positive added value in p95 for PNW, but negative values for PSW and GB due to overestimation of heavy precipitation events.

  13. Modelling of virtual production networks

    Directory of Open Access Journals (Sweden)

    2011-03-01

    Full Text Available Nowadays many companies, especially small and medium-sized enterprises (SMEs, specialize in a limited field of production. It requires forming virtual production networks of cooperating enterprises to manufacture better, faster and cheaper. Apart from that, some production orders cannot be realized, because there is not a company of sufficient production potential. In this case the virtual production networks of cooperating companies can realize these production orders. These networks have larger production capacity and many different resources. Therefore it can realize many more production orders together than each of them separately. Such organization allows for executing high quality product. The maintenance costs of production capacity and used resources are not so high. In this paper a methodology of rapid prototyping of virtual production networks is proposed. It allows to execute production orders on time considered existing logistic constraints.

  14. A Network Disruption Modeling Tool

    National Research Council Canada - National Science Library

    Leinart, James

    1998-01-01

    Given that network disruption has been identified as a military objective and C2-attack has been identified as the mechanism to accomplish this objective, a target set must be acquired and priorities...

  15. Evaluation of precipitation input for SWAT modeling in Alpine catchment: A case study in the Adige river basin (Italy).

    Science.gov (United States)

    Tuo, Ye; Duan, Zheng; Disse, Markus; Chiogna, Gabriele

    2016-12-15

    Precipitation is often the most important input data in hydrological models when simulating streamflow. The Soil and Water Assessment Tool (SWAT), a widely used hydrological model, only makes use of data from one precipitation gauge station that is nearest to the centroid of each subbasin, which is eventually corrected using the elevation band method. This leads in general to inaccurate representation of subbasin precipitation input data, particularly in catchments with complex topography. To investigate the impact of different precipitation inputs on the SWAT model simulations in Alpine catchments, 13years (1998-2010) of daily precipitation data from four datasets including OP (Observed precipitation), IDW (Inverse Distance Weighting data), CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) and TRMM (Tropical Rainfall Measuring Mission) has been considered. Both model performances (comparing simulated and measured streamflow data at the catchment outlet) as well as parameter and prediction uncertainties have been quantified. For all three subbasins, the use of elevation bands is fundamental to match the water budget. Streamflow predictions obtained using IDW inputs are better than those obtained using the other datasets in terms of both model performance and prediction uncertainty. Models using the CHIRPS product as input provide satisfactory streamflow estimation, suggesting that this satellite product can be applied to this data-scarce Alpine region. Comparing the performance of SWAT models using different precipitation datasets is therefore important in data-scarce regions. This study has shown that, precipitation is the main source of uncertainty, and different precipitation datasets in SWAT models lead to different best estimate ranges for the calibrated parameters. This has important implications for the interpretation of the simulated hydrological processes. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  16. Modeling Epidemics Spreading on Social Contact Networks.

    Science.gov (United States)

    Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

    2015-09-01

    Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.

  17. Spatial Epidemic Modelling in Social Networks

    Science.gov (United States)

    Simoes, Joana Margarida

    2005-06-01

    The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.

  18. Implementing network constraints in the EMPS model

    Energy Technology Data Exchange (ETDEWEB)

    Helseth, Arild; Warland, Geir; Mo, Birger; Fosso, Olav B.

    2010-02-15

    This report concerns the coupling of detailed market and network models for long-term hydro-thermal scheduling. Currently, the EPF model (Samlast) is the only tool available for this task for actors in the Nordic market. A new prototype for solving the coupled market and network problem has been developed. The prototype is based on the EMPS model (Samkjoeringsmodellen). Results from the market model are distributed to a detailed network model, where a DC load flow detects if there are overloads on monitored lines or intersections. In case of overloads, network constraints are generated and added to the market problem. Theoretical and implementation details for the new prototype are elaborated in this report. The performance of the prototype is tested against the EPF model on a 20-area Nordic dataset. (Author)

  19. Role models for complex networks

    Science.gov (United States)

    Reichardt, J.; White, D. R.

    2007-11-01

    We present a framework for automatically decomposing (“block-modeling”) the functional classes of agents within a complex network. These classes are represented by the nodes of an image graph (“block model”) depicting the main patterns of connectivity and thus functional roles in the network. Using a first principles approach, we derive a measure for the fit of a network to any given image graph allowing objective hypothesis testing. From the properties of an optimal fit, we derive how to find the best fitting image graph directly from the network and present a criterion to avoid overfitting. The method can handle both two-mode and one-mode data, directed and undirected as well as weighted networks and allows for different types of links to be dealt with simultaneously. It is non-parametric and computationally efficient. The concepts of structural equivalence and modularity are found as special cases of our approach. We apply our method to the world trade network and analyze the roles individual countries play in the global economy.

  20. Uncertainty of global summer precipitation in the CMIP5 models: a comparison between high-resolution and low-resolution models

    Science.gov (United States)

    Huang, Danqing; Yan, Peiwen; Zhu, Jian; Zhang, Yaocun; Kuang, Xueyuan; Cheng, Jing

    2018-04-01

    The uncertainty of global summer precipitation simulated by the 23 CMIP5 CGCMs and the possible impacts of model resolutions are investigated in this study. Large uncertainties exist over the tropical and subtropical regions, which can be mainly attributed to convective precipitation simulation. High-resolution models (HRMs) and low-resolution models (LRMs) are further investigated to demonstrate their different contributions to the uncertainties of the ensemble mean. It shows that the high-resolution model ensemble means (HMME) and low-resolution model ensemble mean (LMME) mitigate the biases between the MME and observation over most continents and oceans, respectively. The HMME simulates more precipitation than the LMME over most oceans, but less precipitation over some continents. The dominant precipitation category in the HRMs (LRMs) is the heavy precipitation (moderate precipitation) over the tropic regions. The combinations of convective and stratiform precipitation are also quite different: the HMME has much higher ratio of stratiform precipitation while the LMME has more convective precipitation. Finally, differences in precipitation between the HMME and LMME can be traced to their differences in the SST simulations via the local and remote air-sea interaction.

  1. Validation of precipitation over Japan during 1985-2004 simulated by three regional climate models and two multi-model ensemble means

    Energy Technology Data Exchange (ETDEWEB)

    Ishizaki, Yasuhiro [Meteorological Research Institute, Tsukuba (Japan); National Institute for Environmental Studies, Tsukuba (Japan); Nakaegawa, Toshiyuki; Takayabu, Izuru [Meteorological Research Institute, Tsukuba (Japan)

    2012-07-15

    We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate. (orig.)

  2. Precipitation intensity probability distribution modelling for hydrological and construction design purposes

    International Nuclear Information System (INIS)

    Koshinchanov, Georgy; Dimitrov, Dobri

    2008-01-01

    The characteristics of rainfall intensity are important for many purposes, including design of sewage and drainage systems, tuning flood warning procedures, etc. Those estimates are usually statistical estimates of the intensity of precipitation realized for certain period of time (e.g. 5, 10 min., etc) with different return period (e.g. 20, 100 years, etc). The traditional approach in evaluating the mentioned precipitation intensities is to process the pluviometer's records and fit probability distribution to samples of intensities valid for certain locations ore regions. Those estimates further become part of the state regulations to be used for various economic activities. Two problems occur using the mentioned approach: 1. Due to various factors the climate conditions are changed and the precipitation intensity estimates need regular update; 2. As far as the extremes of the probability distribution are of particular importance for the practice, the methodology of the distribution fitting needs specific attention to those parts of the distribution. The aim of this paper is to make review of the existing methodologies for processing the intensive rainfalls and to refresh some of the statistical estimates for the studied areas. The methodologies used in Bulgaria for analyzing the intensive rainfalls and produce relevant statistical estimates: - The method of the maximum intensity, used in the National Institute of Meteorology and Hydrology to process and decode the pluviometer's records, followed by distribution fitting for each precipitation duration period; - As the above, but with separate modeling of probability distribution for the middle and high probability quantiles. - Method is similar to the first one, but with a threshold of 0,36 mm/min of intensity; - Another method proposed by the Russian hydrologist G. A. Aleksiev for regionalization of estimates over some territory, improved and adapted by S. Gerasimov for Bulgaria; - Next method is considering only

  3. Improved simulation of precipitation in the tropics using a modified BMJ scheme in the WRF model

    Science.gov (United States)

    Fonseca, R. M.; Zhang, T.; Yong, K.-T.

    2015-09-01

    The successful modelling of the observed precipitation, a very important variable for a wide range of climate applications, continues to be one of the major challenges that climate scientists face today. When the Weather Research and Forecasting (WRF) model is used to dynamically downscale the Climate Forecast System Reanalysis (CFSR) over the Indo-Pacific region, with analysis (grid-point) nudging, it is found that the cumulus scheme used, Betts-Miller-Janjić (BMJ), produces excessive rainfall suggesting that it has to be modified for this region. Experimentation has shown that the cumulus precipitation is not very sensitive to changes in the cloud efficiency but varies greatly in response to modifications of the temperature and humidity reference profiles. A new version of the scheme, denoted "modified BMJ" scheme, where the humidity reference profile is more moist, was developed. In tropical belt simulations it was found to give a better estimate of the observed precipitation as given by the Tropical Rainfall Measuring Mission (TRMM) 3B42 data set than the default BMJ scheme for the whole tropics and both monsoon seasons. In fact, in some regions the model even outperforms CFSR. The advantage of modifying the BMJ scheme to produce better rainfall estimates lies in the final dynamical consistency of the rainfall with other dynamical and thermodynamical variables of the atmosphere.

  4. Modeling the interdependent network based on two-mode networks

    Science.gov (United States)

    An, Feng; Gao, Xiangyun; Guan, Jianhe; Huang, Shupei; Liu, Qian

    2017-10-01

    Among heterogeneous networks, there exist obviously and closely interdependent linkages. Unlike existing research primarily focus on the theoretical research of physical interdependent network model. We propose a two-layer interdependent network model based on two-mode networks to explore the interdependent features in the reality. Specifically, we construct a two-layer interdependent loan network and develop several dependent features indices. The model is verified to enable us to capture the loan dependent features of listed companies based on loan behaviors and shared shareholders. Taking Chinese debit and credit market as case study, the main conclusions are: (1) only few listed companies shoulder the main capital transmission (20% listed companies occupy almost 70% dependent degree). (2) The control of these key listed companies will be more effective of avoiding the spreading of financial risks. (3) Identifying the companies with high betweenness centrality and controlling them could be helpful to monitor the financial risk spreading. (4) The capital transmission channel among Chinese financial listed companies and Chinese non-financial listed companies are relatively strong. However, under greater pressure of demand of capital transmission (70% edges failed), the transmission channel, which constructed by debit and credit behavior, will eventually collapse.

  5. Latent variable models are network models.

    Science.gov (United States)

    Molenaar, Peter C M

    2010-06-01

    Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.

  6. Mechanisms of diurnal precipitation over the US Great Plains: a cloud resolving model perspective

    Science.gov (United States)

    Lee, Myong-In; Choi, Ildae; Tao, Wei-Kuo; Schubert, Siegfried D.; Kang, In-Sik

    2010-02-01

    The mechanisms of summertime diurnal precipitation in the US Great Plains were examined with the two-dimensional (2D) Goddard Cumulus Ensemble (GCE) cloud-resolving model (CRM). The model was constrained by the observed large-scale background state and surface flux derived from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program’s Intensive Observing Period (IOP) data at the Southern Great Plains (SGP). The model, when continuously-forced by realistic surface flux and large-scale advection, simulates reasonably well the temporal evolution of the observed rainfall episodes, particularly for the strongly forced precipitation events. However, the model exhibits a deficiency for the weakly forced events driven by diurnal convection. Additional tests were run with the GCE model in order to discriminate between the mechanisms that determine daytime and nighttime convection. In these tests, the model was constrained with the same repeating diurnal variation in the large-scale advection and/or surface flux. The results indicate that it is primarily the surface heat and moisture flux that is responsible for the development of deep convection in the afternoon, whereas the large-scale upward motion and associated moisture advection play an important role in preconditioning nocturnal convection. In the nighttime, high clouds are continuously built up through their interaction and feedback with long-wave radiation, eventually initiating deep convection from the boundary layer. Without these upper-level destabilization processes, the model tends to produce only daytime convection in response to boundary layer heating. This study suggests that the correct simulation of the diurnal variation in precipitation requires that the free-atmospheric destabilization mechanisms resolved in the CRM simulation must be adequately parameterized in current general circulation models (GCMs) many of which are overly sensitive to the parameterized boundary layer

  7. Mechanisms of Diurnal Precipitation over the United States Great Plains: A Cloud-Resolving Model Simulation

    Science.gov (United States)

    Lee, M.-I.; Choi, I.; Tao, W.-K.; Schubert, S. D.; Kang, I.-K.

    2010-01-01

    The mechanisms of summertime diurnal precipitation in the US Great Plains were examined with the two-dimensional (2D) Goddard Cumulus Ensemble (GCE) cloud-resolving model (CRM). The model was constrained by the observed large-scale background state and surface flux derived from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program s Intensive Observing Period (IOP) data at the Southern Great Plains (SGP). The model, when continuously-forced by realistic surface flux and large-scale advection, simulates reasonably well the temporal evolution of the observed rainfall episodes, particularly for the strongly forced precipitation events. However, the model exhibits a deficiency for the weakly forced events driven by diurnal convection. Additional tests were run with the GCE model in order to discriminate between the mechanisms that determine daytime and nighttime convection. In these tests, the model was constrained with the same repeating diurnal variation in the large-scale advection and/or surface flux. The results indicate that it is primarily the surface heat and moisture flux that is responsible for the development of deep convection in the afternoon, whereas the large-scale upward motion and associated moisture advection play an important role in preconditioning nocturnal convection. In the nighttime, high clouds are continuously built up through their interaction and feedback with long-wave radiation, eventually initiating deep convection from the boundary layer. Without these upper-level destabilization processes, the model tends to produce only daytime convection in response to boundary layer heating. This study suggests that the correct simulation of the diurnal variation in precipitation requires that the free-atmospheric destabilization mechanisms resolved in the CRM simulation must be adequately parameterized in current general circulation models (GCMs) many of which are overly sensitive to the parameterized boundary layer heating.

  8. Homophyly/Kinship Model: Naturally Evolving Networks

    Science.gov (United States)

    Li, Angsheng; Li, Jiankou; Pan, Yicheng; Yin, Xianchen; Yong, Xi

    2015-10-01

    It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks. Here, we propose the hypothesis that homophyly/kinship is the intrinsic mechanism of natural communities, introduce the notion of the affinity exponent and propose the homophyly/kinship model of networks. We demonstrate that the networks of our model satisfy a number of topological, probabilistic and combinatorial properties and, in particular, that the robustness and stability of natural communities increase as the affinity exponent increases and that the reciprocity of the networks in our model decreases as the affinity exponent increases. We show that both homophyly/kinship and reciprocity are essential to the emergence of cooperation in evolutionary games and that the homophyly/kinship and reciprocity determined by the appropriate affinity exponent guarantee the emergence of cooperation in evolutionary games, verifying Darwin’s proposal that kinship and reciprocity are the means of individual fitness. We propose the new principle of structure entropy minimisation for detecting natural communities of networks and verify the functional module property and characteristic properties by a healthy tissue cell network, a citation network, some metabolic networks and a protein interaction network.

  9. Geo-statistical model of Rainfall erosivity by using high temporal resolution precipitation data in Europe

    Science.gov (United States)

    Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine

    2015-04-01

    Rainfall erosivity (R-factor) is among the 6 input factors in estimating soil erosion risk by using the empirical Revised Universal Soil Loss Equation (RUSLE). R-factor is a driving force for soil erosion modelling and potentially can be used in flood risk assessments, landslides susceptibility, post-fire damage assessment, application of agricultural management practices and climate change modelling. The rainfall erosivity is extremely difficult to model at large scale (national, European) due to lack of high temporal resolution precipitation data which cover long-time series. In most cases, R-factor is estimated based on empirical equations which take into account precipitation volume. The Rainfall Erosivity Database on the European Scale (REDES) is the output of an extensive data collection of high resolution precipitation data in the 28 Member States of the European Union plus Switzerland taking place during 2013-2014 in collaboration with national meteorological/environmental services. Due to different temporal resolutions of the data (5, 10, 15, 30, 60 minutes), conversion equations have been applied in order to homogenise the database at 30-minutes interval. The 1,541 stations included in REDES have been interpolated using the Gaussian Process Regression (GPR) model using as covariates the climatic data (monthly precipitation, monthly temperature, wettest/driest month) from WorldClim Database, Digital Elevation Model and latitude/longitude. GPR has been selected among other candidate models (GAM, Regression Kriging) due the best performance both in cross validation (R2=0.63) and in fitting dataset (R2=0.72). The highest uncertainty has been noticed in North-western Scotland, North Sweden and Finland due to limited number of stations in REDES. Also, in highlands such as Alpine arch and Pyrenees the diversity of environmental features forced relatively high uncertainty. The rainfall erosivity map of Europe available at 500m resolution plus the standard error

  10. Microbial network of the carbonate precipitation process induced by microbial consortia and the potential application to crack healing in concrete.

    Science.gov (United States)

    Zhang, Jiaguang; Zhou, Aijuan; Liu, Yuanzhen; Zhao, Bowei; Luan, Yunbo; Wang, Sufang; Yue, Xiuping; Li, Zhu

    2017-11-06

    Current studies have employed various pure-cultures for improving concrete durability based on microbially induced carbonate precipitation (MICP). However, there have been very few reports concerned with microbial consortia, which could perform more complex tasks and be more robust in their resistance to environmental fluctuations. In this study, we constructed three microbial consortia that are capable of MICP under aerobic (AE), anaerobic (AN) and facultative anaerobic (FA) conditions. The results showed that AE consortia showed more positive effects on inorganic carbon conversion than AN and FA consortia. Pyrosequencing analysis showed that clear distinctions appeared in the community structure between different microbial consortia systems. Further investigation on microbial community networks revealed that the species in the three microbial consortia built thorough energetic and metabolic interaction networks regarding MICP, nitrate-reduction, bacterial endospores and fermentation communities. Crack-healing experiments showed that the selected cracks of the three consortia-based concrete specimens were almost completely healed in 28 days, which was consistent with the studies using pure cultures. Although the economic advantage might not be clear yet, this study highlights the potential implementation of microbial consortia on crack healing in concrete.

  11. Phase-field modeling of Mn-Ni-Si precipitate behavior on the bcc-Fe matrix

    International Nuclear Information System (INIS)

    Chang, Kun Ok; Kwon, Jun Hyun

    2016-01-01

    The formation of Mn-Ni-Si precipitate (hereafter MNS precipitate) is widely accepted by one of the main reasons of late stage hardening and embrittlement of Reactor Pressure Vessel (RPV) during nuclear power plant (NPP) operation. Since MNS precipitate is not considered in current regulatory model, this late stage hardening can be a limiting factor for life extension of nuclear power plants up to 80 or more years. The stability of the MNS precipitate was investigated from the thermodynamic view point and they concluded that MNS precipitate is a stable phase even with very little Cu contents, and they assessed UW1 thermodynamic database which can predict the thermodynamic stability of MNS precipitate at operating temperature of NPP ( ∼ 290 .deg. C). Based on the non-classical nucleation theory, we performed the phase-field modeling of nucleation and growth of MNS precipitate. The microstructure evolution of Mn-Ni-Cu precipitate has been simulated using the phase-field method and their approaches are focused on a role of the Cu contents. Also, a role of the interstitial loop on the nucleation and growth kinetics of MNS precipitate was analyzed.

  12. Predictability of Precipitation Over the Conterminous U.S. Based on the CMIP5 Multi-Model Ensemble

    Science.gov (United States)

    Jiang, Mingkai; Felzer, Benjamin S.; Sahagian, Dork

    2016-01-01

    Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensembles, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950–2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040–2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment. PMID:27425819

  13. Neural network tagging in a toy model

    International Nuclear Information System (INIS)

    Milek, Marko; Patel, Popat

    1999-01-01

    The purpose of this study is a comparison of Artificial Neural Network approach to HEP analysis against the traditional methods. A toy model used in this analysis consists of two types of particles defined by four generic properties. A number of 'events' was created according to the model using standard Monte Carlo techniques. Several fully connected, feed forward multi layered Artificial Neural Networks were trained to tag the model events. The performance of each network was compared to the standard analysis mechanisms and significant improvement was observed

  14. An endogenous model of the credit network

    Science.gov (United States)

    He, Jianmin; Sui, Xin; Li, Shouwei

    2016-01-01

    In this paper, an endogenous credit network model of firm-bank agents is constructed. The model describes the endogenous formation of firm-firm, firm-bank and bank-bank credit relationships. By means of simulations, the model is capable of showing some obvious similarities with empirical evidence found by other scholars: the upper-tail of firm size distribution can be well fitted with a power-law; the bank size distribution can be lognormally distributed with a power-law tail; the bank in-degrees of the interbank credit network as well as the firm-bank credit network fall into two-power-law distributions.

  15. Modelling and designing electric energy networks

    International Nuclear Information System (INIS)

    Retiere, N.

    2003-11-01

    The author gives an overview of his research works in the field of electric network modelling. After a brief overview of technological evolutions from the telegraph to the all-electric fly-by-wire aircraft, he reports and describes various works dealing with a simplified modelling of electric systems and with fractal simulation. Then, he outlines the challenges for the design of electric networks, proposes a design process, gives an overview of various design models, methods and tools, and reports an application in the design of electric networks for future jumbo jets

  16. Elastoplastic phase-field modeling of ζ-hydride precipitation in zirconium alloy: dynamics evolution in inhomogeneous elasticity

    International Nuclear Information System (INIS)

    Oum, G.; Thuinet, L.; Legris, A.

    2015-07-01

    A phase-field (PF) model was developed within the framework of homogeneous and heterogeneous elasticity theory to study the precipitation of ζ-hydride in zirconium. By coupling crystal plasticity to PF we show that plastic strain participates in lowering the transformation stresses, and therefore induces changes in nucleation, growth and morphology evolution of the precipitates. (authors)

  17. Modeling the influence of precipitation and nitrogen deposition on forest understory fuel connectivity in Sierra Nevada mixed-conifer forest

    Science.gov (United States)

    M. Hurteau; M. North; T. Foines

    2009-01-01

    Climate change models for California’s Sierra Nevada predict greater inter-annual variability in precipitation over the next 50 years. These increases in precipitation variability coupled with increases in nitrogen deposition fromfossil fuel consumption are likely to result in increased productivity levels and significant increases in...

  18. Queueing Models for Mobile Ad Hoc Networks

    NARCIS (Netherlands)

    de Haan, Roland

    2009-01-01

    This thesis presents models for the performance analysis of a recent communication paradigm: \\emph{mobile ad hoc networking}. The objective of mobile ad hoc networking is to provide wireless connectivity between stations in a highly dynamic environment. These dynamics are driven by the mobility of

  19. Modeling GMPLS and Optical MPLS Networks

    DEFF Research Database (Denmark)

    Christiansen, Henrik Lehrmann; Wessing, Henrik

    2003-01-01

    . The MPLS concept is attractive because it can work as a unifying control structure. covering all technologies. This paper describes how a novel scheme for optical MPLS and circuit switched GMPLS based networks can incorporated in such multi-domain, MPLS-based scenarios and how it could be modeled. Network...

  20. Cyber threat model for tactical radio networks

    Science.gov (United States)

    Kurdziel, Michael T.

    2014-05-01

    The shift to a full information-centric paradigm in the battlefield has allowed ConOps to be developed that are only possible using modern network communications systems. Securing these Tactical Networks without impacting their capabilities has been a challenge. Tactical networks with fixed infrastructure have similar vulnerabilities to their commercial counterparts (although they need to be secure against adversaries with greater capabilities, resources and motivation). However, networks with mobile infrastructure components and Mobile Ad hoc Networks (MANets) have additional unique vulnerabilities that must be considered. It is useful to examine Tactical Network based ConOps and use them to construct a threat model and baseline cyber security requirements for Tactical Networks with fixed infrastructure, mobile infrastructure and/or ad hoc modes of operation. This paper will present an introduction to threat model assessment. A definition and detailed discussion of a Tactical Network threat model is also presented. Finally, the model is used to derive baseline requirements that can be used to design or evaluate a cyber security solution that can be scaled and adapted to the needs of specific deployments.

  1. Modeling documents with Generative Adversarial Networks

    OpenAIRE

    Glover, John

    2016-01-01

    This paper describes a method for using Generative Adversarial Networks to learn distributed representations of natural language documents. We propose a model that is based on the recently proposed Energy-Based GAN, but instead uses a Denoising Autoencoder as the discriminator network. Document representations are extracted from the hidden layer of the discriminator and evaluated both quantitatively and qualitatively.

  2. Designing Network-based Business Model Ontology

    DEFF Research Database (Denmark)

    Hashemi Nekoo, Ali Reza; Ashourizadeh, Shayegheh; Zarei, Behrouz

    2015-01-01

    Survival on dynamic environment is not achieved without a map. Scanning and monitoring of the market show business models as a fruitful tool. But scholars believe that old-fashioned business models are dead; as they are not included the effect of internet and network in themselves. This paper...... is going to propose e-business model ontology from the network point of view and its application in real world. The suggested ontology for network-based businesses is composed of individuals` characteristics and what kind of resources they own. also, their connections and pre-conceptions of connections...... such as shared-mental model and trust. However, it mostly covers previous business model elements. To confirm the applicability of this ontology, it has been implemented in business angel network and showed how it works....

  3. Development of a Unified Dissolution and Precipitation Model and Its Use for the Prediction of Oral Drug Absorption.

    Science.gov (United States)

    Jakubiak, Paulina; Wagner, Björn; Grimm, Hans Peter; Petrig-Schaffland, Jeannine; Schuler, Franz; Alvarez-Sánchez, Rubén

    2016-02-01

    Drug absorption is a complex process involving dissolution and precipitation, along with other kinetic processes. The purpose of this work was to (1) establish an in vitro methodology to study dissolution and precipitation in early stages of drug development where low compound consumption and high throughput are necessary, (2) develop a mathematical model for a mechanistic explanation of generated in vitro dissolution and precipitation data, and (3) extrapolate in vitro data to in vivo situations using physiologically based models to predict oral drug absorption. Small-scale pH-shift studies were performed in biorelevant media to monitor the precipitation of a set of poorly soluble weak bases. After developing a dissolution-precipitation model from this data, it was integrated into a simplified, physiologically based absorption model to predict clinical pharmacokinetic profiles. The model helped explain the consequences of supersaturation behavior of compounds. The predicted human pharmacokinetic profiles closely aligned with the observed clinical data. In summary, we describe a novel approach combining experimental dissolution/precipitation methodology with a mechanistic model for the prediction of human drug absorption kinetics. The approach unifies the dissolution and precipitation theories and enables accurate predictions of in vivo oral absorption by means of physiologically based modeling.

  4. A model for the biological precipitation of Precambrian iron-formation

    Science.gov (United States)

    Laberge, G. L.

    1986-01-01

    A biological model for the precipitation of Precambrian iron formations is presented. Assuming an oxygen deficient atmosphere and water column to allow sufficient Fe solubility, it is proposed that local oxidizing environments, produced biologically, led to precipitation of iron formations. It is further suggested that spheroidal structures about 30 mm in diameter, which are widespread in low grade cherty rion formations, are relict forms of the organic walled microfossil Eosphaera tylerii. The presence of these structures suggests that the organism may have had a siliceous test, which allowed sufficient rigidity for accumulation and preservation. The model involves precipitation of ferric hydrates by oxidation of iron in the photic zone by a variety of photosynthetic organisms. Silica may have formed in the frustules of silica secreting organisms, including Eosphaera tylerii. Iron formates formed, therefore, by a sediment rain of biologically produced ferric hydrates and silica and other organic material. Siderite and hematite formed diagenetically on basin floors, and subsequent metamorphism produced magnetite and iron silicates.

  5. Performance of the general circulation models in simulating temperature and precipitation over Iran

    Science.gov (United States)

    Abbasian, Mohammadsadegh; Moghim, Sanaz; Abrishamchi, Ahmad

    2018-03-01

    General Circulation Models (GCMs) are advanced tools for impact assessment and climate change studies. Previous studies show that the performance of the GCMs in simulating climate variables varies significantly over different regions. This study intends to evaluate the performance of the Coupled Model Intercomparison Project phase 5 (CMIP5) GCMs in simulating temperature and precipitation over Iran. Simulations from 37 GCMs and observations from the Climatic Research Unit (CRU) were obtained for the period of 1901-2005. Six measures of performance including mean bias, root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), linear correlation coefficient (r), Kolmogorov-Smirnov statistic (KS), Sen's slope estimator, and the Taylor diagram are used for the evaluation. GCMs are ranked based on each statistic at seasonal and annual time scales. Results show that most GCMs perform reasonably well in simulating the annual and seasonal temperature over Iran. The majority of the GCMs have a poor skill to simulate precipitation, particularly at seasonal scale. Based on the results, the best GCMs to represent temperature and precipitation simulations over Iran are the CMCC-CMS (Euro-Mediterranean Center on Climate Change) and the MRI-CGCM3 (Meteorological Research Institute), respectively. The results are valuable for climate and hydrometeorological studies and can help water resources planners and managers to choose the proper GCM based on their criteria.

  6. Coupling Poisson rectangular pulse and multiplicative microcanonical random cascade models to generate sub-daily precipitation timeseries

    Science.gov (United States)

    Pohle, Ina; Niebisch, Michael; Müller, Hannes; Schümberg, Sabine; Zha, Tingting; Maurer, Thomas; Hinz, Christoph

    2018-07-01

    To simulate the impacts of within-storm rainfall variabilities on fast hydrological processes, long precipitation time series with high temporal resolution are required. Due to limited availability of observed data such time series are typically obtained from stochastic models. However, most existing rainfall models are limited in their ability to conserve rainfall event statistics which are relevant for hydrological processes. Poisson rectangular pulse models are widely applied to generate long time series of alternating precipitation events durations and mean intensities as well as interstorm period durations. Multiplicative microcanonical random cascade (MRC) models are used to disaggregate precipitation time series from coarse to fine temporal resolution. To overcome the inconsistencies between the temporal structure of the Poisson rectangular pulse model and the MRC model, we developed a new coupling approach by introducing two modifications to the MRC model. These modifications comprise (a) a modified cascade model ("constrained cascade") which preserves the event durations generated by the Poisson rectangular model by constraining the first and last interval of a precipitation event to contain precipitation and (b) continuous sigmoid functions of the multiplicative weights to consider the scale-dependency in the disaggregation of precipitation events of different durations. The constrained cascade model was evaluated in its ability to disaggregate observed precipitation events in comparison to existing MRC models. For that, we used a 20-year record of hourly precipitation at six stations across Germany. The constrained cascade model showed a pronounced better agreement with the observed data in terms of both the temporal pattern of the precipitation time series (e.g. the dry and wet spell durations and autocorrelations) and event characteristics (e.g. intra-event intermittency and intensity fluctuation within events). The constrained cascade model also

  7. Modeling Precipitation Kinetics During Heat Treatment with Calphad-Based Tools

    Science.gov (United States)

    Chen, Qing; Wu, Kaisheng; Sterner, Gustaf; Mason, Paul

    2014-12-01

    Sophisticated precipitation reaction models combined with well-developed CALPHAD databases provide an efficient way to tailor precipitate microstructures that maximize strengthening via the optimization of alloy chemistries and heat treatment schedules. The success of the CALPHAD approach relies on the capability to provide fundamental phase equilibrium and phase transformation information in materials of industrial relevance taking into consideration composition and temperature variation. The newly developed TC-PRISMA program is described. The effect of growth modes, alloy chemistries, and cooling profiles on the formation of multimodal microstructures has been examined in order to understand the underlying thermodynamics and kinetics. Practical issues that are critical to the accuracy and applicability of the current simulations, such as modifications that overcome mean field approximations, compatibility between CALPHAD databases, and selections of key parameters (particularly interfacial energy and nucleation site densities), are also addressed.

  8. Modelling and dynamic simulation of struvite precipitation from source-separated urine.

    Science.gov (United States)

    Schneider, Philip A; Wallace, James W; Tickle, Julian C

    2013-01-01

    A model of a mixed-mode nutrient recovery reactor is developed for a urine feed, incorporating complex solution thermodynamics, dynamic conservation relations and a power-law kinetic expression for crystal growth from seed crystals. Simulations at nominal operating conditions predict phosphorus recoveries greater than 99%, based on existing process kinetic parameters and operating conditions employed in previously published studies. The overall rate of nutrient recovery depends on the saturation index of the precipitating solid, the available surface area for mass transfer and the feed rate of the limiting constituent ion. Under the conditions considered, the nutrient feed rate appears to be the limiting factor for precipitation. Simulations demonstrate that diurnal feed flow variations of ±50% have a small effect on the rate of nutrient recovery. Overall, the study shows that valuable insights are gained in relation to process performance predictions, which should lead to more confident process design, operation and control.

  9. Modelling of anisotropy for Al-Li 2099 T83 extrusions and effect of precipitate density

    International Nuclear Information System (INIS)

    Bois-Brochu, Alexandre; Blais, Carl; Tchitembo Goma, Franck Armel; Larouche, Daniel

    2016-01-01

    The development of aluminum-lithium alloys for aerospace applications requires a thorough understanding of how processing and product geometry impact their microstructure, texture and mechanical properties. The anisotropy of the mechanical properties is in part related to the deformation texture formed during thermo-mechanical processing. In this study, two different extrusions of Al-Li 2099 T83 were characterized, a cylindrical extrusion and an integrally stiffened panel (ISP). A model is proposed to predict mechanical properties and their anisotropy as a function of the <111> fiber texture. Furthermore, the volume fraction of precipitates was measured in zones of high anisotropy (cylindrical extrusion) and low anisotropy (ISP). Results show that there is no significant difference between the two parts concerning volume fraction of precipitates.

  10. Modelling of anisotropy for Al-Li 2099 T83 extrusions and effect of precipitate density

    Energy Technology Data Exchange (ETDEWEB)

    Bois-Brochu, Alexandre, E-mail: Alexandre.Bois-Brochu.1@ulaval.ca; Blais, Carl, E-mail: Carl.Blais@gmn.ulaval.ca; Tchitembo Goma, Franck Armel, E-mail: Franck-Armel.Tchitembo-Goma.1@ulaval.ca; Larouche, Daniel, E-mail: Daniel.Larouche@gmn.ulaval.ca

    2016-09-15

    The development of aluminum-lithium alloys for aerospace applications requires a thorough understanding of how processing and product geometry impact their microstructure, texture and mechanical properties. The anisotropy of the mechanical properties is in part related to the deformation texture formed during thermo-mechanical processing. In this study, two different extrusions of Al-Li 2099 T83 were characterized, a cylindrical extrusion and an integrally stiffened panel (ISP). A model is proposed to predict mechanical properties and their anisotropy as a function of the <111> fiber texture. Furthermore, the volume fraction of precipitates was measured in zones of high anisotropy (cylindrical extrusion) and low anisotropy (ISP). Results show that there is no significant difference between the two parts concerning volume fraction of precipitates.

  11. Numerical modelling of landscape and sediment flux response to precipitation rate change

    Science.gov (United States)

    Armitage, John J.; Whittaker, Alexander C.; Zakari, Mustapha; Campforts, Benjamin

    2018-02-01

    Laboratory-scale experiments of erosion have demonstrated that landscapes have a natural (or intrinsic) response time to a change in precipitation rate. In the last few decades there has been growth in the development of numerical models that attempt to capture landscape evolution over long timescales. However, there is still an uncertainty regarding the validity of the basic assumptions of mass transport that are made in deriving these models. In this contribution we therefore return to a principal assumption of sediment transport within the mass balance for surface processes; we explore the sensitivity of the classic end-member landscape evolution models and the sediment fluxes they produce to a change in precipitation rates. One end-member model takes the mathematical form of a kinetic wave equation and is known as the stream power model, in which sediment is assumed to be transported immediately out of the model domain. The second end-member model is the transport model and it takes the form of a diffusion equation, assuming that the sediment flux is a function of the water flux and slope. We find that both of these end-member models have a response time that has a proportionality to the precipitation rate that follows a negative power law. However, for the stream power model the exponent on the water flux term must be less than one, and for the transport model the exponent must be greater than one, in order to match the observed concavity of natural systems. This difference in exponent means that the transport model generally responds more rapidly to an increase in precipitation rates, on the order of 105 years for post-perturbation sediment fluxes to return to within 50 % of their initial values, for theoretical landscapes with a scale of 100×100 km. Additionally from the same starting conditions, the amplitude of the sediment flux perturbation in the transport model is greater, with much larger sensitivity to catchment size. An important finding is that

  12. Numerical modelling of landscape and sediment flux response to precipitation rate change

    Directory of Open Access Journals (Sweden)

    J. J. Armitage

    2018-02-01

    Full Text Available Laboratory-scale experiments of erosion have demonstrated that landscapes have a natural (or intrinsic response time to a change in precipitation rate. In the last few decades there has been growth in the development of numerical models that attempt to capture landscape evolution over long timescales. However, there is still an uncertainty regarding the validity of the basic assumptions of mass transport that are made in deriving these models. In this contribution we therefore return to a principal assumption of sediment transport within the mass balance for surface processes; we explore the sensitivity of the classic end-member landscape evolution models and the sediment fluxes they produce to a change in precipitation rates. One end-member model takes the mathematical form of a kinetic wave equation and is known as the stream power model, in which sediment is assumed to be transported immediately out of the model domain. The second end-member model is the transport model and it takes the form of a diffusion equation, assuming that the sediment flux is a function of the water flux and slope. We find that both of these end-member models have a response time that has a proportionality to the precipitation rate that follows a negative power law. However, for the stream power model the exponent on the water flux term must be less than one, and for the transport model the exponent must be greater than one, in order to match the observed concavity of natural systems. This difference in exponent means that the transport model generally responds more rapidly to an increase in precipitation rates, on the order of 105 years for post-perturbation sediment fluxes to return to within 50 % of their initial values, for theoretical landscapes with a scale of 100×100 km. Additionally from the same starting conditions, the amplitude of the sediment flux perturbation in the transport model is greater, with much larger sensitivity to catchment size. An

  13. Modeling trust context in networks

    CERN Document Server

    Adali, Sibel

    2013-01-01

    We make complex decisions every day, requiring trust in many different entities for different reasons. These decisions are not made by combining many isolated trust evaluations. Many interlocking factors play a role, each dynamically impacting the others.? In this brief, 'trust context' is defined as the system level description of how the trust evaluation process unfolds.Networks today are part of almost all human activity, supporting and shaping it. Applications increasingly incorporate new interdependencies and new trust contexts. Social networks connect people and organizations throughout

  14. Mathematical model of highways network optimization

    Science.gov (United States)

    Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.

    2017-12-01

    The article deals with the issue of highways network design. Studies show that the main requirement from road transport for the road network is to ensure the realization of all the transport links served by it, with the least possible cost. The goal of optimizing the network of highways is to increase the efficiency of transport. It is necessary to take into account a large number of factors that make it difficult to quantify and qualify their impact on the road network. In this paper, we propose building an optimal variant for locating the road network on the basis of a mathematical model. The article defines the criteria for optimality and objective functions that reflect the requirements for the road network. The most fully satisfying condition for optimality is the minimization of road and transport costs. We adopted this indicator as a criterion of optimality in the economic-mathematical model of a network of highways. Studies have shown that each offset point in the optimal binding road network is associated with all other corresponding points in the directions providing the least financial costs necessary to move passengers and cargo from this point to the other corresponding points. The article presents general principles for constructing an optimal network of roads.

  15. Sensitivity of Sahelian Precipitation to Desert Dust under ENSO variability: a regional modeling study

    Science.gov (United States)

    Jordan, A.; Zaitchik, B. F.; Gnanadesikan, A.

    2016-12-01

    Mineral dust is estimated to comprise over half the total global aerosol burden, with a majority coming from the Sahara and Sahel region. Bounded by the Sahara Desert to the north and the Sahelian Savannah to the south, the Sahel experiences high interannual rainfall variability and a short rainy season during the boreal summer months. Observation-based data for the past three decades indicates a reduced dust emission trend, together with an increase in greening and surface roughness within the Sahel. Climate models used to study regional precipitation changes due to Saharan dust yield varied results, both in sign convention and magnitude. Inconsistency of model estimates drives future climate projections for the region that are highly varied and uncertain. We use the NASA-Unified Weather Research and Forecasting (NU-WRF) model to quantify the interaction and feedback between desert dust aerosol and Sahelian precipitation. Using nested domains at fine spatial resolution we resolve changes to mesoscale atmospheric circulation patterns due to dust, for representative phases of El Niño-Southern Oscillation (ENSO). The NU-WRF regional earth system model offers both advanced land surface data and resolvable detail of the mechanisms of the impact of Saharan dust. Results are compared to our previous work assessed over the Western Sahel using the Geophysical Fluid Dynamics Laboratory (GFDL) CM2Mc global climate model, and to other previous regional climate model studies. This prompts further research to help explain the dust-precipitation relationship and recent North African dust emission trends. This presentation will offer a quantitative analysis of differences in radiation budget, energy and moisture fluxes, and atmospheric dynamics due to desert dust aerosol over the Sahel.

  16. An integrated modeling study on the effects of mineral dust and sea salt particles on clouds and precipitation

    Directory of Open Access Journals (Sweden)

    S. Solomos

    2011-01-01

    Full Text Available This report addresses the effects of pollution on the development of precipitation in clean ("pristine" and polluted ("hazy" environments in the Eastern Mediterranean by using the Integrated Community Limited Area Modeling System (ICLAMS (an extended version of the Regional Atmospheric Modeling System, RAMS. The use of this model allows one to investigate the interactions of the aerosols with cloud development. The simulations show that the onset of precipitation in hazy clouds is delayed compared to pristine conditions. Adding small concentrations of GCCN to polluted clouds promotes early-stage rain. The addition of GCCN to pristine clouds has no effect on precipitation amounts. Topography was found to be more important for the distribution of precipitation than aerosol properties. Increasing by 15% the concentration of hygroscopic dust particles for a case study over the Eastern Mediterranean resulted in more vigorous convection and more intense updrafts. The clouds that were formed extended about three kilometers higher, delaying the initiation of precipitation by one hour. Prognostic treatment of the aerosol concentrations in the explicit cloud droplet nucleation scheme of the model, improved the model performance for the twenty-four hour accumulated precipitation. The spatial distribution and the amounts of precipitation were found to vary greatly between the different aerosol scenarios. These results indicate the large uncertainty that remains and the need for more accurate description of aerosol feedbacks in atmospheric models and climate change predictions.

  17. Reduced Moment-Based Models for Oxygen Precipitates and Dislocation Loops in Silicon

    Science.gov (United States)

    Trzynadlowski, Bart

    The demand for ever smaller, higher-performance integrated circuits and more efficient, cost-effective solar cells continues to push the frontiers of process technology. Fabrication of silicon devices requires extremely precise control of impurities and crystallographic defects. Failure to do so not only reduces performance, efficiency, and yield, it threatens the very survival of commercial enterprises in today's fiercely competitive and price-sensitive global market. The presence of oxygen in silicon is an unavoidable consequence of the Czochralski process, which remains the most popular method for large-scale production of single-crystal silicon. Oxygen precipitates that form during thermal processing cause distortion of the surrounding silicon lattice and can lead to the formation of dislocation loops. Localized deformation caused by both of these defects introduces potential wells that trap diffusing impurities such as metal atoms, which is highly desirable if done far away from sensitive device regions. Unfortunately, dislocations also reduce the mechanical strength of silicon, which can cause wafer warpage and breakage. Engineers must negotiate this and other complex tradeoffs when designing fabrication processes. Accomplishing this in a complex, modern process involving a large number of thermal steps is impossible without the aid of computational models. In this dissertation, new models for oxygen precipitation and dislocation loop evolution are described. An oxygen model using kinetic rate equations to evolve the complete precipitate size distribution was developed first. This was then used to create a reduced model tracking only the moments of the size distribution. The moment-based model was found to run significantly faster than its full counterpart while accurately capturing the evolution of oxygen precipitates. The reduced model was fitted to experimental data and a sensitivity analysis was performed to assess the robustness of the results. Source

  18. Modelling and Mapping Oxygen-18 Isotope Composition of Precipitation in Spain for Hydrologic and Climatic Applications

    International Nuclear Information System (INIS)

    Rodriguez-Arevalo, J.; Diaz-Teijeiro, M.F.; Castano, S.

    2011-01-01

    A simple multiple regression model based on two geographic factors (latitude and elevation) has been developed that reproduces reasonably well the spatial distribution of the current mean oxygen-18 isotope composition in precipitation over Spain. In a preliminary analysis, additional geographic and climatic factors do not improve the performance of the model. A continuous digital map of oxygen-18 isotope composition in precipitation has been produced by combining the polynomial model with a Digital Elevation Model using GIS tools. Application of the resulting map to several case studies in Spain has shown it to be useful as a reference of the isotope input function to groundwater recharge and surface runoff. The results obtained so far show a good fit between modelled stable isotope values and those measured in surface and ground waters from different aquifers and recharge areas. The GIS tools applied to a continuous digital layer of spatial isotope are able to provide accurate information at detailed scales that are not affordable by other means. Further validation of the model, and further testing of its usefulness in surface hydrology and climatic studies, is going on.

  19. Comparing the impact of time displaced and biased precipitation estimates for online updated urban runoff models.

    Science.gov (United States)

    Borup, Morten; Grum, Morten; Mikkelsen, Peter Steen

    2013-01-01

    When an online runoff model is updated from system measurements, the requirements of the precipitation input change. Using rain gauge data as precipitation input there will be a displacement between the time when the rain hits the gauge and the time where the rain hits the actual catchment, due to the time it takes for the rain cell to travel from the rain gauge to the catchment. Since this time displacement is not present for system measurements the data assimilation scheme might already have updated the model to include the impact from the particular rain cell when the rain data is forced upon the model, which therefore will end up including the same rain twice in the model run. This paper compares forecast accuracy of updated models when using time displaced rain input to that of rain input with constant biases. This is done using a simple time-area model and historic rain series that are either displaced in time or affected with a bias. The results show that for a 10 minute forecast, time displacements of 5 and 10 minutes compare to biases of 60 and 100%, respectively, independent of the catchments time of concentration.

  20. Graphical Model Theory for Wireless Sensor Networks

    International Nuclear Information System (INIS)

    Davis, William B.

    2002-01-01

    Information processing in sensor networks, with many small processors, demands a theory of computation that allows the minimization of processing effort, and the distribution of this effort throughout the network. Graphical model theory provides a probabilistic theory of computation that explicitly addresses complexity and decentralization for optimizing network computation. The junction tree algorithm, for decentralized inference on graphical probability models, can be instantiated in a variety of applications useful for wireless sensor networks, including: sensor validation and fusion; data compression and channel coding; expert systems, with decentralized data structures, and efficient local queries; pattern classification, and machine learning. Graphical models for these applications are sketched, and a model of dynamic sensor validation and fusion is presented in more depth, to illustrate the junction tree algorithm

  1. Modeling Network Traffic in Wavelet Domain

    Directory of Open Access Journals (Sweden)

    Sheng Ma

    2004-12-01

    Full Text Available This work discovers that although network traffic has the complicated short- and long-range temporal dependence, the corresponding wavelet coefficients are no longer long-range dependent. Therefore, a "short-range" dependent process can be used to model network traffic in the wavelet domain. Both independent and Markov models are investigated. Theoretical analysis shows that the independent wavelet model is sufficiently accurate in terms of the buffer overflow probability for Fractional Gaussian Noise traffic. Any model, which captures additional correlations in the wavelet domain, only improves the performance marginally. The independent wavelet model is then used as a unified approach to model network traffic including VBR MPEG video and Ethernet data. The computational complexity is O(N for developing such wavelet models and generating synthesized traffic of length N, which is among the lowest attained.

  2. Sparsity in Model Gene Regulatory Networks

    International Nuclear Information System (INIS)

    Zagorski, M.

    2011-01-01

    We propose a gene regulatory network model which incorporates the microscopic interactions between genes and transcription factors. In particular the gene's expression level is determined by deterministic synchronous dynamics with contribution from excitatory interactions. We study the structure of networks that have a particular '' function '' and are subject to the natural selection pressure. The question of network robustness against point mutations is addressed, and we conclude that only a small part of connections defined as '' essential '' for cell's existence is fragile. Additionally, the obtained networks are sparse with narrow in-degree and broad out-degree, properties well known from experimental study of biological regulatory networks. Furthermore, during sampling procedure we observe that significantly different genotypes can emerge under mutation-selection balance. All the preceding features hold for the model parameters which lay in the experimentally relevant range. (author)

  3. Image-based Modeling of Biofilm-induced Calcium Carbonate Precipitation

    Science.gov (United States)

    Connolly, J. M.; Rothman, A.; Jackson, B.; Klapper, I.; Cunningham, A. B.; Gerlach, R.

    2013-12-01

    Pore scale biological processes in the subsurface environment are important to understand in relation to many engineering applications including environmental contaminant remediation, geologic carbon sequestration, and petroleum production. Specifically, biofilm induced calcium carbonate precipitation has been identified as an attractive option to reduce permeability in a lasting way in the subsurface. This technology may be able to replace typical cement-based grouting in some circumstances; however, pore-scale processes must be better understood for it to be applied in a controlled manor. The work presented will focus on efforts to observe biofilm growth and ureolysis-induced mineral precipitation in micro-fabricated flow cells combined with finite element modelling as a tool to predict local chemical gradients of interest (see figure). We have been able to observe this phenomenon over time using a novel model organism that is able to hydrolyse urea and express a fluorescent protein allowing for non-invasive observation over time with confocal microscopy. The results of this study show the likely existence of a wide range of local saturation indices even in a small (1 cm length scale) experimental system. Interestingly, the locations of high predicted index do not correspond to the locations of higher precipitation density, highlighting the need for further understanding. Figure 1 - A micro-fabricated flow cell containing biofilm-induced calcium carbonate precipitation. (A) Experimental results: Active biofilm is in green and dark circles are calcium carbonate crystals. Note the channeling behavior in the top of the image, leaving a large hydraulically inactive area in the biofilm mass. (B) Finite element model: The prediction of relative saturation of calcium carbonate (as calcite). Fluid enters the system at a low saturation state (blue) but areas of high supersaturation (red) are predicted within the hydraulically inactive area in the biofilm. If only effluent

  4. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    Science.gov (United States)

    Tao, Wei-Kuo; Li, Xiaowen; Khain, Alexander; Matsui, Toshihisa; Lang, Stephen; Simpson, Joanne

    2008-01-01

    ]. Please see Tao et al. (2007) for more detailed description on aerosol impact on precipitation. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated.

  5. Simulated precipitation diurnal cycles over East Asia using different CAPE-based convective closure schemes in WRF model

    Science.gov (United States)

    Yang, Ben; Zhou, Yang; Zhang, Yaocun; Huang, Anning; Qian, Yun; Zhang, Lujun

    2018-03-01

    Closure assumption in convection parameterization is critical for reasonably modeling the precipitation diurnal variation in climate models. This study evaluates the precipitation diurnal cycles over East Asia during the summer of 2008 simulated with three convective available potential energy (CAPE) based closure assumptions, i.e. CAPE-relaxing (CR), quasi-equilibrium (QE), and free-troposphere QE (FTQE) and investigates the impacts of planetary boundary layer (PBL) mixing, advection, and radiation on the simulation by using the weather research and forecasting model. The sensitivity of precipitation diurnal cycle to PBL vertical resolution is also examined. Results show that the precipitation diurnal cycles simulated with different closures all exhibit large biases over land and the simulation with FTQE closure agrees best with observation. In the simulation with QE closure, the intensified PBL mixing after sunrise is responsible for the late-morning peak of convective precipitation, while in the simulation with FTQE closure, convective precipitation is mainly controlled by advection cooling. The relative contributions of different processes to precipitation formation are functions of rainfall intensity. In the simulation with CR closure, the dynamical equilibrium in the free troposphere still can be reached, implying the complex cause-effect relationship between atmospheric motion and convection. For simulations in which total CAPE is consumed for the closures, daytime precipitation decreases with increased PBL resolution because thinner model layer produces lower convection starting layer, leading to stronger downdraft cooling and CAPE consumption. The sensitivity of the diurnal peak time of precipitation to closure assumption can also be modulated by changes in PBL vertical resolution. The results of this study help us better understand the impacts of various processes on the precipitation diurnal cycle simulation.

  6. assessment of neural networks performance in modeling rainfall ...

    African Journals Online (AJOL)

    Sholagberu

    neural network architecture for precipitation prediction of Myanmar, World Academy of. Science, Engineering and Technology, 48, pp. 130 – 134. Kumarasiri, A.D. and Sonnadara, D.U.J. (2006). Rainfall forecasting: an artificial neural network approach, Proceedings of the Technical Sessions,. 22, pp. 1-13 Institute of Physics ...

  7. Challenges for Cloud Modeling in the Context of Aerosol–Cloud–Precipitation Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Lebo, Zachary J. [Department of Atmospheric Science, University of Wyoming, Laramie, Wyoming; Shipway, Ben J. [Met Office, Exeter, United Kingdom; Fan, Jiwen [Pacific Northwest National Laboratory, Richland, Washington; Geresdi, Istvan [Faculty of Science, University of Pécs, Pécs, Hungary; Hill, Adrian [Met Office, Exeter, United Kingdom; Miltenberger, Annette [School of Earth and Environment, University of Leeds, Leeds, United Kingdom; Morrison, Hugh [Mesoscale and Microscale Meteorology Laboratory, National Center for Atmospheric Research, Boulder, Colorado; Rosenberg, Phil [School of Earth and Environment, University of Leeds, Leeds, United Kingdom; Varble, Adam [Department of Atmospheric Sciences, University of Utah, Salt Lake City, Utah; Xue, Lulin [Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

    2017-08-01

    The International Cloud Modeling Workshop (CMW) has been a longstanding tradition in the cloud microphysics modeling community and is typically held the week prior to the International Conference on Clouds and Precipitation (ICCP). For the Ninth CMW, more than 40 participants from 10 countries convened at the Met Office in Exeter, United Kingdom. The workshop included 4 detailed case studies (described in more detail below) rooted in recent field campaigns. The overarching objective of these cases was to utilize new observations to better understand inter-model differences and model deficiencies, explore new modeling techniques, and gain physical insight into the behavior of clouds. As was the case at the Eighth CMW, there was a general theme of understanding the role of aerosol impacts in the context of cloud-precipitation interactions. However, an additional objective was the focal point of several cases at the most recent workshop: microphysical-dynamical interactions. Many of the cases focused less on idealized small-domain simulations (as was the general focus of previous workshops) and more on large-scale nested configurations examining effects at various scales.

  8. A deformation and thermodynamic model for hydride precipitation kinetics in spent fuel cladding

    International Nuclear Information System (INIS)

    Stout, R.B.

    1989-10-01

    Hydrogen is contained in the Zircaloy cladding of spent fuel rods from nuclear reactors. All the spent fuel rods placed in a nuclear waste repository will have a temperature history that decreases toward ambient; and as a result, most all of the hydrogen in the Zircaloy will eventually precipitate as zirconium hydride platelets. A model for the density of hydride platelets is a necessary sub-part for predicting Zircaloy cladding failure rate in a nuclear waste repository. A model is developed to describe statistically the hydride platelet density, and the density function includes the orientation as a physical attribute. The model applies concepts from statistical mechanics to derive probable deformation and thermodynamic functionals for cladding material response that depend explicitly on the hydride platelet density function. From this model, hydride precipitation kinetics depend on a thermodynamic potential for hydride density change and on the inner product of a stress tensor and a tensor measure for the incremental volume change due to hydride platelets. The development of a failure response model for Zircaloy cladding exposed to the expected conditions in a nuclear waste repository is supported by the US DOE Yucca Mountain Project. 19 refs., 3 figs

  9. An adaptive spatial model for precipitation data from multiple satellites over large regions

    KAUST Repository

    Chakraborty, Avishek

    2015-03-01

    Satellite measurements have of late become an important source of information for climate features such as precipitation due to their near-global coverage. In this article, we look at a precipitation dataset during a 3-hour window over tropical South America that has information from two satellites. We develop a flexible hierarchical model to combine instantaneous rainrate measurements from those satellites while accounting for their potential heterogeneity. Conceptually, we envision an underlying precipitation surface that influences the observed rain as well as absence of it. The surface is specified using a mean function centered at a set of knot locations, to capture the local patterns in the rainrate, combined with a residual Gaussian process to account for global correlation across sites. To improve over the commonly used pre-fixed knot choices, an efficient reversible jump scheme is used to allow the number of such knots as well as the order and support of associated polynomial terms to be chosen adaptively. To facilitate computation over a large region, a reduced rank approximation for the parent Gaussian process is employed.

  10. A unique model system of microbial carbonate precipitation: Stromatolites of Lagoa Vermelha, Brazil

    Science.gov (United States)

    Warthmann, R. J.; Vasoncelos, C.; van Lith, Y.; Visscher, P. T.; McKenzie, J. A.

    2003-04-01

    this unique model ecosystem controlling microbial carbonate, including dolomite precipitation will provide important insights about ancient biomineralization processes, especially during the Precambrian.

  11. Tracer water transport and subgrid precipitation variation within atmospheric general circulation models

    Science.gov (United States)

    Koster, Randal D.; Eagleson, Peter S.; Broecker, Wallace S.

    1988-03-01

    A capability is developed for monitoring tracer water movement in the three-dimensional Goddard Institute for Space Science Atmospheric General Circulation Model (GCM). A typical experiment with the tracer water model follows water evaporating from selected grid squares and determines where this water first returns to the Earth's surface as precipitation or condensate, thereby providing information on the lateral scales of hydrological transport in the GCM. Through a comparison of model results with observations in nature, inferences can be drawn concerning real world water transport. Tests of the tracer water model include a comparison of simulated and observed vertically-integrated vapor flux fields and simulations of atomic tritium transport from the stratosphere to the oceans. The inter-annual variability of the tracer water model results is also examined.

  12. Tracer water transport and subgrid precipitation variation within atmospheric general circulation models

    Science.gov (United States)

    Koster, Randal D.; Eagleson, Peter S.; Broecker, Wallace S.

    1988-01-01

    A capability is developed for monitoring tracer water movement in the three-dimensional Goddard Institute for Space Science Atmospheric General Circulation Model (GCM). A typical experiment with the tracer water model follows water evaporating from selected grid squares and determines where this water first returns to the Earth's surface as precipitation or condensate, thereby providing information on the lateral scales of hydrological transport in the GCM. Through a comparison of model results with observations in nature, inferences can be drawn concerning real world water transport. Tests of the tracer water model include a comparison of simulated and observed vertically-integrated vapor flux fields and simulations of atomic tritium transport from the stratosphere to the oceans. The inter-annual variability of the tracer water model results is also examined.

  13. Precipitation-centered Conceptual Model for Sub-humid Uplands in Lampasas Cut Plains, TX

    Science.gov (United States)

    Potter, S. R.; Tu, M.; Wilcox, B. P.

    2011-12-01

    Conceptual understandings of dominant hydrological processes, system interactions and feedbacks, and external forcings operating within catchments often defy simple definition and explanation, especially catchments encompassing transition zones, degraded landscapes, rapid development, and where climate forcings exhibit large variations across time and space. However, it is precisely those areas for which understanding and knowledge are most needed to innovate sustainable management strategies and counter past management blunders and failed restoration efforts. The cut plain of central Texas is one such area. Complex geographic and climatic factors lead to spatially and temporally variable precipitation having frequent dry periods interrupted by intense high-volume precipitation. Fort Hood, an army post located in the southeast cut plain contains landscapes ranging from highly degraded to nearly pristine with a topography mainly comprised of flat-topped mesas separated by broad u-shaped valleys. To understand the hydrology of the area and responses to wet-dry cycles we analyzed 4-years of streamflow and rainfall from 8 catchments, sized between 1819 and 16,000 ha. Since aquifer recharge/discharge and surface stream-groundwater interactions are unimportant, we hypothesized a simple conceptual model driven by precipitation and radiative forcings and having stormflow, baseflow, ET, and two hypothetical storage components. The key storage component was conceptualized as a buffer that was highly integrated with the ET component and exerted controls on baseflow. Radiative energy controlled flux from the buffer to ET. We used the conceptual model in making a bimonthly hydrologic budget, which included buffer volumes and a deficit-surplus indicator. Through the analysis, we were led to speculate that buffer capacity plays key roles in these landscapes and even relatively minor changes in capacity, due to soil compaction for example, might lead to ecological shifts. The

  14. Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

    Science.gov (United States)

    Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

    2018-04-01

    A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is

  15. The QKD network: model and routing scheme

    Science.gov (United States)

    Yang, Chao; Zhang, Hongqi; Su, Jinhai

    2017-11-01

    Quantum key distribution (QKD) technology can establish unconditional secure keys between two communicating parties. Although this technology has some inherent constraints, such as the distance and point-to-point mode limits, building a QKD network with multiple point-to-point QKD devices can overcome these constraints. Considering the development level of current technology, the trust relaying QKD network is the first choice to build a practical QKD network. However, the previous research didn't address a routing method on the trust relaying QKD network in detail. This paper focuses on the routing issues, builds a model of the trust relaying QKD network for easily analysing and understanding this network, and proposes a dynamical routing scheme for this network. From the viewpoint of designing a dynamical routing scheme in classical network, the proposed scheme consists of three components: a Hello protocol helping share the network topology information, a routing algorithm to select a set of suitable paths and establish the routing table and a link state update mechanism helping keep the routing table newly. Experiments and evaluation demonstrates the validity and effectiveness of the proposed routing scheme.

  16. A Model of Network Porosity

    Science.gov (United States)

    2016-11-09

    Figure 1. We generally express such networks in terms of the services running in each enclave as well as the routing and firewall rules between the...compromise a server, they can compromise other devices in the same subnet or protected enclave. They probe attached firewalls and routers for open ports and...spam and malware filter would prevent this content from reaching its destination. Content filtering provides another layer of defense to other controls

  17. Can small island mountains provide relief from the Subtropical Precipitation Decline? Simulating future precipitation regimes for small island nations using high resolution Regional Climate Models.

    Science.gov (United States)

    Bowden, J.; Terando, A. J.; Misra, V.; Wootten, A.

    2017-12-01

    Small island nations are vulnerable to changes in the hydrologic cycle because of their limited water resources. This risk to water security is likely even higher in sub-tropical regions where anthropogenic forcing of the climate system is expected to lead to a drier future (the so-called `dry-get-drier' pattern). However, high-resolution numerical modeling experiments have also shown an enhancement of existing orographically-influenced precipitation patterns on islands with steep topography, potentially mitigating subtropical drying on windward mountain sides. Here we explore the robustness of the near-term (25-45 years) subtropical precipitation decline (SPD) across two island groupings in the Caribbean, Puerto Rico and the U.S. Virgin Islands. These islands, forming the boundary between the Greater and Lesser Antilles, significantly differ in size, topographic relief, and orientation to prevailing winds. Two 2-km horizontal resolution regional climate model simulations are used to downscale a total of three different GCMs under the RCP8.5 emissions scenario. Results indicate some possibility for modest increases in precipitation at the leading edge of the Luquillo Mountains in Puerto Rico, but consistent declines elsewhere. We conclude with a discussion of potential explanations for these patterns and the attendant risks to water security that subtropical small island nations could face as the climate warms.

  18. Thermal conductivity model for nanofiber networks

    Science.gov (United States)

    Zhao, Xinpeng; Huang, Congliang; Liu, Qingkun; Smalyukh, Ivan I.; Yang, Ronggui

    2018-02-01

    Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.

  19. Thermal conductivity model for nanofiber networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Xinpeng [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Huang, Congliang [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China; Liu, Qingkun [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Smalyukh, Ivan I. [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Yang, Ronggui [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Buildings and Thermal Systems Center, National Renewable Energy Laboratory, Golden, Colorado 80401, USA

    2018-02-28

    Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.

  20. A quantum-implementable neural network model

    Science.gov (United States)

    Chen, Jialin; Wang, Lingli; Charbon, Edoardo

    2017-10-01

    A quantum-implementable neural network, namely quantum probability neural network (QPNN) model, is proposed in this paper. QPNN can use quantum parallelism to trace all possible network states to improve the result. Due to its unique quantum nature, this model is robust to several quantum noises under certain conditions, which can be efficiently implemented by the qubus quantum computer. Another advantage is that QPNN can be used as memory to retrieve the most relevant data and even to generate new data. The MATLAB experimental results of Iris data classification and MNIST handwriting recognition show that much less neuron resources are required in QPNN to obtain a good result than the classical feedforward neural network. The proposed QPNN model indicates that quantum effects are useful for real-life classification tasks.

  1. Combinatorial explosion in model gene networks

    Science.gov (United States)

    Edwards, R.; Glass, L.

    2000-09-01

    The explosive growth in knowledge of the genome of humans and other organisms leaves open the question of how the functioning of genes in interacting networks is coordinated for orderly activity. One approach to this problem is to study mathematical properties of abstract network models that capture the logical structures of gene networks. The principal issue is to understand how particular patterns of activity can result from particular network structures, and what types of behavior are possible. We study idealized models in which the logical structure of the network is explicitly represented by Boolean functions that can be represented by directed graphs on n-cubes, but which are continuous in time and described by differential equations, rather than being updated synchronously via a discrete clock. The equations are piecewise linear, which allows significant analysis and facilitates rapid integration along trajectories. We first give a combinatorial solution to the question of how many distinct logical structures exist for n-dimensional networks, showing that the number increases very rapidly with n. We then outline analytic methods that can be used to establish the existence, stability and periods of periodic orbits corresponding to particular cycles on the n-cube. We use these methods to confirm the existence of limit cycles discovered in a sample of a million randomly generated structures of networks of 4 genes. Even with only 4 genes, at least several hundred different patterns of stable periodic behavior are possible, many of them surprisingly complex. We discuss ways of further classifying these periodic behaviors, showing that small mutations (reversal of one or a few edges on the n-cube) need not destroy the stability of a limit cycle. Although these networks are very simple as models of gene networks, their mathematical transparency reveals relationships between structure and behavior, they suggest that the possibilities for orderly dynamics in such

  2. Impact of Precipitating Ice Hydrometeors on Longwave Radiative Effect Estimated by a Global Cloud-System Resolving Model

    Science.gov (United States)

    Chen, Ying-Wen; Seiki, Tatsuya; Kodama, Chihiro; Satoh, Masaki; Noda, Akira T.

    2018-02-01

    Satellite observation and general circulation model (GCM) studies suggest that precipitating ice makes nonnegligible contributions to the radiation balance of the Earth. However, in most GCMs, precipitating ice is diagnosed and its radiative effects are not taken into account. Here we examine the longwave radiative impact of precipitating ice using a global nonhydrostatic atmospheric model with a double-moment cloud microphysics scheme. An off-line radiation model is employed to determine cloud radiative effects according to the amount and altitude of each type of ice hydrometeor. Results show that the snow radiative effect reaches 2 W m-2 in the tropics, which is about half the value estimated by previous studies. This effect is strongly dependent on the vertical separation of ice categories and is partially generated by differences in terminal velocities, which are not represented in GCMs with diagnostic precipitating ice. Results from sensitivity experiments that artificially change the categories and altitudes of precipitating ice show that the simulated longwave heating profile and longwave radiation field are sensitive to the treatment of precipitating ice in models. This study emphasizes the importance of incorporating appropriate treatments for the radiative effects of precipitating ice in cloud and radiation schemes in GCMs in order to capture the cloud radiative effects of upper level clouds.

  3. Complex networks under dynamic repair model

    Science.gov (United States)

    Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

    2018-01-01

    Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

  4. Performance modeling, stochastic networks, and statistical multiplexing

    CERN Document Server

    Mazumdar, Ravi R

    2013-01-01

    This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the importan

  5. Network Modeling and Simulation A Practical Perspective

    CERN Document Server

    Guizani, Mohsen; Khan, Bilal

    2010-01-01

    Network Modeling and Simulation is a practical guide to using modeling and simulation to solve real-life problems. The authors give a comprehensive exposition of the core concepts in modeling and simulation, and then systematically address the many practical considerations faced by developers in modeling complex large-scale systems. The authors provide examples from computer and telecommunication networks and use these to illustrate the process of mapping generic simulation concepts to domain-specific problems in different industries and disciplines. Key features: Provides the tools and strate

  6. Development of a methodology for probable maximum precipitation estimation over the American River watershed using the WRF model

    Science.gov (United States)

    Tan, Elcin

    A new physically-based methodology for probable maximum precipitation (PMP) estimation is developed over the American River Watershed (ARW) using the Weather Research and Forecast (WRF-ARW) model. A persistent moisture flux convergence pattern, called Pineapple Express, is analyzed for 42 historical extreme precipitation events, and it is found that Pineapple Express causes extreme precipitation over the basin of interest. An average correlation between moisture flux convergence and maximum precipitation is estimated as 0.71 for 42 events. The performance of the WRF model is verified for precipitation by means of calibration and independent validation of the model. The calibration procedure is performed only for the first ranked flood event 1997 case, whereas the WRF model is validated for 42 historical cases. Three nested model domains are set up with horizontal resolutions of 27 km, 9 km, and 3 km over the basin of interest. As a result of Chi-square goodness-of-fit tests, the hypothesis that "the WRF model can be used in the determination of PMP over the ARW for both areal average and point estimates" is accepted at the 5% level of significance. The sensitivities of model physics options on precipitation are determined using 28 microphysics, atmospheric boundary layer, and cumulus parameterization schemes combinations. It is concluded that the best triplet option is Thompson microphysics, Grell 3D ensemble cumulus, and YSU boundary layer (TGY), based on 42 historical cases, and this TGY triplet is used for all analyses of this research. Four techniques are proposed to evaluate physically possible maximum precipitation using the WRF: 1. Perturbations of atmospheric conditions; 2. Shift in atmospheric conditions; 3. Replacement of atmospheric conditions among historical events; and 4. Thermodynamically possible worst-case scenario creation. Moreover, climate change effect on precipitation is discussed by emphasizing temperature increase in order to determine the

  7. Modeling acquaintance networks based on balance theory

    Directory of Open Access Journals (Sweden)

    Vukašinović Vida

    2014-09-01

    Full Text Available An acquaintance network is a social structure made up of a set of actors and the ties between them. These ties change dynamically as a consequence of incessant interactions between the actors. In this paper we introduce a social network model called the Interaction-Based (IB model that involves well-known sociological principles. The connections between the actors and the strength of the connections are influenced by the continuous positive and negative interactions between the actors and, vice versa, the future interactions are more likely to happen between the actors that are connected with stronger ties. The model is also inspired by the social behavior of animal species, particularly that of ants in their colony. A model evaluation showed that the IB model turned out to be sparse. The model has a small diameter and an average path length that grows in proportion to the logarithm of the number of vertices. The clustering coefficient is relatively high, and its value stabilizes in larger networks. The degree distributions are slightly right-skewed. In the mature phase of the IB model, i.e., when the number of edges does not change significantly, most of the network properties do not change significantly either. The IB model was found to be the best of all the compared models in simulating the e-mail URV (University Rovira i Virgili of Tarragona network because the properties of the IB model more closely matched those of the e-mail URV network than the other models

  8. Modeling particulate removal in plate-plate and wire-plate electrostatic precipitators

    Directory of Open Access Journals (Sweden)

    S Ramechecandane

    2016-09-01

    Full Text Available The present study is concerned with the modeling of electrically charged particles in a model plate-plate and a single wire-plate electrostatic precipitator (ESP. The particle concentration distributions for both a plate-plate and a wire-plate ESP are calculated using a modified drift flux model. Numerical investigations are performed using the modified drift flux model for particle number concentration, in addition to the RNG k - ε model for the mean turbulent flow field and the Poisson equation for the electric field. The proposed model and the outlined methodology for coupling the flow field, electric field, charging kinetics and particle concentration is applied to two model precipitators that are truly representative of a wide class of commercialized ESPs. The present investigation is quite different from the earlier studies as it does not make assumptions like a homogeneous electric field or an infinite turbulent diffusivity. The electric field calculated is a strong function of position and controls the migration velocity of particles. Hence, the proposed model can be implemented in a flow solver to obtain a full-fledged solution for any kind of ESP with no limitations on the particle number concentration, as encountered in a Lagrangian approach. The effect of turbulent diffusivity on particle number concentration in a plate-plate ESP is investigated in detail and the results obtained are compared with available experimental data. Similarly, the effect of particle size/diameter and applied electric potential on the accumulative collection performance in the case of a wire-plate ESP is studied and the results obtained are compared with available numerical data. The numerical results obtained using the modified drift flux model for both the plate-plate and wire-plate ESP are in close agreement with available experimental and numerical data.

  9. Optimal transportation networks models and theory

    CERN Document Server

    Bernot, Marc; Morel, Jean-Michel

    2009-01-01

    The transportation problem can be formalized as the problem of finding the optimal way to transport a given measure into another with the same mass. In contrast to the Monge-Kantorovitch problem, recent approaches model the branched structure of such supply networks as minima of an energy functional whose essential feature is to favour wide roads. Such a branched structure is observable in ground transportation networks, in draining and irrigation systems, in electrical power supply systems and in natural counterparts such as blood vessels or the branches of trees. These lectures provide mathematical proof of several existence, structure and regularity properties empirically observed in transportation networks. The link with previous discrete physical models of irrigation and erosion models in geomorphology and with discrete telecommunication and transportation models is discussed. It will be mathematically proven that the majority fit in the simple model sketched in this volume.

  10. Flood routing modelling with Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    R. Peters

    2006-01-01

    Full Text Available For the modelling of the flood routing in the lower reaches of the Freiberger Mulde river and its tributaries the one-dimensional hydrodynamic modelling system HEC-RAS has been applied. Furthermore, this model was used to generate a database to train multilayer feedforward networks. To guarantee numerical stability for the hydrodynamic modelling of some 60 km of streamcourse an adequate resolution in space requires very small calculation time steps, which are some two orders of magnitude smaller than the input data resolution. This leads to quite high computation requirements seriously restricting the application – especially when dealing with real time operations such as online flood forecasting. In order to solve this problem we tested the application of Artificial Neural Networks (ANN. First studies show the ability of adequately trained multilayer feedforward networks (MLFN to reproduce the model performance.

  11. Multidecadal trends in the duration of wet spells and associated intensity of precipitation as revealed by a very dense observational German network

    International Nuclear Information System (INIS)

    Zolina, Olga

    2014-01-01

    Precipitation durations and intensities over the period 1950–2008 are analysed using daily rain gauge data from the Deutsche Wetterdienst raingauge network—one of the densest and most properly maintained precipitation observational networks in Europe. Truncated geometric distribution of the family of discrete distributions was applied for quantifying probability distribution of the durations of wet spells. Further intensities of wet spells of different durations were analysed along with wet spell lengths. During the cold season (October–March) wet periods over the whole of Germany demonstrate a robust pattern of lengthening by about 2–3% for the mean durations of wet spells and up to 6% for extremely long wet periods. This tendency is clearly associated with growing (up to 10% per decade in Eastern Germany) intensity of precipitation during long wet periods (more than 5 days) and the weakening of precipitation events associated with short and moderately long wet periods with both signals being statistically significant. Trends are superimposed with interdecadal variability, which is the strongest in Northern and Central Germany. In the warm season (April–September) there is no robust pan-German trend pattern in the wet spell durations and associated precipitation intensities. Strong structural changes in winter precipitation over Germany potentially imply growing rates of winter ground water recharge over Germany and increasing probability of winter flash and river flooding. (paper)

  12. Linear approximation model network and its formation via ...

    Indian Academy of Sciences (India)

    To overcome the deficiency of `local model network' (LMN) techniques, an alternative `linear approximation model' (LAM) network approach is proposed. Such a network models a nonlinear or practical system with multiple linear models fitted along operating trajectories, where individual models are simply networked ...

  13. Errors and parameter estimation in precipitation-runoff modeling: 1. Theory

    Science.gov (United States)

    Troutman, Brent M.

    1985-01-01

    Errors in complex conceptual precipitation-runoff models may be analyzed by placing them into a statistical framework. This amounts to treating the errors as random variables and defining the probabilistic structure of the errors. By using such a framework, a large array of techniques, many of which have been presented in the statistical literature, becomes available to the modeler for quantifying and analyzing the various sources of error. A number of these techniques are reviewed in this paper, with special attention to the peculiarities of hydrologic models. Known methodologies for parameter estimation (calibration) are particularly applicable for obtaining physically meaningful estimates and for explaining how bias in runoff prediction caused by model error and input error may contribute to bias in parameter estimation.

  14. Asymmetric Responses of Primary Productivity to Altered Precipitation Simulated by Land Surface Models across Three Long-term Grassland Sites

    Science.gov (United States)

    Wu, D.; Ciais, P.; Viovy, N.; Knapp, A.; Wilcox, K.; Bahn, M.; Smith, M. D.; Ito, A.; Arneth, A.; Harper, A. B.; Ukkola, A.; Paschalis, A.; Poulter, B.; Peng, C.; Reick, C. H.; Hayes, D. J.; Ricciuto, D. M.; Reinthaler, D.; Chen, G.; Tian, H.; Helene, G.; Zscheischler, J.; Mao, J.; Ingrisch, J.; Nabel, J.; Pongratz, J.; Boysen, L.; Kautz, M.; Schmitt, M.; Krohn, M.; Zeng, N.; Meir, P.; Zhang, Q.; Zhu, Q.; Hasibeder, R.; Vicca, S.; Sippel, S.; Dangal, S. R. S.; Fatichi, S.; Sitch, S.; Shi, X.; Wang, Y.; Luo, Y.; Liu, Y.; Piao, S.

    2017-12-01

    Changes in precipitation variability including the occurrence of extreme events strongly influence plant growth in grasslands. Field measurements of aboveground net primary production (ANPP) in temperate grasslands suggest a positive asymmetric response with wet years resulting in ANPP gains larger than ANPP declines in dry years. Whether land surface models used for historical simulations and future projections of the coupled carbon-water system in grasslands are capable to simulate such non-symmetrical ANPP responses remains an important open research question. In this study, we evaluate the simulated responses of grassland primary productivity to altered precipitation with fourteen land surface models at the three sites of Colorado Shortgrass Steppe (SGS), Konza prairie (KNZ) and Stubai Valley meadow (STU) along a rainfall gradient from dry to wet. Our results suggest that: (i) Gross primary production (GPP), NPP, ANPP and belowground NPP (BNPP) show nonlinear response curves (concave-down) in all the models, but with different curvatures and mean values. In contrast across the sites, primary production increases and then saturates along increasing precipitation with a flattening at the wetter site. (ii) Slopes of spatial relationships between modeled primary production and precipitation are steeper than the temporal slopes (obtained from inter-annual variations). (iii) Asymmetric responses under nominal precipitation range with modeled inter-annual primary production show large uncertainties, and model-ensemble median generally suggests negative asymmetry (greater declines in dry years than increases in wet years) across the three sites. (iv) Primary production at the drier site is predicted to more sensitive to precipitation compared to wetter site, and median sensitivity consistently indicates greater negative impacts of reduced precipitation than positive effects of increased precipitation under extreme conditions. This study implies that most models

  15. Modeling Security Aspects of Network

    Science.gov (United States)

    Schoch, Elmar

    With more and more widespread usage of computer systems and networks, dependability becomes a paramount requirement. Dependability typically denotes tolerance or protection against all kinds of failures, errors and faults. Sources of failures can basically be accidental, e.g., in case of hardware errors or software bugs, or intentional due to some kind of malicious behavior. These intentional, malicious actions are subject of security. A more complete overview on the relations between dependability and security can be found in [31]. In parallel to the increased use of technology, misuse also has grown significantly, requiring measures to deal with it.

  16. Validation of EURO-CORDEX regional climate models in reproducing the variability of precipitation extremes in Romania

    Science.gov (United States)

    Dumitrescu, Alexandru; Busuioc, Aristita

    2016-04-01

    EURO-CORDEX is the European branch of the international CORDEX initiative that aims to provide improved regional climate change projections for Europe. The main objective of this paper is to document the performance of the individual models in reproducing the variability of precipitation extremes in Romania. Here three EURO-CORDEX regional climate models (RCMs) ensemble (scenario RCP4.5) are analysed and inter-compared: DMI-HIRHAM5, KNMI-RACMO2.2 and MPI-REMO. Compared to previous studies, when the RCM validation regarding the Romanian climate has mainly been made on mean state and at station scale, a more quantitative approach of precipitation extremes is proposed. In this respect, to have a more reliable comparison with observation, a high resolution daily precipitation gridded data set was used as observational reference (CLIMHYDEX project). The comparison between the RCM outputs and observed grid point values has been made by calculating three extremes precipitation indices, recommended by the Expert Team on Climate Change Detection Indices (ETCCDI), for the 1976-2005 period: R10MM, annual count of days when precipitation ≥10mm; RX5DAY, annual maximum 5-day precipitation and R95P%, precipitation fraction of annual total precipitation due to daily precipitation > 95th percentile. The RCMs capability to reproduce the mean state for these variables, as well as the main modes of their spatial variability (given by the first three EOF patterns), are analysed. The investigation confirms the ability of RCMs to simulate the main features of the precipitation extreme variability over Romania, but some deficiencies in reproducing of their regional characteristics were found (for example, overestimation of the mea state, especially over the extra Carpathian regions). This work has been realised within the research project "Changes in climate extremes and associated impact in hydrological events in Romania" (CLIMHYDEX), code PN II-ID-2011-2-0073, financed by the Romanian

  17. Modeling and optimization of an electric power distribution network ...

    African Journals Online (AJOL)

    Modeling and optimization of an electric power distribution network planning system using ... of the network was modelled with non-linear mathematical expressions. ... given feasible locations, re-conductoring of existing feeders in the network, ...

  18. Hydrological modelling of the Mabengnong catchment in the southeast Tibet with support of short term intensive precipitation observation

    Science.gov (United States)

    Wang, L.; Zhang, F.; Zhang, H.; Scott, C. A.; Zeng, C.; SHI, X.

    2017-12-01

    Precipitation is one of the crucial inputs for models used to better understand hydrological processes. In high mountain areas, it is a difficult task to obtain a reliable precipitation data set describing the spatial and temporal characteristic due to the limited meteorological observations and high variability of precipitation. This study carries out intensive observation of precipitation in a high mountain catchment in the southeast of the Tibet during July to August 2013. According to the rain gauges set up at different altitudes, it is found that precipitation is greatly influenced by altitude. The observed precipitation is used to depict the precipitation gradient (PG) and hourly distribution (HD), showing that the average duration is around 0.1, 0.8 and 6.0 hours and the average PG is 0.10, 0.28 and 0.26 mm/d/100m for trace, light and moderate rain, respectively. Based on the gridded precipitation derived from the PG and HD and the nearby Linzhi meteorological station at lower altitude, a distributed biosphere hydrological model based on water and energy budgets (WEB-DHM) is applied to simulate the hydrological processes. Beside the observed runoff, MODIS/Terra snow cover area (SCA) data, and MODIS/Terra land surface temperature (LST) data are also used for model calibration and validation. The resulting runoff, SCA and LST simulations are all reasonable. Sensitivity analyses indicate that runoff is greatly underestimated without considering PG, illustrating that short-term intensive precipitation observation contributes to improving hydrological modelling of poorly gauged high mountain catchments.

  19. On the importance of appropriate precipitation gauge catch correction for hydrological modelling at mid to high latitudes

    Science.gov (United States)

    Stisen, S.; Højberg, A. L.; Troldborg, L.; Refsgaard, J. C.; Christensen, B. S. B.; Olsen, M.; Henriksen, H. J.

    2012-11-01

    Precipitation gauge catch correction is often given very little attention in hydrological modelling compared to model parameter calibration. This is critical because significant precipitation biases often make the calibration exercise pointless, especially when supposedly physically-based models are in play. This study addresses the general importance of appropriate precipitation catch correction through a detailed modelling exercise. An existing precipitation gauge catch correction method addressing solid and liquid precipitation is applied, both as national mean monthly correction factors based on a historic 30 yr record and as gridded daily correction factors based on local daily observations of wind speed and temperature. The two methods, named the historic mean monthly (HMM) and the time-space variable (TSV) correction, resulted in different winter precipitation rates for the period 1990-2010. The resulting precipitation datasets were evaluated through the comprehensive Danish National Water Resources model (DK-Model), revealing major differences in both model performance and optimised model parameter sets. Simulated stream discharge is improved significantly when introducing the TSV correction, whereas the simulated hydraulic heads and multi-annual water balances performed similarly due to recalibration adjusting model parameters to compensate for input biases. The resulting optimised model parameters are much more physically plausible for the model based on the TSV correction of precipitation. A proxy-basin test where calibrated DK-Model parameters were transferred to another region without site specific calibration showed better performance for parameter values based on the TSV correction. Similarly, the performances of the TSV correction method were superior when considering two single years with a much dryer and a much wetter winter, respectively, as compared to the winters in the calibration period (differential split-sample tests). We conclude that TSV

  20. On the importance of appropriate precipitation gauge catch correction for hydrological modelling at mid to high latitudes

    Directory of Open Access Journals (Sweden)

    S. Stisen

    2012-11-01

    Full Text Available Precipitation gauge catch correction is often given very little attention in hydrological modelling compared to model parameter calibration. This is critical because significant precipitation biases often make the calibration exercise pointless, especially when supposedly physically-based models are in play. This study addresses the general importance of appropriate precipitation catch correction through a detailed modelling exercise. An existing precipitation gauge catch correction method addressing solid and liquid precipitation is applied, both as national mean monthly correction factors based on a historic 30 yr record and as gridded daily correction factors based on local daily observations of wind speed and temperature. The two methods, named the historic mean monthly (HMM and the time–space variable (TSV correction, resulted in different winter precipitation rates for the period 1990–2010. The resulting precipitation datasets were evaluated through the comprehensive Danish National Water Resources model (DK-Model, revealing major differences in both model performance and optimised model parameter sets. Simulated stream discharge is improved significantly when introducing the TSV correction, whereas the simulated hydraulic heads and multi-annual water balances performed similarly due to recalibration adjusting model parameters to compensate for input biases. The resulting optimised model parameters are much more physically plausible for the model based on the TSV correction of precipitation. A proxy-basin test where calibrated DK-Model parameters were transferred to another region without site specific calibration showed better performance for parameter values based on the TSV correction. Similarly, the performances of the TSV correction method were superior when considering two single years with a much dryer and a much wetter winter, respectively, as compared to the winters in the calibration period (differential split-sample tests

  1. An evolving network model with modular growth

    International Nuclear Information System (INIS)

    Zou Zhi-Yun; Liu Peng; Lei Li; Gao Jian-Zhi

    2012-01-01

    In this paper, we propose an evolving network model growing fast in units of module, according to the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected nodes and the nodes between the modules are linked by preferential attachment on degree of nodes. We study the modularity measure of the proposed model, which can be adjusted by changing the ratio of the number of inner-module edges and the number of inter-module edges. In view of the mean-field theory, we develop an analytical function of the degree distribution, which is verified by a numerical example and indicates that the degree distribution shows characteristics of the small-world network and the scale-free network distinctly at different segments. The clustering coefficient and the average path length of the network are simulated numerically, indicating that the network shows the small-world property and is affected little by the randomness of the new module. (interdisciplinary physics and related areas of science and technology)

  2. Modeling of contact tracing in social networks

    Science.gov (United States)

    Tsimring, Lev S.; Huerta, Ramón

    2003-07-01

    Spreading of certain infections in complex networks is effectively suppressed by using intelligent strategies for epidemic control. One such standard epidemiological strategy consists in tracing contacts of infected individuals. In this paper, we use a recently introduced generalization of the standard susceptible-infectious-removed stochastic model for epidemics in sparse random networks which incorporates an additional (traced) state. We describe a deterministic mean-field description which yields quantitative agreement with stochastic simulations on random graphs. We also discuss the role of contact tracing in epidemics control in small-world and scale-free networks. Effectiveness of contact tracing grows as the rewiring probability is reduced.

  3. A Network Model of Credit Risk Contagion

    Directory of Open Access Journals (Sweden)

    Ting-Qiang Chen

    2012-01-01

    Full Text Available A network model of credit risk contagion is presented, in which the effect of behaviors of credit risk holders and the financial market regulators and the network structure are considered. By introducing the stochastic dominance theory, we discussed, respectively, the effect mechanisms of the degree of individual relationship, individual attitude to credit risk contagion, the individual ability to resist credit risk contagion, the monitoring strength of the financial market regulators, and the network structure on credit risk contagion. Then some derived and proofed propositions were verified through numerical simulations.

  4. Mathematical Modelling of Carbonitride Precipitation during Hot Working in Nb Microalloyed Steels

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Based on thermodynamics and kinetics, precipitation behavior of microalloyed steels was analyzed. Deformation greatly promotes isothermal carbonitride precipitation and makes C-curve shift leftwards. The position and shape of C-curve also depend on the content of Nb and N. C-curve shifts leftwards a little when N content increases and the nose temperature is raised with increasing Nb content. Deformation shortened precipitation start time during continuous cooling, raised precipitation start temperature, accelerated precipitation kinetics of carbonitrides. With decreasing the finishing temperature and coiling temperature, the precipitates volume fraction increases and strength increment is raised during hot rolling. The simulated results are in agreementwith experiment results.

  5. Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?: NUDGING AND MODEL SENSITIVITIES

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Guangxing [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Wan, Hui [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Zhang, Kai [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Qian, Yun [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Ghan, Steven J. [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA

    2016-07-10

    Efficient simulation strategies are crucial for the development and evaluation of high resolution climate models. This paper evaluates simulations with constrained meteorology for the quantification of parametric sensitivities in the Community Atmosphere Model version 5 (CAM5). Two parameters are perturbed as illustrating examples: the convection relaxation time scale (TAU), and the threshold relative humidity for the formation of low-level stratiform clouds (rhminl). Results suggest that the fidelity and computational efficiency of the constrained simulations depend strongly on 3 factors: the detailed implementation of nudging, the mechanism through which the perturbed parameter affects precipitation and cloud, and the magnitude of the parameter perturbation. In the case of a strong perturbation in convection, temperature and/or wind nudging with a 6-hour relaxation time scale leads to non-negligible side effects due to the distorted interactions between resolved dynamics and parameterized convection, while a 1-year free running simulation can satisfactorily capture the annual mean precipitation sensitivity in terms of both global average and geographical distribution. In the case of a relatively weak perturbation the large-scale condensation scheme, results from 1-year free-running simulations are strongly affected by noise associated with internal variability, while nudging winds effectively reduces the noise, and reasonably reproduces the response of precipitation and cloud forcing to parameter perturbation. These results indicate that caution is needed when using nudged simulations to assess precipitation and cloud forcing sensitivities to parameter changes in general circulation models. We also demonstrate that ensembles of short simulations are useful for understanding the evolution of model sensitivities.

  6. The International Trade Network: weighted network analysis and modelling

    International Nuclear Information System (INIS)

    Bhattacharya, K; Mukherjee, G; Manna, S S; Saramäki, J; Kaski, K

    2008-01-01

    Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network we argue that the scaled link weight distribution has an approximate log-normal distribution which remains robust over a period of 53 years. Another universal feature is observed in the power-law growth of the trade strength with gross domestic product, the exponent being similar for all countries. Using the 'rich-club' coefficient measure of the weighted networks it has been shown that the size of the rich-club controlling half of the world's trade is actually shrinking. While the gravity law is known to describe well the social interactions in the static networks of population migration, international trade, etc, here for the first time we studied a non-conservative dynamical model based on the gravity law which excellently reproduced many empirical features of the ITN

  7. Keystone Business Models for Network Security Processors

    OpenAIRE

    Arthur Low; Steven Muegge

    2013-01-01

    Network security processors are critical components of high-performance systems built for cybersecurity. Development of a network security processor requires multi-domain experience in semiconductors and complex software security applications, and multiple iterations of both software and hardware implementations. Limited by the business models in use today, such an arduous task can be undertaken only by large incumbent companies and government organizations. Neither the “fabless semiconductor...

  8. Stochastic modeling and analysis of telecoms networks

    CERN Document Server

    Decreusefond, Laurent

    2012-01-01

    This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an

  9. Decomposed Implicit Models of Piecewise - Linear Networks

    Directory of Open Access Journals (Sweden)

    J. Brzobohaty

    1992-05-01

    Full Text Available The general matrix form of the implicit description of a piecewise-linear (PWL network and the symbolic block diagram of the corresponding circuit model are proposed. Their decomposed forms enable us to determine quite separately the existence of the individual breakpoints of the resultant PWL characteristic and their coordinates using independent network parameters. For the two-diode and three-diode cases all the attainable types of the PWL characteristic are introduced.

  10. Artificial Immune Networks: Models and Applications

    Directory of Open Access Journals (Sweden)

    Xian Shen

    2008-06-01

    Full Text Available Artificial Immune Systems (AIS, which is inspired by the nature immune system, has been applied for solving complex computational problems in classification, pattern rec- ognition, and optimization. In this paper, the theory of the natural immune system is first briefly introduced. Next, we compare some well-known AIS and their applications. Several representative artificial immune networks models are also dis- cussed. Moreover, we demonstrate the applications of artificial immune networks in various engineering fields.

  11. Continuum Modeling of Biological Network Formation

    KAUST Repository

    Albi, Giacomo

    2017-04-10

    We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes the pressure field using a Darcy type equation and the dynamics of the conductance network under pressure force effects. Randomness in the material structure is represented by a linear diffusion term and conductance relaxation by an algebraic decay term. We first introduce micro- and mesoscopic models and show how they are connected to the macroscopic PDE system. Then, we provide an overview of analytical results for the PDE model, focusing mainly on the existence of weak and mild solutions and analysis of the steady states. The analytical part is complemented by extensive numerical simulations. We propose a discretization based on finite elements and study the qualitative properties of network structures for various parameter values.

  12. Adaptive-network models of collective dynamics

    Science.gov (United States)

    Zschaler, G.

    2012-09-01

    Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge

  13. Network Design Models for Container Shipping

    DEFF Research Database (Denmark)

    Reinhardt, Line Blander; Kallehauge, Brian; Nielsen, Anders Nørrelund

    This paper presents a study of the network design problem in container shipping. The paper combines the network design and fleet assignment problem into a mixed integer linear programming model minimizing the overall cost. The major contributions of this paper is that the time of a vessel route...... is included in the calculation of the capacity and that a inhomogeneous fleet is modeled. The model also includes the cost of transshipment which is one of the major cost for the shipping companies. The concept of pseudo simple routes is introduced to expand the set of feasible routes. The linearization...

  14. Modeling the relationship between precipitation and malaria incidence in children from a holoendemic area in Ghana.

    Science.gov (United States)

    Krefis, Anne Caroline; Schwarz, Norbert Georg; Krüger, Andreas; Fobil, Julius; Nkrumah, Bernard; Acquah, Samuel; Loag, Wibke; Sarpong, Nimako; Adu-Sarkodie, Yaw; Ranft, Ulrich; May, Jürgen

    2011-02-01

    Climatic factors influence the incidence of vector-borne diseases such as malaria. They modify the abundance of mosquito populations, the length of the extrinsic parasite cycle in the mosquito, the malarial dynamics, and the emergence of epidemics in areas of low endemicity. The objective of this study was to investigate temporal associations between weekly malaria incidence in 1,993 children < 15 years of age and weekly rainfall. A time series analysis was conducted by using cross-correlation function and autoregressive modeling. The regression model showed that the level of rainfall predicted the malaria incidence after a time lag of 9 weeks (mean = 60 days) and after a time lag between one and two weeks. The analyses provide evidence that high-resolution precipitation data can directly predict malaria incidence in a highly endemic area. Such models might enable the development of early warning systems and support intervention measures.

  15. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    Science.gov (United States)

    Tao, Wei-Kuo; Li, Xiaowen; Khain, Alexander; Matsui, Toshihisa; Lang, Stephen; Simpson, Joanne

    2012-01-01

    Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low clean concentration and a high dirty concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated.

  16. Modelling the regional climate and isotopic composition of Svalbard precipitation using REMOiso

    DEFF Research Database (Denmark)

    Divine..[], D.V.; Sjolte, Jesper; Isaksson, E.

    2011-01-01

    Simulations of a regional (approx. 50 km resolution) circulation model REMOiso with embedded stable water isotope module covering the period 1958-2001 are compared with the two instrumental climate and four isotope series (d18O) from western Svalbard. We examine the data from ice cores drilled...... than summer. The simulated and measured Holtedahlfonna d18O series agree reasonably well, whereas no significant correlation has been observed between the modelled and measured Lomonosovfonna ice core isotopic series. It is shown that sporadic nature as well as variability in the amount inherent...... in reproducing the local climate. The model successfully captures the climate variations on the daily to multidecadal times scales although it tends to systematically underestimate the winter SAT. Analysis suggests that REMOiso performs better at simulating isotope compositions of precipitation in the winter...

  17. Characterization and Modeling of Network Traffic

    DEFF Research Database (Denmark)

    Shawky, Ahmed; Bergheim, Hans; Ragnarsson, Olafur

    2011-01-01

    -arrival time, IP addresses, port numbers and transport protocol are the only necessary parameters to model network traffic behaviour. In order to recreate this behaviour, a complex model is needed which is able to recreate traffic behaviour based on a set of statistics calculated from the parameters values...

  18. Modelling and characterization of chi-phase grain boundary precipitation during aging of Fe-Cr-Ni-Mo stainless steel

    International Nuclear Information System (INIS)

    Xu, W.; San Martin, D.; Rivera Diaz del Castillo, P.E.J.; Zwaag, S. van der

    2007-01-01

    High molybdenum stainless steels may contain the chi-phase precipitate (χ, Fe 36 Cr 12 Mo 10 ) which may lead to undesirable effects on strength, toughness and corrosion resistance. In the present work, specimens of a 12Cr-9Ni-4Mo wt% steel are heat treated at different temperatures and times, and the average particle size and particle size distribution of chi-phase precipitate are studied quantitatively. A computer model based on the KWN framework has been developed to describe the evolution of chi-phase precipitation. The kinetic model takes advantage of the KWN model to describe the precipitate particle size distribution, and is coupled with the thermodynamic software ThermoCalc for calculating the instantaneous local thermodynamic equilibrium condition at the interface and the driving force for nucleation. A modified version of Zener's theory accounting for capillarity effects at early growth stages is implemented in this model. The prediction of the model for chi-phase precipitation at a grain boundary is compared to experimental results and both the average particle size and the particle size distribution are found to be in good agreement with experimental observations at late precipitation stages

  19. Phenomenological network models: Lessons for epilepsy surgery.

    Science.gov (United States)

    Hebbink, Jurgen; Meijer, Hil; Huiskamp, Geertjan; van Gils, Stephan; Leijten, Frans

    2017-10-01

    The current opinion in epilepsy surgery is that successful surgery is about removing pathological cortex in the anatomic sense. This contrasts with recent developments in epilepsy research, where epilepsy is seen as a network disease. Computational models offer a framework to investigate the influence of networks, as well as local tissue properties, and to explore alternative resection strategies. Here we study, using such a model, the influence of connections on seizures and how this might change our traditional views of epilepsy surgery. We use a simple network model consisting of four interconnected neuronal populations. One of these populations can be made hyperexcitable, modeling a pathological region of cortex. Using model simulations, the effect of surgery on the seizure rate is studied. We find that removal of the hyperexcitable population is, in most cases, not the best approach to reduce the seizure rate. Removal of normal populations located at a crucial spot in the network, the "driver," is typically more effective in reducing seizure rate. This work strengthens the idea that network structure and connections may be more important than localizing the pathological node. This can explain why lesionectomy may not always be sufficient. © 2017 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.

  20. Agent based modeling of energy networks

    International Nuclear Information System (INIS)

    Gonzalez de Durana, José María; Barambones, Oscar; Kremers, Enrique; Varga, Liz

    2014-01-01

    Highlights: • A new approach for energy network modeling is designed and tested. • The agent-based approach is general and no technology dependent. • The models can be easily extended. • The range of applications encompasses from small to large energy infrastructures. - Abstract: Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed

  1. Combined observational and modeling efforts of aerosol-cloud-precipitation interactions over Southeast Asia

    Science.gov (United States)

    Loftus, Adrian; Tsay, Si-Chee; Nguyen, Xuan Anh

    2016-04-01

    Low-level stratocumulus (Sc) clouds cover more of the Earth's surface than any other cloud type rendering them critical for Earth's energy balance, primarily via reflection of solar radiation, as well as their role in the global hydrological cycle. Stratocumuli are particularly sensitive to changes in aerosol loading on both microphysical and macrophysical scales, yet the complex feedbacks involved in aerosol-cloud-precipitation interactions remain poorly understood. Moreover, research on these clouds has largely been confined to marine environments, with far fewer studies over land where major sources of anthropogenic aerosols exist. The aerosol burden over Southeast Asia (SEA) in boreal spring, attributed to biomass burning (BB), exhibits highly consistent spatiotemporal distribution patterns, with major variability due to changes in aerosol loading mediated by processes ranging from large-scale climate factors to diurnal meteorological events. Downwind from source regions, the transported BB aerosols often overlap with low-level Sc cloud decks associated with the development of the region's pre-monsoon system, providing a unique, natural laboratory for further exploring their complex micro- and macro-scale relationships. Compared to other locations worldwide, studies of springtime biomass-burning aerosols and the predominately Sc cloud systems over SEA and their ensuing interactions are underrepresented in scientific literature. Measurements of aerosol and cloud properties, whether ground-based or from satellites, generally lack information on microphysical processes; thus cloud-resolving models are often employed to simulate the underlying physical processes in aerosol-cloud-precipitation interactions. The Goddard Cumulus Ensemble (GCE) cloud model has recently been enhanced with a triple-moment (3M) bulk microphysics scheme as well as the Regional Atmospheric Modeling System (RAMS) version 6 aerosol module. Because the aerosol burden not only affects cloud

  2. Delay and Disruption Tolerant Networking MACHETE Model

    Science.gov (United States)

    Segui, John S.; Jennings, Esther H.; Gao, Jay L.

    2011-01-01

    To verify satisfaction of communication requirements imposed by unique missions, as early as 2000, the Communications Networking Group at the Jet Propulsion Laboratory (JPL) saw the need for an environment to support interplanetary communication protocol design, validation, and characterization. JPL's Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE), described in Simulator of Space Communication Networks (NPO-41373) NASA Tech Briefs, Vol. 29, No. 8 (August 2005), p. 44, combines various commercial, non-commercial, and in-house custom tools for simulation and performance analysis of space networks. The MACHETE environment supports orbital analysis, link budget analysis, communications network simulations, and hardware-in-the-loop testing. As NASA is expanding its Space Communications and Navigation (SCaN) capabilities to support planned and future missions, building infrastructure to maintain services and developing enabling technologies, an important and broader role is seen for MACHETE in design-phase evaluation of future SCaN architectures. To support evaluation of the developing Delay Tolerant Networking (DTN) field and its applicability for space networks, JPL developed MACHETE models for DTN Bundle Protocol (BP) and Licklider/Long-haul Transmission Protocol (LTP). DTN is an Internet Research Task Force (IRTF) architecture providing communication in and/or through highly stressed networking environments such as space exploration and battlefield networks. Stressed networking environments include those with intermittent (predictable and unknown) connectivity, large and/or variable delays, and high bit error rates. To provide its services over existing domain specific protocols, the DTN protocols reside at the application layer of the TCP/IP stack, forming a store-and-forward overlay network. The key capabilities of the Bundle Protocol include custody-based reliability, the ability to cope with intermittent connectivity

  3. Evaluation of the TMPA-3B42 precipitation product using a high-density rain gauge network over complex terrain in northeastern Iberia

    KAUST Repository

    El Kenawy, Ahmed M.

    2015-08-29

    The performance of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA)-3B42 version 7 product is assessed over north-eastern Iberia, a region with considerable topographical gradients and complexity. Precipitation characteristics from a dense network of 656 rain gauges, spanning the period from 1998 to 2009, are used to evaluate TMPA-3B42 estimates on a daily scale. A set of accuracy estimators, including the relative bias, mean absolute error (MAE), root mean square error (RMSE) and Spearman coefficient was used to evaluate the results. The assessment indicates that TMPA-3B42 product is capable of describing the seasonal characteristics of the observed precipitation over most of the study domain. In particular, TMPA-3B42 precipitation agrees well with in situ measurements, with MAE less than 2.5mm.day-1, RMSE of 6.4mm.day-1 and Spearman correlation coefficients generally above 0.6. TMPA-3B42 provides improved accuracies in winter and summer, whereas it performs much worse in spring and autumn. Spatially, the retrieval errors show a consistent trend, with a general overestimation in regions of low altitude and underestimation in regions of heterogeneous terrain. TMPA-3B42 generally performs well over inland areas, while showing less skill in the coastal regions. A set of skill metrics, including a false alarm ratio [FAR], frequency bias index [FBI], the probability of detection [POD] and threat score [TS], is also used to evaluate TMPA performance under different precipitation thresholds (1, 5, 10, 25 and 50mm.day-1). The results suggest that TMPA-3B42 retrievals perform well in specifying moderate rain events (5-25mm.day-1), but show noticeably less skill in producing both light (<1mm.day-1) and heavy rainfall thresholds (more than 50mm.day-1). Given the complexity of the terrain and the associated high spatial variability of precipitation in north-eastern Iberia, the results reveal that TMPA-3B42 data provide an

  4. Evaluation of the TMPA-3B42 precipitation product using a high-density rain gauge network over complex terrain in northeastern Iberia

    KAUST Repository

    El Kenawy, Ahmed M.; Lopez-Moreno, Juan I.; McCabe, Matthew; Vicente-Serrano, Sergio M.

    2015-01-01

    The performance of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA)-3B42 version 7 product is assessed over north-eastern Iberia, a region with considerable topographical gradients and complexity. Precipitation characteristics from a dense network of 656 rain gauges, spanning the period from 1998 to 2009, are used to evaluate TMPA-3B42 estimates on a daily scale. A set of accuracy estimators, including the relative bias, mean absolute error (MAE), root mean square error (RMSE) and Spearman coefficient was used to evaluate the results. The assessment indicates that TMPA-3B42 product is capable of describing the seasonal characteristics of the observed precipitation over most of the study domain. In particular, TMPA-3B42 precipitation agrees well with in situ measurements, with MAE less than 2.5mm.day-1, RMSE of 6.4mm.day-1 and Spearman correlation coefficients generally above 0.6. TMPA-3B42 provides improved accuracies in winter and summer, whereas it performs much worse in spring and autumn. Spatially, the retrieval errors show a consistent trend, with a general overestimation in regions of low altitude and underestimation in regions of heterogeneous terrain. TMPA-3B42 generally performs well over inland areas, while showing less skill in the coastal regions. A set of skill metrics, including a false alarm ratio [FAR], frequency bias index [FBI], the probability of detection [POD] and threat score [TS], is also used to evaluate TMPA performance under different precipitation thresholds (1, 5, 10, 25 and 50mm.day-1). The results suggest that TMPA-3B42 retrievals perform well in specifying moderate rain events (5-25mm.day-1), but show noticeably less skill in producing both light (<1mm.day-1) and heavy rainfall thresholds (more than 50mm.day-1). Given the complexity of the terrain and the associated high spatial variability of precipitation in north-eastern Iberia, the results reveal that TMPA-3B42 data provide an

  5. A comprehensive Network Security Risk Model for process control networks.

    Science.gov (United States)

    Henry, Matthew H; Haimes, Yacov Y

    2009-02-01

    The risk of cyber attacks on process control networks (PCN) is receiving significant attention due to the potentially catastrophic extent to which PCN failures can damage the infrastructures and commodity flows that they support. Risk management addresses the coupled problems of (1) reducing the likelihood that cyber attacks would succeed in disrupting PCN operation and (2) reducing the severity of consequences in the event of PCN failure or manipulation. The Network Security Risk Model (NSRM) developed in this article provides a means of evaluating the efficacy of candidate risk management policies by modeling the baseline risk and assessing expectations of risk after the implementation of candidate measures. Where existing risk models fall short of providing adequate insight into the efficacy of candidate risk management policies due to shortcomings in their structure or formulation, the NSRM provides model structure and an associated modeling methodology that captures the relevant dynamics of cyber attacks on PCN for risk analysis. This article develops the NSRM in detail in the context of an illustrative example.

  6. Probability Modeling of Precipitation Extremes over Two River Basins in Northwest of China

    Directory of Open Access Journals (Sweden)

    Zhanling Li

    2015-01-01

    Full Text Available This paper is focused on the probability modeling with a range of distribution models over two inland river basins in China, together with the estimations of return levels on various return periods. Both annual and seasonal maximum precipitations (MP are investigated based on daily precipitation data at 13 stations from 1960 to 2010 in Heihe River and Shiyang River basins. Results show that GEV, Burr, and Weibull distributions provide the best fit to both annual and seasonal MP. Exponential and Pareto 2 distributions show the worst fit. The estimated return levels for spring MP show decreasing trends from the upper to the middle and then to the lower reaches totally speaking. Summer MP approximates to annual MP both in the quantity and in the spatial distributions. Autumn MP shows a little higher value in the estimated return levels than Spring MP, while keeping consistent with spring MP in the spatial distribution. It is also found that the estimated return levels for annual MP derived from various distributions differ by 22%, 36%, and 53% on average at 20-year, 50-year, and 100-year return periods, respectively.

  7. Circulation controls on southern African precipitation in coupled models: The role of the Angola Low

    Science.gov (United States)

    Munday, Callum; Washington, Richard

    2017-01-01

    In southern Africa, models from the latest Coupled Model Intercomparison Project produce a wide variety of rainfall climatologies. Differences between models in rainfall amount reach 70% in the rainy season (December-February; DJF), and the median model overestimates rainfall by between 15 and 40% throughout the annual cycle. This paper investigates the role of an understudied regional circulation feature, the Angola Low, in differentiating between model estimates of precipitation. In austral spring, the Angola Low is a heat low, driven by strong surface heating whereas in DJF it is more similar to a tropical low and is associated with moist instability. In the austral summer, we find that the simulated strength of the Angola Low is associated with between 40 and 60% of the intermodel variability in model mean rainfall across the subcontinent. The relationship is particularly strong along a northwest, southeast axis aligned from Angola down to the Mozambican Channel. Along this axis, models with stronger Angola Lows simulate enhanced, by up to 50 g kg-1 ms-1, northeasterly and northwesterly moisture transport. The enhanced southward moisture flux in models with relatively deep Angola Lows increases the rate of moisture convergence in central areas of the subcontinent and reduces moisture divergence across the Mozambican coast. The results highlight the need to better understand the links between the Angola Low and southern African rainfall and suggest that improving the simulation of the Angola Low can help to constrain model estimates of southern African rainfall.

  8. A Study of Precipitation Climatology and Its Variability over Europe Using an Advanced Regional Model (WRF)

    KAUST Repository

    Dasari, Hari Prasad

    2015-03-06

    In recent years long-term precipitation trends on a regional scale have been given emphasis due to the impacts of global warming on regional hydrology. In this study, regional precipitation trends are simulated over the Europe continent for a 60-year period in 1950-2010 using an advanced regional model, WRF, to study extreme precipitation events over Europe. The model runs continuously for each year during the period at a horizontal resolution of 25 km with initial/ boundary conditions derived from the National Center for Environmental Prediction (NCEP) 2.5 degree reanalysis data sets. The E-OBS 0.25 degree rainfall observation analysis is used for model validation. Results indicate that the model could reproduce the spatial annual rainfall pattern over Europe with low amounts (250 - 750 mm) in Iberian Peninsula, moderate to large amounts (750 - 1500 mm) in central, eastern and northeastern parts of Europe and extremely heavy falls (1500 - 2000 mm) in hilly areas of Alps with a slight overestimation in Alps and underestimation in other parts of Europe. The regional model integrations showed increasing errors (mean absolute errors) and decreasing correlations with increasing time scale (daily to seasonal). Rainfall is simulated relatively better in Iberian Peninsula, northwest and central parts of Europe. A large spatial variability with the highest number of wet days over eastern, central Europe and Alps (~200 days/year) and less number of wet days over Iberian Peninsula (≤150 days/year) is also found in agreement with observations. The model could simulate the spatial rainfall climate variability reasonably well with low rainfall days (1 - 10 mm/days) in almost all zones, heavy rainfall events in western, northern, southeastern hilly and coastal zones and extremely heavy rainfall events in northern coastal zones. An increasing trend of heavy rainfall in central, southern and southeastern parts, a decreasing trend in Iberian Peninsula and a steady trend in other

  9. The new Passive microwave Neural network Precipitation Retrieval (PNPR algorithm for the cross-track scanning ATMS radiometer: description and verification study over Europe and Africa using GPM and TRMM spaceborne radars

    Directory of Open Access Journals (Sweden)

    P. Sanò

    2016-11-01

    Full Text Available The objective of this paper is to describe the development and evaluate the performance of a completely new version of the Passive microwave Neural network Precipitation Retrieval (PNPR v2, an algorithm based on a neural network approach, designed to retrieve the instantaneous surface precipitation rate using the cross-track Advanced Technology Microwave Sounder (ATMS radiometer measurements. This algorithm, developed within the EUMETSAT H-SAF program, represents an evolution of the previous version (PNPR v1, developed for AMSU/MHS radiometers (and used and distributed operationally within H-SAF, with improvements aimed at exploiting the new precipitation-sensing capabilities of ATMS with respect to AMSU/MHS. In the design of the neural network the new ATMS channels compared to AMSU/MHS, and their combinations, including the brightness temperature differences in the water vapor absorption band, around 183 GHz, are considered. The algorithm is based on a single neural network, for all types of surface background, trained using a large database based on 94 cloud-resolving model simulations over the European and the African areas. The performance of PNPR v2 has been evaluated through an intercomparison of the instantaneous precipitation estimates with co-located estimates from the TRMM Precipitation Radar (TRMM-PR and from the GPM Core Observatory Ku-band Precipitation Radar (GPM-KuPR. In the comparison with TRMM-PR, over the African area the statistical analysis was carried out for a 2-year (2013–2014 dataset of coincident observations over a regular grid at 0.5°  ×  0.5° resolution. The results have shown a good agreement between PNPR v2 and TRMM-PR for the different surface types. The correlation coefficient (CC was equal to 0.69 over ocean and 0.71 over vegetated land (lower values were obtained over arid land and coast, and the root mean squared error (RMSE was equal to 1.30 mm h−1 over ocean and 1.11 mm h−1 over

  10. Discrete dynamic modeling of cellular signaling networks.

    Science.gov (United States)

    Albert, Réka; Wang, Rui-Sheng

    2009-01-01

    Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

  11. Neural network modeling of associative memory: Beyond the Hopfield model

    Science.gov (United States)

    Dasgupta, Chandan

    1992-07-01

    A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying dynamics are used to store and associatively recall information, are described. In the first class of models, a hierarchical structure is used to store an exponentially large number of strongly correlated memories. The second class of models uses limit cycles to store and retrieve individual memories. A neurobiologically plausible